Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.21037/qims-2025-1378
Yan Qi, Yan Jiang, Haichao Liu, Long Li, Mengya Guo, Dongjing Zhou, Yupin Liu
Background: Spectral computed tomography (CT) vessel wall imaging can clearly visualize vessel wall structures, but its ability to depict fine features is limited. Small field-of-view (FOV) reconstruction technology helps improve image spatial resolution. This study sought to assess the technical efficacy of small-FOV vascular wall spectral imaging in enhancing vascular wall imaging quality compared to conventional normal-FOV imaging.
Methods: The data of 52 patients who underwent chest dual-energy CT (DECT) were retrospectively reviewed. Vascular wall spectral images were reconstructed using both small-FOV and normal-FOV protocols. Quantitatively, the contrast-to-noise ratios (CNRs) of the descending aorta between the vessel wall and periaortic fat/lumen of the small-FOV and normal-FOV groups were calculated and compared. Qualitatively, two radiologists independently evaluated the vessel wall clarity and edge smoothness of both groups. Wall thickness (WT) and descending aortic wall area (DAWA) were measured, and inter-observer intraclass correlation coefficients (ICCs) were calculated. These metrics were compared between the small-FOV and normal-FOV reconstruction groups, as well as between the patient groups with and without atherosclerotic risk factors.
Results: The small-FOV group had significantly high CNR values than the normal-FOV group (wall-lumen: 9.45±3.28 vs. 4.86±2.16; wall-perivascular fat: 5.63±2.89 vs. 3.88±2.09, both P<0.001). The qualitative analysis also indicated that the small-FOV images were superior to the normal-FOV images (P<0.05). There were no significant differences between the small-FOV and normal-FOV groups in terms of the WT and DAWA. The mean WT values of the small-FOV and normal-FOV groups were 2.11±0.28 and 2.14±0.30 mm (Observer 1), and 2.15±0.30 and 2.13±0.28 mm (Observer 2), respectively. The mean DAWA values of the small-FOV and normal-FOV groups were 148.57±37.45 and 148.04±35.57 mm2 (Observer 1), and 149.53±36.49 and 147.98±33.44 mm2 (Observer 2), respectively. The patients with atherosclerotic risk factors showed significantly greater WT on the small-FOV images, and larger DAWA on both the small-FOV and normal-FOV images (all P<0.05). The ICC values for WT were 0.93 and 0.97 for the normal-FOV and small-FOV groups, respectively, and those for DAWA were 0.97 and 0.98, respectively.
Conclusions: The small-FOV technique significantly improved the image quality of the vascular wall spectral images, demonstrating clinical potential for detailed vascular assessment.
背景：频谱计算机断层扫描（CT）血管壁成像可以清晰地显示血管壁结构，但其描绘精细特征的能力有限。小视场（FOV）重建技术有助于提高图像空间分辨率。本研究旨在评估小视场血管壁光谱成像与常规正常视场成像相比在提高血管壁成像质量方面的技术功效。方法：回顾性分析52例胸部双能CT （DECT）的临床资料。采用小视场和正常视场两种方法重建血管壁光谱图像。定量计算并比较小视距组和正常视距组降主动脉血管壁与主动脉周围脂肪/腔间的噪比（CNRs）。定性方面，两名放射科医生独立评估两组的血管壁清晰度和边缘平滑度。测量壁厚（WT）和降主动脉壁面积（DAWA），计算观察者间类内相关系数（ICCs）。这些指标在小视场重建组和正常视场重建组之间以及有和没有动脉粥样硬化危险因素的患者组之间进行了比较。结果：小视场组CNR值明显高于正常视场组(壁腔：9.45±3.28 vs. 4.86±2.16；壁周脂肪：5.63±2.89 vs. 3.88±2.09，均为P2（观察者1），149.53±36.49和147.98±33.44 mm2（观察者2）。具有动脉粥样硬化危险因素的患者在小视场图像上表现出更大的WT，在小视场和正常视场图像上表现出更大的DAWA（均为p）。结论：小视场技术显著提高了血管壁光谱图像的图像质量，为血管精细评估提供了临床潜力。
{"title":"Enhancing vascular wall assessment in computed tomography: image quality optimization via small-field-of-view vascular wall spectral images.","authors":"Yan Qi, Yan Jiang, Haichao Liu, Long Li, Mengya Guo, Dongjing Zhou, Yupin Liu","doi":"10.21037/qims-2025-1378","DOIUrl":"https://doi.org/10.21037/qims-2025-1378","url":null,"abstract":"<p><strong>Background: </strong>Spectral computed tomography (CT) vessel wall imaging can clearly visualize vessel wall structures, but its ability to depict fine features is limited. Small field-of-view (FOV) reconstruction technology helps improve image spatial resolution. This study sought to assess the technical efficacy of small-FOV vascular wall spectral imaging in enhancing vascular wall imaging quality compared to conventional normal-FOV imaging.</p><p><strong>Methods: </strong>The data of 52 patients who underwent chest dual-energy CT (DECT) were retrospectively reviewed. Vascular wall spectral images were reconstructed using both small-FOV and normal-FOV protocols. Quantitatively, the contrast-to-noise ratios (CNRs) of the descending aorta between the vessel wall and periaortic fat/lumen of the small-FOV and normal-FOV groups were calculated and compared. Qualitatively, two radiologists independently evaluated the vessel wall clarity and edge smoothness of both groups. Wall thickness (WT) and descending aortic wall area (DAWA) were measured, and inter-observer intraclass correlation coefficients (ICCs) were calculated. These metrics were compared between the small-FOV and normal-FOV reconstruction groups, as well as between the patient groups with and without atherosclerotic risk factors.</p><p><strong>Results: </strong>The small-FOV group had significantly high CNR values than the normal-FOV group (wall-lumen: 9.45±3.28 <i>vs</i>. 4.86±2.16; wall-perivascular fat: 5.63±2.89 <i>vs</i>. 3.88±2.09, both P<0.001). The qualitative analysis also indicated that the small-FOV images were superior to the normal-FOV images (P<0.05). There were no significant differences between the small-FOV and normal-FOV groups in terms of the WT and DAWA. The mean WT values of the small-FOV and normal-FOV groups were 2.11±0.28 and 2.14±0.30 mm (Observer 1), and 2.15±0.30 and 2.13±0.28 mm (Observer 2), respectively. The mean DAWA values of the small-FOV and normal-FOV groups were 148.57±37.45 and 148.04±35.57 mm<sup>2</sup> (Observer 1), and 149.53±36.49 and 147.98±33.44 mm<sup>2</sup> (Observer 2), respectively. The patients with atherosclerotic risk factors showed significantly greater WT on the small-FOV images, and larger DAWA on both the small-FOV and normal-FOV images (all P<0.05). The ICC values for WT were 0.93 and 0.97 for the normal-FOV and small-FOV groups, respectively, and those for DAWA were 0.97 and 0.98, respectively.</p><p><strong>Conclusions: </strong>The small-FOV technique significantly improved the image quality of the vascular wall spectral images, demonstrating clinical potential for detailed vascular assessment.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"241"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: The levator ani hiatus (LAH) area is closely associated with the occurrence and severity of pelvic organ prolapse (POP). However, no current data on the definition of normal hiatal dimensions in Chinese women have been published. This study aimed to assess the cut-off area of the LAH for the occurrence of objective and severe POP in Chinese women based on a retrospective cross-sectional study with a large sample.
