Quantitative Imaging in Medicine and Surgery最新文献

Background: Pancreatic cystic lesions (PCLs) are recommended to be examined by magnetic resonance imaging (MRI), yet MRI still has limitations, such as high costs, the risk of triggering claustrophobia, and relatively low availability compared with ultrasound. Oral contrast agents-assisted ultrasound has been used to examine the gallbladder and stomach, but whether oral contrast agents could improve the accuracy of transabdominal ultrasound (TAUS) for PCLs and could be a potential alternative to non-contrast MRI for PCL follow-up has not been studied. This study aimed to explore the value of cereal-based oral contrast agents in improving the accuracy of PCLs during TAUS.

Methods: This is a prospective cohort study. Patients with PCL who were admitted to our center between January 2023 and January 2024 were enrolled, and TAUS was performed before and after taking cereal-based oral contrast agents. The imaging quality of the PCL was measured by structural visualization scores. The structural visualization scores of oral contrast agent-assisted ultrasound and non-contrast MRI were also compared.

Results: A total of 27 patients with PCLs were enrolled, and 30 PCLs were detected. The sonolucency of the PCL improved after oral contrast agent administration. Before taking the agent, only 30% of patients had satisfactory sonolucency; after taking the oral contrast agent, the corresponding proportion reached 80% (P=0.002). The structural visualization score of the PCL determined by oral contrast agent-assisted TAUS was higher than that determined without the aid of an agent [1 (0-6) vs. 1 (0-3), P=0.001], which was mainly reflected in the increase in the number of visible septa after taking the agent. No significant difference was detected between the structural visualization score of the PCL examined by oral contrast agent-assisted TAUS and that examined by non-contrast MRI and the correlation between the 2 types of scores were satisfactory [1 (0-6) vs. 2 (0-7), P=0.070, Spearman correlation factor r=0.880].

Conclusions: This study used a structured scoring system to confirm that cereal-based oral contrast agents could improve the ultrasound quality of PCLs, and the correlation between the quality of oral contrast agent-assisted ultrasound and non-contrast MRI findings on PCLs was satisfactory. Further research to improve visualization of PCLs on TAUS using oral contrast agents could result in TAUS being a potential alternative to MRI in the follow-up of PCLs in resource-limited situations.

Benign thyroid nodules are significantly common and occur in 50-60% of the population. Therefore, differentiation from malignant nodes and the choice of treatment tactics in some cases of benign pathology remain relevant. Despite advances in the clinical evaluation of thyroid nodules, methodological challenges exist due to empirically simplistic understandings of the nodular process. Different opinions on the pathogenesis of thyroid nodules and the history of the formation of the idea of ​​the stages of nodules are considered. For the first time, based on natural principles and many years of ultrasound analysis of changes in benign thyroid nodules, three stages of the nodular process were identified: Development, Wasting and Scarring. The stage of exhaustion has three substages: Initial, Moderate and Significant Wasting. The principles of stage-by-stage changes in nodules are explained and their ultrasound signs are shown. The key principle of the stages of nodules is the ratio of the magnitudes of the processes of regeneration (proliferation) and destruction in the nodule. Separate stage changes may occur in node segments. In such cases, part of the segments may show signs of the Development stage, another part-Wasting, and the third part-Scarring. The different variants of thyroid nodules are explained in terms of stages. Practical recommendations for differentiating ultrasound signs of nodules associated with stages are proposed. Knowledge about the staged changes in thyroid nodules helps reduce the likelihood of diagnostic errors, better navigate the prognosis and choice of treatment tactics, and recommend preventive ultrasound examination of the thyroid.

Background: The integration of artificial intelligence (AI) into medicine is growing, with some experts predicting its standalone use soon. However, skepticism remains due to limited positive outcomes from independent validations. This research evaluates AI software's effectiveness in analyzing chest X-rays (CXR) to identify lung nodules, a possible lung cancer indicator.

Methods: This retrospective study analyzed 7,670,212 record pairs from radiological exams conducted between 2020 and 2022 during the Moscow Computer Vision Experiment, focusing on CXR and computed tomography (CT) scans. All images were acquired during clinical routine. The final dataset comprised 100 CXR images (50 with lung nodules, 50 without), selected consecutively and based on inclusion and exclusion criteria, to evaluate the performance of all five AI-based solutions, participating in the Moscow Computer Vision Experiment and analyzing CXR. The evaluation was performed in 3 stages. In the first stage, the probability of a nodule in the lung obtained from AI services was compared with the Ground Truth (1-there is a nodule, 0-there is no nodule). In the second stage, 3 radiologists evaluated the segmentation of nodules performed by the AI services (1-nodule correctly segmented, 0-nodule incorrectly segmented or not segmented at all). In the third stage, the same radiologists additionally evaluated the classification of the nodules (1-nodule correctly segmented and classified, 0-all other cases). The results obtained in stages 2 and 3 were compared with Ground Truth, which was common to all three stages. For each stage, diagnostic accuracy metrics were calculated for each AI service.

