Quantitative Imaging in Medicine and Surgery最新文献

Background: Lymphovascular invasion (LVI) and perineural invasion (PNI) are important histopathological variables that are directly related to the survival and recurrence of patients with colorectal cancer (CRC). Preoperative prediction of LVI and PNI status in CRC is helpful in selecting patients requiring appropriate adjuvant therapy and evaluating prognosis. This study aimed to investigate the value of combining single-source dual-energy computed tomography (ssDECT)-derived parameters with extracellular volume (ECV) fraction for preoperative evaluation of LVI and PNI in CRC.

Methods: This retrospective study included patients with CRC who underwent contrast-enhanced ssDECT. All diagnoses were confirmed through histopathology, and the patients were classified into positive and negative groups based on the presence of LVI/PNI. Clinical data were collected. In the arterial (AP), venous (VP) and delayed phases (DP), the ssDECT-derived parameters were measured by two radiologists. The measurement consistency was evaluated using intraclass correlation coefficients. Differences between the two groups were analyzed using the t-test, Mann-Whitney U test, or Chi-square test. Binary logistic regression was employed to construct models incorporating multiple parameters. The diagnostic performance of various parameters or models was assessed by analyzing receiver operating characteristic curves.

Results: In total, 118 patients with CRC were included in the study. Serum carcinoembryonic antigen levels, T and N stages, and histological grades differed between the two groups (all P<0.05). The ssDECT-derived parameters in the VP and DP of LVI/PNI-positive group were higher than those of -negative group (all P<0.05). The ECV fraction in the DP of LVI/PNI-positive group was higher than that of -negative group (P=0.001). Discriminating capability analysis demonstrated that the diagnostic efficacies of the DP parameters were superior to those of the VP parameters, and the normalized iodine concentration in the DP exhibited the best performance [area under the curve (AUC): 0.750; 95% confidence interval (CI): 0.648-0.852]. The combination of ECV DP with clinical and ssDECT-derived parameters demonstrated the highest discriminative capability (AUC: 0.857; 95% CI: 0.786-0.928).

Conclusions: ssDECT-derived parameters and ECV fraction may serve as non-invasive tools for predicting the LVI/PNI status in CRC.

Background: Time-resolved angiography with interleaved stochastic trajectories (TWIST) magnetic resonance angiography (MRA) may obscure smaller vessels and is highly susceptibility to motion artifacts, potentially reducing endoleak detection accuracy after endovascular aortic repair (EVAR). The novel golden-angle radial sparse parallel (GRASP) sequence enhances spatial and temporal resolution with continuous, motion-robust datasets, showing promise for accurate endoleak detection post-EVAR. This study aimed to compare the diagnostic effectiveness of contrast-enhanced compressed-sensing radial GRASP-volume interpolated breath-hold examination (VIBE) sequence with standard contrast-enhanced dynamic TWIST-VIBE sequence in patients with inconclusive computed tomography angiography (CTA) findings regarding endoleak after EVAR.

Methods: This single-center prospective study consecutively enrolled adults with inconclusive findings regarding the presence or type of endoleak in multiphasic CTA following EVAR for abdominal aortic aneurysms. Participants underwent contrast-enhanced MRA, acquiring dynamic TWIST-VIBE and GRASP-VIBE sequences. Two independent radiologists assessed the datasets for image quality, diagnostic confidence, and the presence and type of endoleak. Additionally, quantitative assessments with signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNR) were performed. Statistical analyses included interrater and intermethod agreement, and diagnostic performance testing.

Results: Twenty participants (mean age, 72±9 years; 13 males) were included. GRASP-VIBE demonstrated superior image quality over TWIST-VIBE sequence with predominantly absent motion artifacts and increased diagnostic confidence (all P<0.001). Diagnostic performance significantly improved for detecting type II endoleaks in GRASP-VIBE compared to TWIST-VIBE scans [area under the curve (AUC): 0.96 vs. 0.73; P=0.04]. Diagnostic accuracy improved with GRASP-VIBE for overall (AUC: 0.94 vs. 0.79) and endoleak type I detection (AUC: 1.0 vs. 0.90), however, not significantly (P≥0.05). TWIST-VIBE sequences demonstrated significantly higher SNR for measurements in the clotted aneurysm sac (P=0.01). No significant differences were observed in CNR for the aorta and any aneurysm sacs across the compared imaging sequences.