Methods: Women from the Postpartum Clinic and Rehabilitation Center of the Pelvic Diseases and Urogynecologic Department of a tertiary hospital were recruited between May 2017 and November 2022. All women underwent Pelvic Organ Prolapse Quantification grading and three-dimensional pelvic floor ultrasonography examinations performed by experienced doctors. The LAH area was measured at resting and maximum Valsalva states using ultrasonography. The association between the hiatal areas and the stages of prolapse was analyzed using the univariant Chi-squared test and Wilcoxon rank sum test. Receiver operating characteristic curve analysis was used to obtain the cut-off area of the LAH for the occurrence of objective and severe POP.
Results: Overall, 1,633 women were recruited in this study. The hiatal area at rest showed a significant association with POP severity, especially in stages 1, 2, and 3. Larger hiatal areas at rest were correlated with more advanced prolapse stages. For the anterior vaginal wall, a cut-off hiatal area of 14.45 cm2 at rest yielded a sensitivity of 0.57 and a specificity of 0.65 [area under the curve (AUC): 0.65; 95% confidence interval (CI): 0.62-0.68] for significant objective POP, which was the smallest among the three pelvic zones. In cases involving the uterus or vaginal fornix, a cut-off hiatal area of 20.30 cm2 at rest achieved a sensitivity of 0.39 and a specificity of 0.75 (AUC: 0.57; 95% CI: 0.50-0.64) for severe POP, representing the largest cut-off among the three pelvic zones.
Conclusions: For Chinese women, we suggest a cut-off of 14.45 cm2 at rest for 'normal' LAH and the hiatal area of ≥20.30 cm2 at rest for a close correlation with severe POP.
{"title":"Three-dimensional pelvic floor ultrasound measuring levator ani hiatus area and its association with pelvic organ prolapse: a population based retrospective cross-sectional study in Chinese women.","authors":"Ling Mei, Dongmei Wei, Meiqin Zhang, Fengyuan Zou, Xiaoyu Niu","doi":"10.21037/qims-2025-1980","DOIUrl":"https://doi.org/10.21037/qims-2025-1980","url":null,"abstract":"<p><strong>Background: </strong>The levator ani hiatus (LAH) area is closely associated with the occurrence and severity of pelvic organ prolapse (POP). However, no current data on the definition of normal hiatal dimensions in Chinese women have been published. This study aimed to assess the cut-off area of the LAH for the occurrence of objective and severe POP in Chinese women based on a retrospective cross-sectional study with a large sample.</p><p><strong>Methods: </strong>Women from the Postpartum Clinic and Rehabilitation Center of the Pelvic Diseases and Urogynecologic Department of a tertiary hospital were recruited between May 2017 and November 2022. All women underwent Pelvic Organ Prolapse Quantification grading and three-dimensional pelvic floor ultrasonography examinations performed by experienced doctors. The LAH area was measured at resting and maximum Valsalva states using ultrasonography. The association between the hiatal areas and the stages of prolapse was analyzed using the univariant Chi-squared test and Wilcoxon rank sum test. Receiver operating characteristic curve analysis was used to obtain the cut-off area of the LAH for the occurrence of objective and severe POP.</p><p><strong>Results: </strong>Overall, 1,633 women were recruited in this study. The hiatal area at rest showed a significant association with POP severity, especially in stages 1, 2, and 3. Larger hiatal areas at rest were correlated with more advanced prolapse stages. For the anterior vaginal wall, a cut-off hiatal area of 14.45 cm<sup>2</sup> at rest yielded a sensitivity of 0.57 and a specificity of 0.65 [area under the curve (AUC): 0.65; 95% confidence interval (CI): 0.62-0.68] for significant objective POP, which was the smallest among the three pelvic zones. In cases involving the uterus or vaginal fornix, a cut-off hiatal area of 20.30 cm<sup>2</sup> at rest achieved a sensitivity of 0.39 and a specificity of 0.75 (AUC: 0.57; 95% CI: 0.50-0.64) for severe POP, representing the largest cut-off among the three pelvic zones.</p><p><strong>Conclusions: </strong>For Chinese women, we suggest a cut-off of 14.45 cm<sup>2</sup> at rest for 'normal' LAH and the hiatal area of ≥20.30 cm<sup>2</sup> at rest for a close correlation with severe POP.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"213"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12976565/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147445976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-29DOI: 10.21037/qims-2025-1215
Xiaoming Ding, Guang Chen, Yiwen Zhang, Weiwei Ying, Qingqing Zhu, Lisha He, Xiaoping Feng, Giuseppe Lanza, Rita Bella, Xianfang Lin
Background: Transcranial color-coded sonography (TCCS) is widely used to detect middle cerebral artery (MCA) stenosis in clinical settings; however, the image quality can be affected by temporal bone window acoustic transmission conditions. In this study, we evaluated the value of contrast-enhanced (CE)-TCCS for diagnosing MCA stenosis in patients with poor temporal bone windows.
Methods: In total, 77 patients with 154 MCA images were assessed. The clinical symptoms were classified as symptomatic (n=28, 36.4%) and asymptomatic (n=49, 63.6%). The flow velocity parameters of the MCA images were measured, including the peak systolic velocity (PSV), end diastolic velocity (EDV), and mean flow velocity (MFV), with computed tomography angiography (CTA) used as a reference. The best cutoff value for the various velocity parameters measured by CE-TCCS for diagnosing MCA stenosis and its severity was determined based on the maximum Youden's index through receiver operating characteristic (ROC) curve analysis.