Results: Three software solutions (Celsus, Lunit INSIGHT CXR, and qXR) demonstrated diagnostic metrics that matched or surpassed the vendor specifications, and achieved the highest area under the receiver operating characteristic curve (AUC) of 0.956 [95% confidence interval (CI): 0.918 to 0.994]. However, when evaluated by three radiologists for accurate nodule segmentation and classification, all solutions performed below the vendor-declared metrics, with the highest AUC reaching 0.812 (95% CI: 0.744 to 0.879). Meanwhile, all AI services demonstrated 100% specificity at stages 2 and 3 of the study.

Conclusions: To ensure the reliability and applicability of AI-based software, it is crucial to validate performance metrics using high-quality datasets and engage radiologists in the evaluation process. Developers are recommended to improve the accuracy of the underlying models before allowing the standalone use of the software for lung nodule detection. The dataset created during the study may be accessed at https://mosmed.ai/datasets/mosmeddatargogksnalichiemiotsutstviemlegochnihuzlovtipvii/.

Background: Three-dimensional pseudo-continuous arterial spin-labeling (3D pCASL) with dual postlabeling delay (PLD) captures both early and delayed cerebral blood flow (CBF), yet its potential in reflecting blood flow regulation in hydrocephalus patients remains uncertain. This study investigated the hemodynamic characteristics in patients with hydrocephalus and whether the difference in cerebral blood flow using short and long PLDs (ΔCBF = CBFPLD =2.5 s - CBFPLD =1.5 s) could reflect cerebral regulation and further aimed to demonstrate the associations between regional ΔCBF and the degree of ventricular dilatation.

Methods: This retrospective study included consecutive patients with hydrocephalus and control participants attending The Second Affiliated Hospital of Nanchang University from December 2017 to December 2022. The CBF in 18 brain regions was manually delineated by two radiologists. Regional CBF and ΔCBF were compared via covariance analyses. The associations between ΔCBF and the degree of ventricular dilatation were investigated using linear regression analyses and interaction analysis.

Results: In total, 58 patients with communicating hydrocephalus, 57 patients with obstructive hydrocephalus, and 52 controls were analyzed. CBF of the hydrocephalus groups was lower than that of the control group at the shorter PLD. CBF was higher at a longer PLD, with no difference between the hydrocephalus groups and the control group in some regions. The hydrocephalus groups showed a higher ΔCBF compared to the control group. Furthermore, in the left medial watershed (10.6±5.66 vs. 7.01±5.88 mL/100 g/min; P=0.038), communicating hydrocephalus exhibited greater ΔCBF than did obstructive hydrocephalus. ΔCBF of the right posterior external watershed [adjusted β: 0.276; 95% confidence interval (CI): 0.047-0.505; P=0.019] and right parietal cortex (adjusted β: 0.277; 95% CI: 0.056-0.498; P=0.015) in the obstructive hydrocephalus group and ΔCBF of the left internal watershed (adjusted β: 0.274; 95% CI: 0.013-0.536; P=0.040) in the communicating hydrocephalus group were associated with the degree of ventricular dilatation, respectively.

Conclusions: Patients with hydrocephalus showed cerebral regulation in maintaining adequate CBF, resulting in longer arterial transit times. The ability to regulate CBF in brain regions represented by the watershed was associated with the degree of ventricular dilation.

Background: The musculoskeletal system participates in the pathology of metabolic disorders. Several studies have focused on body composition changes; however, the adipose tissue between muscle bundles with different metabolic statuses has rarely been studied. This study sought to explore the association between body compositions and metabolic disorders in Asians, and identify whether these body compositions can be used to detect metabolic disorders with different waist circumferences (WCs) by computed tomography (CT).