Conclusions: Compressed-sensing dynamic GRASP-VIBE sequence, with its superior image quality, diagnostic confidence, and performance, may be preferred over standard TWIST-VIBE sequence in inconclusive endoleak cases.

Background: Hepatic steatosis is closely related to the occurrence and development of coronary plaques. Spectral detector computed tomography (SDCT) can provide more precise multiparameter quantitative parameters for hepatic steatosis. Hence, the purpose of this cross-sectional study was to explore the effect of quantitative liver metrics measured using SDCT on the extent and severity of coronary plaques.

Methods: In patients who underwent upper abdomen unenhanced SDCT and coronary computed tomography angiography, plaque extent and severity were assessed using segmental involvement score (SIS) and segmental stenosis score (SSS). Liver fat quantification was evaluated by polychromatic and virtual mono-energetic images at 40 and 70 kev, spectral attenuation curve slope, and effective atomic number (CT40 keV, CT70 kev, λHU, and Zeff, respectively). A logistic regression model evaluated the factors influencing high SIS and SSS.

Results: Enrolled patients (n=644) were divided into groups: low SIS (<5) (n=451), high SIS (≥5) (n=193), low SSS (<5) (n=461), and high SSS (≥5) (n=183). Zeff was more closely correlated with SIS (standard partial regression coefficient =-0.422, P<0.001) and SSS (standard partial regression coefficient =-0.346, P<0.001). Zeff was divided into four groups using interquartile intervals. Compared with the patients in the lowest quartile, those in the second [odds ratio (OR) =2.116, 95% confidence interval (CI): 1.134-3.949, P=0.018], third (OR =2.832, 95% CI: 1.461-5.491, P=0.002), and fourth (OR =3.584, 95% CI: 1.857-6.918, P<0.001) quartiles showed higher risk for high SIS. And correspondingly, the second (OR =1.933, 95% CI: 1.040-3.592, P=0.037), third (OR =2.900, 95% CI: 1.499-5.609, P=0.002), and fourth (OR =3.368, 95% CI: 1.743-6.510, P<0.001) quartiles showed higher risk for high SSS, especially in those who were <60 years old, male and had visceral adipose tissue/subcutaneous adipose tissue <1.18.

Conclusions: The SDCT-Zeff was an independent factor associated with high SIS and SSS. The quantification of liver fat may be useful for evaluating the risk and prognosis of coronary atherosclerosis.

Background: Early detection of nasopharyngeal carcinoma (NPC) patients who are not sensitive to neoadjuvant chemotherapy (NAC) can guard against overtreatment. This study aimed to evaluate the effectiveness of amide proton transfer (APT) imaging and diffusion-weighted imaging (DWI) in predicting the early response to NAC in patients with NPC.

Methods: This prospective study enrolled fifty patients with biopsy-confirmed NPC from September 2021 to May 2023. Magnetic resonance imaging (MRI) including APT and DWI, was performed before NAC. After NAC, patients were divided into complete response (CR), partial response (PR), and stable disease (SD) and progressive disease (PD) groups based on the Response Evaluation Criteria in Solid Tumours Version 1.1. The Kruskal-Wallis H test was used for statistical analysis. The differences in APT and apparent diffusion coefficient (ADC) values among the different efficacy groups were compared, the receiver operating characteristic (ROC) curve was drawn for statistically significant parameters, and the area under the curve (AUC) was calculated.

Results: Fifty patients (mean age: 47±14 years; 42 males and 8 females) were included in the final analysis (11 were in the CR group, 30 in the PR group, 9 in the SD group, and 0 in the PD group). The ADC values showed no significant differences among the different treatment response groups. The SD group showed significantly lower APT_max (P=0.025), APT_skewness (P=0.025) and APT_90% (P=0.001) values than the CR and PR groups. Setting APT_90% =3.10% as the cut-off value, optimal diagnostic performance (AUC: 0.831; sensitivity: 0.778; specificity: 0.878) was obtained in predicting the SD group.