Results: Symptomatic patients had a high prevalence of MCA stenosis [odds ratio (OR) =4.386; 95% confidence interval (CI): 1.110-17.324]. Out of the 154 MCA images with a poor temporal bone window under the TCCS modality, 133 (86.4%) had a good temporal bone window under the CE-TCCS modality. In the stenosis group, the PSV, EDV, and MFV values measured via CE-TCCS were significantly greater than those in the normal group (P<0.001). The flow velocity increases gradually with worsening stenosis severity (P<0.001). The optimal cutoff values for the mild stenosis and normal groups were as follows: PSV ≥173.5 cm/s (sensitivity: 96.7%, specificity: 95.2%), EDV ≥66.6 cm/s (sensitivity: 76.7%, specificity: 87.3%), MFV ≥102.5 cm/s (sensitivity: 83.3%, specificity: 95.2%); the optimal cutoff values for the moderate and mild stenosis were as follows: PSV ≥213 cm/s (sensitivity: 91.7%, specificity: 100%), EDV ≥84.5 cm/s (sensitivity: 83.3%, specificity: 80.0%), MFV ≥130.5 cm/s (sensitivity: 87.5%, specificity: 100%); the optimal cutoff values for the severe and moderate stenosis were as follows: PSV ≥261.5 cm/s (sensitivity: 93.8%, specificity: 100%), EDV ≥105 cm/s (sensitivity: 93.8%, specificity: 83.3%), MFV ≥159.5 cm/s (sensitivity: 93.8%, specificity: 95.8%).
Conclusions: CE-TCCS can enhance the temporal bone window visualization in patients with poor temporal window under TCCS, providing diagnostic value for varying degrees of MCA stenosis.
{"title":"Value of contrast-enhanced transcranial color-coded sonography for diagnosing middle cerebral artery stenosis in patients with poor temporal bone windows.","authors":"Xiaoming Ding, Guang Chen, Yiwen Zhang, Weiwei Ying, Qingqing Zhu, Lisha He, Xiaoping Feng, Giuseppe Lanza, Rita Bella, Xianfang Lin","doi":"10.21037/qims-2025-1215","DOIUrl":"https://doi.org/10.21037/qims-2025-1215","url":null,"abstract":"<p><strong>Background: </strong>Transcranial color-coded sonography (TCCS) is widely used to detect middle cerebral artery (MCA) stenosis in clinical settings; however, the image quality can be affected by temporal bone window acoustic transmission conditions. In this study, we evaluated the value of contrast-enhanced (CE)-TCCS for diagnosing MCA stenosis in patients with poor temporal bone windows.</p><p><strong>Methods: </strong>In total, 77 patients with 154 MCA images were assessed. The clinical symptoms were classified as symptomatic (n=28, 36.4%) and asymptomatic (n=49, 63.6%). The flow velocity parameters of the MCA images were measured, including the peak systolic velocity (PSV), end diastolic velocity (EDV), and mean flow velocity (MFV), with computed tomography angiography (CTA) used as a reference. The best cutoff value for the various velocity parameters measured by CE-TCCS for diagnosing MCA stenosis and its severity was determined based on the maximum Youden's index through receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>Symptomatic patients had a high prevalence of MCA stenosis [odds ratio (OR) =4.386; 95% confidence interval (CI): 1.110-17.324]. Out of the 154 MCA images with a poor temporal bone window under the TCCS modality, 133 (86.4%) had a good temporal bone window under the CE-TCCS modality. In the stenosis group, the PSV, EDV, and MFV values measured via CE-TCCS were significantly greater than those in the normal group (P<0.001). The flow velocity increases gradually with worsening stenosis severity (P<0.001). The optimal cutoff values for the mild stenosis and normal groups were as follows: PSV ≥173.5 cm/s (sensitivity: 96.7%, specificity: 95.2%), EDV ≥66.6 cm/s (sensitivity: 76.7%, specificity: 87.3%), MFV ≥102.5 cm/s (sensitivity: 83.3%, specificity: 95.2%); the optimal cutoff values for the moderate and mild stenosis were as follows: PSV ≥213 cm/s (sensitivity: 91.7%, specificity: 100%), EDV ≥84.5 cm/s (sensitivity: 83.3%, specificity: 80.0%), MFV ≥130.5 cm/s (sensitivity: 87.5%, specificity: 100%); the optimal cutoff values for the severe and moderate stenosis were as follows: PSV ≥261.5 cm/s (sensitivity: 93.8%, specificity: 100%), EDV ≥105 cm/s (sensitivity: 93.8%, specificity: 83.3%), MFV ≥159.5 cm/s (sensitivity: 93.8%, specificity: 95.8%).</p><p><strong>Conclusions: </strong>CE-TCCS can enhance the temporal bone window visualization in patients with poor temporal window under TCCS, providing diagnostic value for varying degrees of MCA stenosis.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"235"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-10DOI: 10.21037/qims-2025-392
Lingxiang Ma, Mei Jin, Bing Li, Xuning Huang, Meihua Chen
Background: Early detection of the changes of left atrial (LA) structure and function in uremic patients after peritoneal dialysis (PD) treatment facilitates clinical evaluation and early intervention. This study aimed to construct a model using the four-dimensional automatic LA quantification technique (4D-LAQ) to evaluate the impact of PD on the left atrium of patients with chronic kidney disease stage 5 (CKD-5).
Methods: This study included 109 patients with CKD-5 and 38 age- and gender-matched healthy volunteers. The required clinical and ultrasound parameters were collected from all participants. Continuous variables were expressed as mean ± standard deviation or median (interquartile range), whereas categorical variables were presented as frequency (percentage). Independent risk factors associated with PD treatment were identified using binary logistic regression analysis, which was also employed to construct a predictive model. The performance of this model was assessed using receiver operating characteristic (ROC) curve analysis, with the area under the curve (AUC) and its confidence interval (CI) calculated to quantify predictive accuracy. A P value <0.05 was considered statistically significant.
Results: (I) Compared with group n, the LA volume of CKD-5 patients was higher. (II) Compared with the PD group, maximum left atrial volume (LAVmax), left atrial pre-atrial contraction volume (LAVpreA), left atrial maximum volume index (LAVImax), and left atrial ejection volume (LAEV) in the CK5 stage (N-PD) group increased (P<0.05). (III) 4D-LAQ can be used to construct a risk model for predicting adverse cardiovascular events, for which LAVImax is an independent risk factor. (IV) LAVImax, New York Heart Association (NYHA) heart function classification ≥ II, and E/e' ≥14 combined had the largest AUC.
Conclusions: The 4D-LAQ technique can be used to evaluate the effect of PD on the left atrium of CKD-5 patients, and can predict the probability of adverse cardiovascular events in CKD-5 patients after PD.