Methods: A total of 116 subjects were included in the study and categorized into the following four groups according to WC and metabolic syndrome (MS): (I) the healthy control group; (II) the normal WC with metabolic disorder group; (III) the normal WC with MS group; and (IV) the larger WC with MS group. The International Diabetes Federation (IDF) criteria based on WC, laboratory tests, body mass index (BMI), and medical history was used to diagnose MS. Body composition parameters, such as muscle attenuation, the cross-sectional area of subcutaneous adipose tissue (SAT), muscle, extramyocellular lipid (EMCL), visceral adipose tissue (VAT), and the ratios between different compositions [e.g., the SMR (SAT/muscle), EMR (EMCL/muscle), and VMR (VAT/muscle)] were calculated for the thigh and abdomen. The areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves adjusted for multiple comparisons were used to discriminate among metabolic disorders.

Results: The groups with metabolic disorders had more SAT (P=0.001) and EMCL (P=0.040) in the thigh, and more VAT (P=0.001) and a higher SMR (P<0.001) in the abdomen. EMCL and muscle attenuation in the thigh (AUCs =0.790 and 0.791), and the VMR and SMR in the abdomen were better able to diagnose metabolic disorders (AUCs =0.752 and 0.746) than other body composition parameters. While SAT and EMCL in the thigh (AUCs =0.768 and 0.760), and VAT and the VMR in the abdomen (AUCs =0.788 and 0.775) were better able to diagnose MS than other parameters.

Conclusions: Body composition parameters for the thigh and abdomen could assist in detecting patients with an increased risk of MS.

Background: Changes in both the vascular system and brain tissues can occur after a prior episode of coronavirus disease 2019 (COVID-19), detectable through modifications in diffusion parameters using magnetic resonance imaging (MRI) techniques. These changes in diffusion parameters may be particularly prominent in highly organized structures such as the corpus callosum (CC), including its major components, which have not been adequately studied following COVID-19 infection. Therefore, the study aimed to evaluate microstructural changes in whole-brain (WB) diffusion, with a specific focus on the CC.

Methods: A total of 101 probands (age range from 18 to 69 years) participated in this retrospective study, consisting of 55 volunteers and 46 post-COVID-19 patients experiencing neurological symptoms. The participants were recruited from April 2022 to September 2023 at the Institute for Clinical and Experimental Medicine in Prague, Czech Republic. All participants underwent MRI examinations on a 3T MR scanner with a diffusion protocol, complemented by additional MRI techniques. Two volunteers and five patients were excluded from the study due to motion artefacts, severe hypoperfusion or the presence of lesions. Participants were selected by a neurologist based on clinical examination and a serological test for COVID-19 antibodies. They were then divided into three groups: a control group of healthy volunteers (n=28), an asymptomatic group (n=25) with a history of infection but no symptoms, and a symptomatic group (n=41) with a history of COVID-19 and neurological symptoms. Symptomatic patients did not exhibit neurological symptoms before contracting COVID-19. Diffusion data underwent eddy current and susceptibility distortion corrections, and fiber tracking was performed using default parameters in DSI studio. Subsequently, various diffusion metrics, were computed within the reconstructed tracts of the WB and CC. To assess the impact of COVID-19 and its associated symptoms on diffusion indices within the white matter of the WB and CC regions, while considering age, we employed a statistical analysis using a linear mixed-effects model within the R framework.

Results: Statistical analysis revealed a significant difference in mean diffusivity (MD) between the symptomatic and control groups in the forceps minor (P=0.001) and CC body (P=0.003). In addition to changes in diffusion, alterations in brain perfusion were observed in two post-COVID-19 patients who experienced a severe course. Furthermore, hyperintense lesions were identified in subcortical and deep white matter areas in the vast majority of symptomatic patients.

Conclusions: The main finding of our study was that post-COVID-19 patients exhibit increased MD in the forceps minor and body of the CC. This finding suggests a potential association between microstructural brain changes in post-COVID-19 patients and

Background: Accurately and promptly predicting the response of gastrointestinal stromal tumors (GISTs) to targeted therapy is essential for optimizing treatment strategies. However, some fractions of recurrent or metastatic GISTs present as non-FDG-avid lesions, limiting the value of [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography ([¹⁸F]FDG PET/CT) in treatment evaluation. This study evaluated the efficacy of [¹⁸F]F-fibroblast activation protein inhibitor (FAPI)-42 [¹⁸F]FAPI-42) PET/CT for assessing the treatment response in recurrent or metastatic GISTs, in comparison to [¹⁸F]FDG PET/CT and explores a model integrating PET/CT imaging and clinical parameters to optimize the clinical use of these diagnostic tools.