Conclusions: APT imaging can predict the early tumour response to NAC in patients with NPC. APT imaging may be superior to DWI in predicting tumour response.

Background: Static nailfold capillary parameters are important parameters that reflect the health of the human body. Disease onset or progression is often accompanied by changes in the physiological parameters of the nailfold. Hence, the physiological parameters of the nailfold are closely related to the study of disease, with their automated and high-precision measurements playing a crucial role in these studies. Currently, manually measured values of the nailfold's parameters are the gold standard; however, they are time consuming and labor intensive, making the development of automated measurement methods essential. Most automated measurement methods use skeleton lines; however, current skeleton-thinning algorithms have non-single pixels and redundant branches that lead to reduced measurement accuracy. This study proposes a single-pixel and non-redundant branching-based skeleton line extraction algorithm for nailfold capillaries, which is then applied to nailfold static parameter calculations to improve accuracy.

Methods: The algorithm includes deletion and restoration templates combined with the depth-first search method to obtain single-pixel skeleton lines without redundant branches. These lines are applied to the static nailfold capillary parameter measurement method based on digital image processing to calculate the blood vessel diameter.

Results: The results show that the proposed method can obtain the single-pixel skeleton line without the redundant branches that are required for the parameter calculations and improve the accuracy of the nailfold capillary diameter measurement. Experiments showed that the root mean square errors (RMSEs) of the labeled apical diameter, arterial limb diameter, and venous limb diameter were 0.794, 0.756, and 0.830 µm, respectively, when the calculated results were compared with those of the manual calculations. According to the accuracy formula, the accuracy of the method in this study is 90%. We calculated the P values of the algorithmic and manual measurements to P<0.001 and found that the difference in the measurements of the proposed algorithm is statistically significant. Therefore, the method in this study has high sensitivity and specificity for the measurement of normal nailfold capillaries.

Conclusions: The proposed algorithm could obtain single-pixel skeleton lines without redundant branches, thereby improving the nailfold static parameter measurement accuracy.

Background: Pulmonary nodules with Lung Imaging Reporting and Data System (Lung-RADS) 4X are of greater clinical significance, and accurate differentiation of pathological types and visceral pleural invasion (VPI) of Lung-RADS 4X peripheral pulmonary nodules before treatment can aid in stratification. This study set out to investigate whether the tumour-pleura relationship on computed tomography (CT) can provide effective risk stratification for peripheral pulmonary nodules with Lung-RADS 4X.

Methods: This was a single institution, retrospective study of 482 consecutive patients with Lung-RADS score 4X, who were pathologically diagnosed with tuberculous granuloma and adenocarcinoma from January 2019 to December 2023. We assessed clinical factors (baseline characteristics and tumour markers) and CT findings. Univariate and multivariate logistic regression analyses were used to determine the classification of pulmonary nodules and predictors of VPI.

Results: Multivariate analysis revealed that gender [odds ratio (OR) =0.392; P<0.001], carcinoembryonic antigen (CEA) level (OR =8.331; P<0.001), type of nodules (OR =13.551 and 7.478; P<0.001 and P=0.016) and maximum base width of soft tissue component on the pleura side (OR =0.857; P=0.005) were significant independent factors for distinguishing tuberculous granuloma from adenocarcinoma. And the type of linear connection between lesion and pleura (OR =3.936; P<0.001), and the maximum base width of soft tissue components on the pleura side (OR =1.359; P=0.001) were correlated independently with VPI. The area under the curve (AUC) for predicting pulmonary nodules classification was 82.60% [95% confidence interval (CI): 78.85-86.35%), and the AUC for predicting VPI was 76.10% (95% CI: 69.83-82.38%).

Conclusions: The tumour-pleura relationship will be helpful in further risk stratification for peripheral pulmonary nodules with a score of Lung-RADS 4X.