{"title":"4D automatic left atrial quantification technology-recommended for evaluating the impact of peritoneal dialysis on the left atrium of chronic kidney disease stage 5 patients.","authors":"Lingxiang Ma, Mei Jin, Bing Li, Xuning Huang, Meihua Chen","doi":"10.21037/qims-2025-392","DOIUrl":"https://doi.org/10.21037/qims-2025-392","url":null,"abstract":"<p><strong>Background: </strong>Early detection of the changes of left atrial (LA) structure and function in uremic patients after peritoneal dialysis (PD) treatment facilitates clinical evaluation and early intervention. This study aimed to construct a model using the four-dimensional automatic LA quantification technique (4D-LAQ) to evaluate the impact of PD on the left atrium of patients with chronic kidney disease stage 5 (CKD-5).</p><p><strong>Methods: </strong>This study included 109 patients with CKD-5 and 38 age- and gender-matched healthy volunteers. The required clinical and ultrasound parameters were collected from all participants. Continuous variables were expressed as mean ± standard deviation or median (interquartile range), whereas categorical variables were presented as frequency (percentage). Independent risk factors associated with PD treatment were identified using binary logistic regression analysis, which was also employed to construct a predictive model. The performance of this model was assessed using receiver operating characteristic (ROC) curve analysis, with the area under the curve (AUC) and its confidence interval (CI) calculated to quantify predictive accuracy. A P value <0.05 was considered statistically significant.</p><p><strong>Results: </strong>(I) Compared with group n, the LA volume of CKD-5 patients was higher. (II) Compared with the PD group, maximum left atrial volume (LAVmax), left atrial pre-atrial contraction volume (LAVpreA), left atrial maximum volume index (LAVImax), and left atrial ejection volume (LAEV) in the CK5 stage (N-PD) group increased (P<0.05). (III) 4D-LAQ can be used to construct a risk model for predicting adverse cardiovascular events, for which LAVImax is an independent risk factor. (IV) LAVImax, New York Heart Association (NYHA) heart function classification ≥ II, and E/e' ≥14 combined had the largest AUC.</p><p><strong>Conclusions: </strong>The 4D-LAQ technique can be used to evaluate the effect of PD on the left atrium of CKD-5 patients, and can predict the probability of adverse cardiovascular events in CKD-5 patients after PD.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"227"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971368/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.21037/qims-2025-856
Wenbei Xu, Juan Long, Chenzi Wang, Meng Yu, Xiaohan Liu, Zhongxiao Liu, Chong Wang, Yang Wu, He Zhang, Aiyun Sun, Shuai Zhang, Chunfeng Hu, Kai Xu, Yankai Meng
Background: Overweight and obesity are significant risk factors for carotid atherosclerosis in patients with metabolic syndrome and type 2 diabetes mellitus, and carotid computed tomography angiography (CTA) plays a critical role in assessing vascular health. However, obese patients often require higher doses of radiation and contrast agents, which can pose risks. The deep learning image reconstruction with high setting (DLIR-H) algorithm offers the potential to enhance image quality while minimizing exposure. The objective of this study was to evaluate the effectiveness of the DLIR-H algorithm in improving CTA image quality under a triple-low scan protocol (low radiation dose, low contrast agent usage, and low injection rate) for overweight and obese patients [body mass index (BMI) >25 kg/m2], using dual-energy CTA (DE-CTA) and virtual monoenergetic images (VMIs) at 50 keV.
Methods: A prospective study was conducted involving 62 patients who were randomly assigned to either the control or experimental group. The experimental group used the adaptive statistical iterative reconstruction-V (ASIR-V) 50%, deep learning image reconstruction with low setting (DLIR-L), deep learning image reconstruction with medium setting (DLIR-M), and DLIR-H algorithms with reduced radiation exposure and contrast agent. Both objective and subjective image quality evaluations were conducted. The effective dose (ED), contrast agent dose, computed tomography values (CTV), standard deviation of the carotid artery vessels (SDV), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were calculated and compared at four anatomical regions: the aortic arch (AA), common carotid artery (CCA) origin, carotid bifurcation (CB), and internal carotid artery (ICA) origin.
Results: The DLIR-H algorithm demonstrated image quality comparable to that of the ASIR-V algorithm. The experimental group exhibited a 49.4% reduction in ED (calculated from the dose length product, DLP) and a 13.5% reduction in contrast agent usage compared to the control group. At the AA level, the DLIR-H group had a significantly lower CTV than the control group [561.90 (516.90, 661.00) vs. 649.30 (572.60, 745.50), P<0.05]. At the CCA level, the DLIR-H group demonstrated a significantly lower SDV than the control group [35.90 (29.20, 43.80) vs. 41.70 (35.90, 54.70), P<0.05]. Except for the CCA level, at other anatomical levels, the DLIR-H group showed significantly lower SDV compared with the ASIR-V 50%, DLIR-L, and DLIR-M groups (P<0.05). Additionally, the DLIR-H group exhibited higher CNR and SNR than the ASIR-V 50%, DLIR-L, and DLIR-M groups at several anatomical levels (P<0.05).
Conclusions: The DLIR-H algorithm significantly enhances image quality in CTA, reducing both radiation exposure and contrast agent usage in overweight and obese patients.