Methods: Our retrospective analysis included 27 patients with recurrent or metastatic GISTs who underwent [¹⁸F]FAPI-42 PET/CT and [¹⁸F]FDG PET/CT at baseline before switching targeted therapy. Treatment response status was divided into a progression group (PG) and a non-progression group (NPG) based on the Response Criteria in Solid Tumors (RECIST) 1.1, according to the contrast-enhanced computed tomography (CT) scan at six months. [¹⁸F]FAPI-42 and [¹⁸F]FDG PET/CT parameters including the mean standardized uptake value (SUV_mean), the standard uptake value corrected for lean body mass (SUL_peak), the maximum standardized uptake value (SUV_max), tumor-to-blood pool SUV ratio (TBR), tumor-to-liver SUV ratio (TLR), metabolic tumor volume (MTV)/FAPI-positive tumor volume (GTV-FAPI), total lesion glycolysis (TLG)/FAPI-positive total lesion accumulation (TLF) were correlated with the response status to identify indicative of treatment response. The predictive performance of them was quantified by generating receiver operating characteristic curves (ROC), calibration curves, and cross-validation.

Results: A total of 110 lesions were identified in 27 patients. Compared with PG, NPG was associated with lower levels of TBR and SUV_mean in FDG PET/CT (TBR-FDG, SUV_mean-FDG; P=0.033 and P=0.038, respectively), with higher SUL_peak and TLF in FAPI PET/CT (SUL_peak-FAPI, TLF-FAPI; P=0.10 and P=0.049, respectively). The predictive power of a composite-parameter model, including TBR-FDG, SUL_peak-FAPI, gene mutation, and type of targeted therapy [area under the curve (AUC) =0.865], was superior to the few-parameter models incorporating TBR-FDG (AUC =0.637, P<0.001), SUL_peak-FAPI (AUC =0.665, P<0.001) or both (AUC =0.721, P<0.001).

Conclusions: Both [¹⁸F]FAPI-42 PET/CT and [¹⁸F]FDG PET/CT have value in predicting the treatment response of recurrent or metastatic GISTs. And [¹⁸F]FAPI-42 PET/CT offers synergistic value when u

Background: Cesarean scar defect (CSD) is a potential complication following cesarean section (CS), which has significant clinical implications, and is usually clinically diagnosed by ultrasound. However, the optimal timing for ultrasound diagnosis of CSD after CS has not been well established. This study aimed to evaluate the appropriate time for the diagnosis of CSD after CS by ultrasonography.

Methods: The prospective study involved 120 women who delivered by elective CS with single birth and term birth from January 2021 to June 2022. Sample enrollment was consecutive in the study. Each woman underwent 3 ultrasound examinations for CSD diagnosis at 6 weeks, 6 months, and 12 months postpartum according to a modified Delphi method. The ultrasound indicators about the incision situation were recorded and statistically analyzed. Paired 4-fold table chi-square test was used to evaluate the consistency between the 3 diagnoses. The diagnostic sensitivity and specificity were calculated using a 4-cell table. According to whether the diagnosis was consistent to that at 6 or 12 months, the 120 cases at week 6 were separated into a consistent group and inconsistent group for statistical evaluation of the ultrasound indicators. Additionally, the menstrual duration of the included women was also recorded to analyze the correlation to ultrasound indicators of CSD at 6 months postpartum using the Person correlation coefficient.

Results: The included 120 women were divided into normal (3-7 days, n=52) and prolonged menstrual period (>7 days, n=68) groups. The 2 groups had no statistical differences in age, body mass index (BMI), gestational week of delivery, assisted reproduction rates, or postpartum complications. Among the 120 women, 100, 66, and 61 women were diagnosed as CSD at 6 weeks, 6 months, and 12 months postpartum, respectively. The results indicated that the diagnostic results of 6 weeks were inconsistent with those of 6 or 12 months postpartum, but the last 2 diagnostic results were consistent. The diagnostic sensitivity of 6 months was 100% and the specificity was 91.53% [95% confidence interval (CI): 85.84-95.26%]. Further, significant differences were found in depth of the defect, and the thickness (T) and ratio of residual muscle between the inconsistent group and the consistent group at 6 weeks. The patients could be considered self-recovered from CSD at 6 months when the defect depth was equal to or less than 4.04±0.82 mm at 6 weeks after CS. Additionally, in the CSD group at 6 months, the length (r=0.828, P<0.001), depth (r=0.784, P<0.001), width (r=0.787, P<0.001) of the defect, the T (r=0.831, P<0.001) and ratio of residual muscle (r=0.821, P<0.001) were strongly correlated with menstrual duration.

Conclusions: CSD evaluation at week 6 after CS may cause misdiagnosis or overdiagnosis. The diagnosis of CSD was suggested to be made following 6 months o