背景：超重和肥胖是代谢综合征和2型糖尿病患者颈动脉粥样硬化的重要危险因素，颈动脉ct血管造影（CTA）在评估血管健康方面起着至关重要的作用。然而，肥胖患者通常需要更高剂量的辐射和造影剂，这可能会带来风险。高设置深度学习图像重建（DLIR-H）算法提供了在最小化曝光的同时提高图像质量的潜力。本研究的目的是评估DLIR-H算法在三低扫描方案（低辐射剂量，低造影剂使用和低注射率）下对超重和肥胖患者[体重指数(BMI) >25 kg/m2]，使用双能CTA （DE-CTA）和虚拟单能图像（VMIs）在50 keV下改善CTA图像质量的有效性。方法：对62例患者进行前瞻性研究，随机分为对照组和实验组。实验组采用自适应统计迭代重建- v (ASIR-V) 50%、低设置深度学习图像重建（DLIR-L）、中设置深度学习图像重建（DLIR-M）和减少辐射暴露和造影剂的DLIR-H算法。对图像质量进行了客观和主观评价。计算并比较主动脉弓（AA）、颈总动脉（CCA）起始点、颈动脉分叉（CB）、颈内动脉（ICA）起始点4个解剖区域的有效剂量（ED）、造影剂剂量、ct值（CTV）、颈动脉血管标准差（SDV）、信噪比（CNR）和噪声比（SNR）。结果：DLIR-H算法的图像质量与ASIR-V算法相当。与对照组相比，实验组ED减少了49.4%（根据剂量长度乘积DLP计算），对比剂使用量减少了13.5%。在AA水平上，DLIR-H组CTV明显低于对照组[561.90（516.90,661.00）比649.30 (572.60,745.50),p41.70(35.90, 54.70)]，结论：DLIR-H算法显著提高了CTA图像质量，减少了超重和肥胖患者的辐射暴露和造影剂使用。
{"title":"Comparison of deep learning reconstruction and iterative reconstruction algorithms for virtual monoenergetic image quality in overweight and obese patients with triple-low scan protocol dual-energy carotid computed tomography angiography.","authors":"Wenbei Xu, Juan Long, Chenzi Wang, Meng Yu, Xiaohan Liu, Zhongxiao Liu, Chong Wang, Yang Wu, He Zhang, Aiyun Sun, Shuai Zhang, Chunfeng Hu, Kai Xu, Yankai Meng","doi":"10.21037/qims-2025-856","DOIUrl":"https://doi.org/10.21037/qims-2025-856","url":null,"abstract":"<p><strong>Background: </strong>Overweight and obesity are significant risk factors for carotid atherosclerosis in patients with metabolic syndrome and type 2 diabetes mellitus, and carotid computed tomography angiography (CTA) plays a critical role in assessing vascular health. However, obese patients often require higher doses of radiation and contrast agents, which can pose risks. The deep learning image reconstruction with high setting (DLIR-H) algorithm offers the potential to enhance image quality while minimizing exposure. The objective of this study was to evaluate the effectiveness of the DLIR-H algorithm in improving CTA image quality under a triple-low scan protocol (low radiation dose, low contrast agent usage, and low injection rate) for overweight and obese patients [body mass index (BMI) >25 kg/m<sup>2</sup>], using dual-energy CTA (DE-CTA) and virtual monoenergetic images (VMIs) at 50 keV.</p><p><strong>Methods: </strong>A prospective study was conducted involving 62 patients who were randomly assigned to either the control or experimental group. The experimental group used the adaptive statistical iterative reconstruction-V (ASIR-V) 50%, deep learning image reconstruction with low setting (DLIR-L), deep learning image reconstruction with medium setting (DLIR-M), and DLIR-H algorithms with reduced radiation exposure and contrast agent. Both objective and subjective image quality evaluations were conducted. The effective dose (ED), contrast agent dose, computed tomography values (CTV), standard deviation of the carotid artery vessels (SDV), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were calculated and compared at four anatomical regions: the aortic arch (AA), common carotid artery (CCA) origin, carotid bifurcation (CB), and internal carotid artery (ICA) origin.</p><p><strong>Results: </strong>The DLIR-H algorithm demonstrated image quality comparable to that of the ASIR-V algorithm. The experimental group exhibited a 49.4% reduction in ED (calculated from the dose length product, DLP) and a 13.5% reduction in contrast agent usage compared to the control group. At the AA level, the DLIR-H group had a significantly lower CTV than the control group [561.90 (516.90, 661.00) <i>vs.</i> 649.30 (572.60, 745.50), P<0.05]. At the CCA level, the DLIR-H group demonstrated a significantly lower SDV than the control group [35.90 (29.20, 43.80) <i>vs.</i> 41.70 (35.90, 54.70), P<0.05]. Except for the CCA level, at other anatomical levels, the DLIR-H group showed significantly lower SDV compared with the ASIR-V 50%, DLIR-L, and DLIR-M groups (P<0.05). Additionally, the DLIR-H group exhibited higher CNR and SNR than the ASIR-V 50%, DLIR-L, and DLIR-M groups at several anatomical levels (P<0.05).</p><p><strong>Conclusions: </strong>The DLIR-H algorithm significantly enhances image quality in CTA, reducing both radiation exposure and contrast agent usage in overweight and obese patients.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"233"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.21037/qims-2025-1161
Xi Li, Wenhan Hu, Yong Tang, Xinyue Mao, Chunmei Li, Zhaohuan Li, Mingliang Zuo, Lixue Yin, Yan Deng, Liqiang Deng
Background: Artificial intelligence (AI) characterizes thyroid nodules by automatically extracting features from ultrasound images, whereas elastography quantitatively assesses tissue stiffness to aid in discriminating between benign and malignant cases. This study systematically evaluated the diagnostic accuracy of combining AI with elastography in differentiating benign and malignant thyroid nodule.
Methods: A comprehensive literature search was conducted in the databases of PubMed, Embase, Web of Science, and the China National Knowledge Infrastructure (CNKI) using a predefined "subject + keyword" strategy to locate diagnostic studies on the combined use of elastography and AI in differentiating benign and malignant thyroid nodule. Diagnostic test performance was evaluated by generating summary receiver operating characteristic (SROC) curves and calculating pooled estimates of sensitivity and specificity. The methodological quality of the included studies was appraised using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Data analysis was performed using Review Manager 5.4 and Stata 17.
Results: A total of 19 studies comprising 4,655 ultrasound images of thyroid nodule were included. Compared with available technologies, the combination of AI and elastography demonstrated superior diagnostic performance for thyroid diseases, with a pooled sensitivity of 0.88 [95% confidence interval (CI): 0.84-0.91], a specificity of 0.91 (95% CI: 0.88-0.94), a diagnostic odds ratio (DOR) of 73.89 (95% CI: 40.49-134.85), and an area under the curve (AUC) of 0.95 (95% CI: 0.93-0.97).
Conclusions: AI combined with elastography has high diagnostic accuracy for thyroid nodule, and this promising technology is expected to be integrated into routine clinical practice to improve the diagnosis and prognosis of thyroid nodule.
{"title":"Artificial intelligence and elastography in diagnostic work-up of thyroid nodules: a systematic review and meta-analysis.","authors":"Xi Li, Wenhan Hu, Yong Tang, Xinyue Mao, Chunmei Li, Zhaohuan Li, Mingliang Zuo, Lixue Yin, Yan Deng, Liqiang Deng","doi":"10.21037/qims-2025-1161","DOIUrl":"https://doi.org/10.21037/qims-2025-1161","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) characterizes thyroid nodules by automatically extracting features from ultrasound images, whereas elastography quantitatively assesses tissue stiffness to aid in discriminating between benign and malignant cases. This study systematically evaluated the diagnostic accuracy of combining AI with elastography in differentiating benign and malignant thyroid nodule.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted in the databases of PubMed, Embase, Web of Science, and the China National Knowledge Infrastructure (CNKI) using a predefined \"subject + keyword\" strategy to locate diagnostic studies on the combined use of elastography and AI in differentiating benign and malignant thyroid nodule. Diagnostic test performance was evaluated by generating summary receiver operating characteristic (SROC) curves and calculating pooled estimates of sensitivity and specificity. The methodological quality of the included studies was appraised using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Data analysis was performed using Review Manager 5.4 and Stata 17.</p><p><strong>Results: </strong>A total of 19 studies comprising 4,655 ultrasound images of thyroid nodule were included. Compared with available technologies, the combination of AI and elastography demonstrated superior diagnostic performance for thyroid diseases, with a pooled sensitivity of 0.88 [95% confidence interval (CI): 0.84-0.91], a specificity of 0.91 (95% CI: 0.88-0.94), a diagnostic odds ratio (DOR) of 73.89 (95% CI: 40.49-134.85), and an area under the curve (AUC) of 0.95 (95% CI: 0.93-0.97).</p><p><strong>Conclusions: </strong>AI combined with elastography has high diagnostic accuracy for thyroid nodule, and this promising technology is expected to be integrated into routine clinical practice to improve the diagnosis and prognosis of thyroid nodule.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"252"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971365/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.21037/qims-2025-aw-2110
Junzhuo Chen, Fan Xu, Aixin Li, Xi Wang, Wei Wang, Hongjun Li
<p><strong>Background: </strong>Human immunodeficiency virus (HIV) infection can lead to HIV-associated neurocognitive disorders (HAND), among which asymptomatic neurocognitive impairment (ANI) represents a critical stage for early intervention. However, neuroimaging biomarkers with high sensitivity and specificity for ANI are lacking. The neurovascular coupling (NVC) characteristic in ANI remains unclear. This study aimed to investigate changes in cerebral blood flow (CBF), functional connectivity strength (FCS), and their coupling in patients with ANI under both resting-state and movie-watching conditions, and to evaluate the discriminative performance of multimodal neuroimaging indicators for ANI.</p><p><strong>Methods: </strong>This study enrolled 75 participants with HIV, including 41 with ANI and 34 who were cognitively normal (CN). All participants underwent multimodal magnetic resonance imaging (MRI), including T1-weighted imaging, arterial spin labeling (ASL), resting-state and movie-watching-state functional MRI (fMRI). CBF, FCS, and CBF-FCS coupling coefficients were calculated. Between-group differences were assessed using independent-samples t-tests, with adjustments for age and years of education, and multiple-comparison correction where applicable. Correlation analyses were conducted to explore their associations with cognitive and clinical indicators. Three machine learning (ML) models [K-Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machine (SVM)] with leave-one-out cross-validation were constructed to evaluate the classification performance of multimodal neuroimaging metrics for ANI, and SHapley Additive exPlanations (SHAP) were applied to quantify feature importance.</p><p><strong>Results: </strong>The ANI group exhibited abnormal CBF in multiple brain regions and abnormal FCS in both resting-state and movie-watching-state. At the whole-brain level, the CBF-FCS coupling reversed from weakly positive in the CN participants (resting-state: <i>r</i>=0.0348; movie-watching-state: <i>r</i>=0.0364) to weakly negative in the ANI participants (resting-state: <i>r</i>=-0.0283; movie-watching-state: <i>r</i>=-0.0354), and the coupling coefficients were significantly reduced in the ANI participants compared to the CN participants (resting-state: P=0.004; movie-watching-state: P<0.001). Among the ML models, the full multimodal feature set achieved optimal classification performance [KNN: area under the curve (AUC) =0.957; accuracy =0.890; sensitivity =0.980; specificity =0.790], and the movie-based combination "CBF + movie-FCS + movie CBF-FCS coupling" showed consistently high performance across the models (AUC =0.929-0.962). SHAP indicated that the movie-watching-state NVC contributed the most prominently to the prediction of ANI.</p><p><strong>Conclusions: </strong>Patients with ANI exhibit abnormal CBF, FCS, and NVC. Compared with the resting-state paradigm, the movie paradigm was more sensitive in detecting neural fun
{"title":"Altered neurovascular coupling in patients with human immunodeficiency virus-associated asymptomatic neurocognitive impairment: a multimodal magnetic resonance imaging study.","authors":"Junzhuo Chen, Fan Xu, Aixin Li, Xi Wang, Wei Wang, Hongjun Li","doi":"10.21037/qims-2025-aw-2110","DOIUrl":"https://doi.org/10.21037/qims-2025-aw-2110","url":null,"abstract":"<p><strong>Background: </strong>Human immunodeficiency virus (HIV) infection can lead to HIV-associated neurocognitive disorders (HAND), among which asymptomatic neurocognitive impairment (ANI) represents a critical stage for early intervention. However, neuroimaging biomarkers with high sensitivity and specificity for ANI are lacking. The neurovascular coupling (NVC) characteristic in ANI remains unclear. This study aimed to investigate changes in cerebral blood flow (CBF), functional connectivity strength (FCS), and their coupling in patients with ANI under both resting-state and movie-watching conditions, and to evaluate the discriminative performance of multimodal neuroimaging indicators for ANI.</p><p><strong>Methods: </strong>This study enrolled 75 participants with HIV, including 41 with ANI and 34 who were cognitively normal (CN). All participants underwent multimodal magnetic resonance imaging (MRI), including T1-weighted imaging, arterial spin labeling (ASL), resting-state and movie-watching-state functional MRI (fMRI). CBF, FCS, and CBF-FCS coupling coefficients were calculated. Between-group differences were assessed using independent-samples t-tests, with adjustments for age and years of education, and multiple-comparison correction where applicable. Correlation analyses were conducted to explore their associations with cognitive and clinical indicators. Three machine learning (ML) models [K-Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machine (SVM)] with leave-one-out cross-validation were constructed to evaluate the classification performance of multimodal neuroimaging metrics for ANI, and SHapley Additive exPlanations (SHAP) were applied to quantify feature importance.</p><p><strong>Results: </strong>The ANI group exhibited abnormal CBF in multiple brain regions and abnormal FCS in both resting-state and movie-watching-state. At the whole-brain level, the CBF-FCS coupling reversed from weakly positive in the CN participants (resting-state: <i>r</i>=0.0348; movie-watching-state: <i>r</i>=0.0364) to weakly negative in the ANI participants (resting-state: <i>r</i>=-0.0283; movie-watching-state: <i>r</i>=-0.0354), and the coupling coefficients were significantly reduced in the ANI participants compared to the CN participants (resting-state: P=0.004; movie-watching-state: P<0.001). Among the ML models, the full multimodal feature set achieved optimal classification performance [KNN: area under the curve (AUC) =0.957; accuracy =0.890; sensitivity =0.980; specificity =0.790], and the movie-based combination \"CBF + movie-FCS + movie CBF-FCS coupling\" showed consistently high performance across the models (AUC =0.929-0.962). SHAP indicated that the movie-watching-state NVC contributed the most prominently to the prediction of ANI.</p><p><strong>Conclusions: </strong>Patients with ANI exhibit abnormal CBF, FCS, and NVC. Compared with the resting-state paradigm, the movie paradigm was more sensitive in detecting neural fun","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"251"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971328/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.21037/qims-2025-1439
Chao Wang, Lei Zhang, Yancheng Song, Zhibin Pan, Guoce Li, Xiaodong Yuan, Fenghai Liu
<p><strong>Background: </strong>Dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) can be used to differentiate the glioma grade and characterize the high-perfusion cores of gliomas. However, the arterial input function (AIF) and gamma-variate fitting (GVF) can both derive perfusion metrics [e.g., the relative cerebral blood volume (rCBV)]. The study aimed to compare the consistency of the normalized rCBV (nrCBV) between AIF and GVF in adult-type gliomas with different grades and isocitrate dehydrogenase (IDH) statuses, and then investigated the efficiency of percentage of signal recovery (PSR) and gadolinium (Gd) leakage effects in evaluating adult-type gliomas.</p><p><strong>Methods: </strong>A total of 60 patients with preoperative adult-type gliomas [IDH-mutant (IDH<sup>M</sup>): 37 <i>vs.</i> IDH wild-type (IDH<sup>W</sup>): 23] were retrospectively imaged via DSC-PWI, which was processed to obtain the nrCBV via AIF (AIF-nrCBV) and GVF (GVF-nrCBV). IDH<sup>M</sup> includes adult-type gliomas with grade 2 [19] and grade 3 [18]. IDH<sup>W</sup> includes 23 adult-type gliomas with grade 4. The PSR was calculated from the raw time-signal intensity curve (TIC). T<sub>2</sub>* and T1 leakage effects derived from AIF were graded via a Likert scale (ranging from 0 to 3). The correlation and paired difference of nrCBV between AIF and GVF were analyzed by linear correlation analysis and Bland-Altman plots in adult-type gliomas with different grades and IDH statuses. Spearman correlation analysis was used to test the correlation between PSR and two leakage effects. The differences of PSR and both leakage effect in adult-type gliomas with different grades and IDH statuses (IDH<sup>M</sup> <i>vs.</i> IDH<sup>W</sup>) were evaluated by one-way analysis of variance and Fisher's exact test.</p><p><strong>Results: </strong>AIF-nrCBV was correlated with GVF-nrCBV in adult-type gliomas with different grades and IDH statuses (r=0.56-0.90, all P<0.01). However, the AIF slightly underestimated the nrCBV compared with the GVF in adult-type gliomas with grade 2 (-0.09±0.27) and IDH<sup>M</sup> (-0.04±0.32); conversely, the AIF slightly overestimated the nrCBV in adult-type gliomas with grades 3 (0.01±0.37), 4 (0.06±0.40), and IDH<sup>W</sup> (0.06±0.40). The PSR was negatively correlated with the point difference between two leakage effects (r=-0.64, P<0.001). The PSR of gliomas with grade 4 and IDH<sup>W</sup> was greater than that of those with grade 2 and IDH<sup>M</sup> (all P<0.05). Although the point difference in leakage effects was not significant between different grades and IDH statuses, the adult-type gliomas with high grades and IDH<sup>W</sup> were more prone to T<sub>2</sub>* and T<sub>1</sub> leakage.</p><p><strong>Conclusions: </strong>AIF-nrCBV is correlated with the GVF-nrCBV in adult-type gliomas, regardless of grades and IDH statuses; however, the grades and IDH statuses could affect the consistency of the nrCBV between AIF and
{"title":"Comparison of the normalized cerebral blood volume (CBV) between different models and evaluation of the efficacy of gadolinium leakage in evaluating preoperative adult-type gliomas.","authors":"Chao Wang, Lei Zhang, Yancheng Song, Zhibin Pan, Guoce Li, Xiaodong Yuan, Fenghai Liu","doi":"10.21037/qims-2025-1439","DOIUrl":"https://doi.org/10.21037/qims-2025-1439","url":null,"abstract":"<p><strong>Background: </strong>Dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) can be used to differentiate the glioma grade and characterize the high-perfusion cores of gliomas. However, the arterial input function (AIF) and gamma-variate fitting (GVF) can both derive perfusion metrics [e.g., the relative cerebral blood volume (rCBV)]. The study aimed to compare the consistency of the normalized rCBV (nrCBV) between AIF and GVF in adult-type gliomas with different grades and isocitrate dehydrogenase (IDH) statuses, and then investigated the efficiency of percentage of signal recovery (PSR) and gadolinium (Gd) leakage effects in evaluating adult-type gliomas.</p><p><strong>Methods: </strong>A total of 60 patients with preoperative adult-type gliomas [IDH-mutant (IDH<sup>M</sup>): 37 <i>vs.</i> IDH wild-type (IDH<sup>W</sup>): 23] were retrospectively imaged via DSC-PWI, which was processed to obtain the nrCBV via AIF (AIF-nrCBV) and GVF (GVF-nrCBV). IDH<sup>M</sup> includes adult-type gliomas with grade 2 [19] and grade 3 [18]. IDH<sup>W</sup> includes 23 adult-type gliomas with grade 4. The PSR was calculated from the raw time-signal intensity curve (TIC). T<sub>2</sub>* and T1 leakage effects derived from AIF were graded via a Likert scale (ranging from 0 to 3). The correlation and paired difference of nrCBV between AIF and GVF were analyzed by linear correlation analysis and Bland-Altman plots in adult-type gliomas with different grades and IDH statuses. Spearman correlation analysis was used to test the correlation between PSR and two leakage effects. The differences of PSR and both leakage effect in adult-type gliomas with different grades and IDH statuses (IDH<sup>M</sup> <i>vs.</i> IDH<sup>W</sup>) were evaluated by one-way analysis of variance and Fisher's exact test.</p><p><strong>Results: </strong>AIF-nrCBV was correlated with GVF-nrCBV in adult-type gliomas with different grades and IDH statuses (r=0.56-0.90, all P<0.01). However, the AIF slightly underestimated the nrCBV compared with the GVF in adult-type gliomas with grade 2 (-0.09±0.27) and IDH<sup>M</sup> (-0.04±0.32); conversely, the AIF slightly overestimated the nrCBV in adult-type gliomas with grades 3 (0.01±0.37), 4 (0.06±0.40), and IDH<sup>W</sup> (0.06±0.40). The PSR was negatively correlated with the point difference between two leakage effects (r=-0.64, P<0.001). The PSR of gliomas with grade 4 and IDH<sup>W</sup> was greater than that of those with grade 2 and IDH<sup>M</sup> (all P<0.05). Although the point difference in leakage effects was not significant between different grades and IDH statuses, the adult-type gliomas with high grades and IDH<sup>W</sup> were more prone to T<sub>2</sub>* and T<sub>1</sub> leakage.</p><p><strong>Conclusions: </strong>AIF-nrCBV is correlated with the GVF-nrCBV in adult-type gliomas, regardless of grades and IDH statuses; however, the grades and IDH statuses could affect the consistency of the nrCBV between AIF and","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"225"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971338/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Repeat misdiagnosis of chylous pneumonia: a case description.","authors":"Qiangjin Gong, Yuanyuan Wang, Sheng Xu, Cheng Yang, Huizhi Zhu, Yating Gao","doi":"10.21037/qims-2025-aw-2209","DOIUrl":"https://doi.org/10.21037/qims-2025-aw-2209","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"16 3","pages":"263"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971351/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.21037/qims-2025-1651
Tianshu Zhao, Haiyang Chen, Lan Lan, Juan Gao, Zhuo Chen, Jingyi He, Lizhi Xu, Haibo Xu, Chenxi Hu
<p><strong>Background: </strong>Free-breathing cardiac multi-parametric mapping is clinically important but requires accurate motion correction (MoCo). The clinical adoption of the dictionary-matching and low-rank (DM + LR) method remains limited due to computational bottlenecks and a lack of clinical validation. This study aimed to develop and validate a modified dictionary-matching and low-rank (mDM + LR) MoCo approach with improved computational efficiency and diagnostic performance in free-breathing cardiac T1/T2 mapping.</p><p><strong>Methods: </strong>This prospective study enrolled 130 patients with cardiac diseases and 23 healthy controls (HCs). All participants underwent cardiac magnetic resonance imaging (MRI) on a 3T scanner (uMR 790) using electrocardiogram-gated balanced Steady-State Free Precession (bSSFP)-based multimapping for joint T1/T2 mapping under free-breathing conditions. Breath-hold multimapping, Modified Look-Locker Inversion recovery (MOLLI), and T2 mapping served as reference standards in a subset of 19 patients. The mDM + LR MoCo method integrated a pre-trained multi-layer perceptron (MLP), trained on 12.5 million extended phase graph (EPG)-simulated samples, to map T1, T2, and RR-interval history to signals, reducing the runtime to ~25 seconds per sample. MoCo accuracy was evaluated against non-MoCo and parametric image registration with total variation-regularization (pTVreg) using quantitative metrics [Dice similarity coefficient (DSC) scores, mean contour distance (MCD) values, and relative dictionary-matching errors (RDMEs)], qualitative map scores assessed by two blinded readers, and T1/T2 quantification accuracy via correlation and Bland-Altman analyses against breath-hold references. Diagnostic performance (i.e., sensitivity, specificity, and accuracy) was assessed using thresholds derived from HC breath-hold data. Statistical analyses included the Shapiro-Wilk test, <i>t</i>-test or Mann-Whitney <i>U</i> test, Wilcoxon signed-rank test, intraclass correlation coefficients (ICCs), and Bonferroni correction (significance: P<0.05).</p><p><strong>Results: </strong>In the patients, mDM + LR outperformed non-MoCo and pTVreg in quantitative metrics such as DSC scores (78.0%±7.6% <i>vs.</i> 61.4%±13.3% and 74.5%±11.2%), MCD values (1.20±0.40 <i>vs.</i> 2.41±1.12 and 1.48±0.72 voxels), and RDMEs (8.4%±2.3% <i>vs.</i> 14.6%±3.9% and 9.9%±3.0%), as well as qualitative scores such as map quality scores (T1/T2: 4.65±0.58/4.69±0.49 <i>vs.</i> 3.72±0.81/3.56±0.75 and 3.76±0.78/3.87±0.75, all P<0.01). The mDM + LR method also resulted in higher correlations between global T1/T2 values and breath-holding reference values (r=0.81/0.80 <i>vs.</i> 0.53/0.46 and 0.70/0.64), improved diagnostic specificity (93%/100% <i>vs.</i> 21%/69% and 64%/81%), and improved diagnostic accuracy (89%/100% <i>vs.</i> 42%/74% and 68%/84%). No statistically significant difference was observed between the DM + LR and mDM + LR results. The processing
背景：自由呼吸心脏多参数测绘在临床上很重要，但需要精确的运动校正（MoCo）。由于计算瓶颈和缺乏临床验证，字典匹配和低秩（DM + LR）方法的临床应用仍然有限。本研究旨在开发和验证一种改进的字典匹配和低秩（mDM + LR） MoCo方法，该方法可以提高自由呼吸心脏T1/T2制图的计算效率和诊断性能。方法：本前瞻性研究纳入了130例心脏病患者和23例健康对照（hc）。所有参与者在3T扫描仪（uMR 790）上使用基于心电图门控平衡稳态自由进动（bSSFP）的多映射进行心脏磁共振成像（MRI），在自由呼吸条件下进行关节T1/T2映射。屏气多映射、改良Look-Locker反转恢复（MOLLI）和T2映射作为19例患者的参考标准。mDM + LR MoCo方法集成了一个预先训练的多层感知器（MLP），该感知器在1250万个扩展相位图（EPG）模拟样本上进行训练，将T1、T2和rr间隔历史映射到信号，将每个样本的运行时间减少到约25秒。采用定量指标（Dice similarity coefficient， DSC）评分、平均轮廓距离（mean contour distance， MCD）值和相对字典匹配误差（relative字典匹配误差，RDMEs）评估MoCo精度与非MoCo精度和参数化图像配准（total variation-regularization, pTVreg），两名盲法读者评估定性地图评分，以及通过相关分析和Bland-Altman分析对呼吸参考进行T1/T2量化精度评估。诊断性能（即敏感性、特异性和准确性）使用HC屏气数据得出的阈值进行评估。统计分析包括Shapiro-Wilk检验、t检验或Mann-Whitney U检验、Wilcoxon符号秩检验、类内相关系数（ICCs）和Bonferroni校正(显著性：在患者中，mDM + LR在定量指标如DSC评分（78.0%±7.6%比61.4%±13.3%和74.5%±11.2%）、MCD值（1.20±0.40比2.41±1.12和1.48±0.72体素）、rdme（8.4%±2.3%比14.6%±3.9%和9.9%±3.0%）以及定性评分如地图质量评分(T1/T2：（4.65±0.58/4.69±0.49 vs. 3.72±0.81/3.56±0.75和3.76±0.78/3.87±0.75，均为0.53/0.46和0.70/0.64），提高了诊断特异性（93%/100% vs. 21%/69%和64%/81%），提高了诊断准确性（89%/100% vs. 42%/74%和68%/84%）。DM + LR与mDM + LR结果无统计学差异。每个样本的mDM + LR处理时间约为25秒。结论：mDM + LR可显著提高自由呼吸多参数制图的MoCo、定量准确性和诊断性能，可应用于临床。
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