Purpose To evaluate the value of a combined model based on multiphase contrast-enhanced CT radiomics and clinical features for differentiating hypovascular pancreatic neuroendocrine tumors (hypo-PNETs) from pancreatic ductal adenocarcinoma (PDAC). Methods A total of 297 patients with pathologically confirmed pancreatic tumors, including 99 hypo-PNETs and 198 PDACs, were retrospectively enrolled. Radiomics features were extracted from non-contrast, arterial-phase, venous-phase, and combined three-phase CT images. After feature selection, radiomics models were established using multiple machine-learning classifiers. Independent clinical predictors were identified by logistic regression and integrated with the optimal radiomics signature to construct a combined model. Model performance was assessed using receiver operating characteristic analysis, calibration curves, decision curve analysis, net reclassification improvement, and integrated discrimination improvement. Results Pancreatic duct dilatation, tumor composition, age, and maximum tumor diameter were identified as independent predictors. Among the radiomics models, the combined three-phase SVM model achieved the best performance, with AUCs of 0.814 and 0.812 in the training and test sets, respectively. The combined model yielded the highest AUCs (0.886 in the training set and 0.849 in the test set); however, because several between-model comparisons in the test set did not reach statistical significance, its advantage should be interpreted as a potential incremental benefit rather than definitive superiority. Conclusion A combined model integrating multiphasic CT radiomics and clinical features showed promising performance for differentiating hypo-PNETs from PDAC. This model may provide complementary support for preoperative diagnosis, although its incremental value over the radiomics-only model requires further validation.
Objective:To analyze the changes in white matter volume of the temporal lobe subre-gions in patients with medial temporal lobe epilepsy with hippocampal sclerosis(MTLE-HS)by auto-matic brain segmentation technique(FreeSurfer)and to investigate its clinical application value in MTLE-HS.Methods:A total of 53 patients diagnosed with MTLE-HS through postoperative pathology or magnetic resonance imaging(MRI)from January 2021 to September 2023 were collected,including 30 patients with left MTLE-HS(LMTLE-HS)and 23 patients with right MTLE-HS(RMTLE-HS).Meanwhile,43 gender-and age-matched healthy controls were recruited.All participants underwent T1-weighted three-dimensional magnetization-prepared rapid acquisition gradient echo sequence(3D-T1 WI-MPRAGE)scanning on a 3.0T MR.The FreeSurfer software was used to perform whole-brain segmentation on the T1-MPRAGE images,and white matter volume data of the temporal lobe subre-gions(posterior superior temporal gyrus,temporal pole,superior temporal gyrus,middle temporal gy-rus,inferior temporal gyrus,fusiform gyrus and parahippocampal gyrus)were collected.Paired t-tests were used to compare the differences in white matter volumes of each subregion between the left and right temporal lobes in the control group.Independent samples t-tests were used to compare the differ-ences in white matter volumes of each temporal lobe subregion between the control group and the LM-TLE-HS and RMTLE-HS groups,as well as between the affected and unaffected sides within the LM-TLE-HS and RMTLE-HS groups.Results:There were statistically significant differences in white mat-ter volumes of the transverse temporal gyrus,superior temporal gyrus,middle temporal gyrus,inferior temporal gyrus,fusiform gyrus and parahippocampal gyrus between the left and right sides in the con-trol group(P＜0.05).Significant differences in white matter volumes were found in the affected side of the LMTLE-HS group compared to the left side of the control group(temporal pole,transverse temporal gyrus,superior temporal gyrus,middle temporal gyrus,inferior temporal gyrus,fusiform gy-rus and parahippocampal gyrus)(P＜0.05).Significant differences in white matter volumes were found in the unaffected side of the LMTLE-HS group(posterior superior temporal gyrus,superior temporal gyrus,middle temporal gyrus,inferior temporal gyrus,fusiform gyrus and parahippocampal gyrus)and in the affected side of the RMTLE-HS group(posterior superior temporal gyrus,middle temporal gyrus,inferior temporal gyrus,fusiform gyrus and parahippocampal gyrus)compared to the right side of the control groups(P＜0.05).There were no statistically significant differences in volume among the other subregions(P＞0.05).Conclusion:The quantitative analysis of temporal lobe white matter volume using the automatic brain segmentation technique is of certain significance for preoper-ative evaluation and surgical approach selection in patients with hippocampal sclerotic medial temporal lobe epilepsy.
AIM: To determine the effect of second-generation motion correction (MC2) on image quality and measurement reproducibility of cardiac CT images in patients with a myocardial bridge and mural coronary artery (MB-MCA) compared to standard (STD) images without motion correction and with first-generation motion correction (MC1). MATERIALS AND METHODS: A total of 66 patients with MB-MCA in the left anterior descending branch who underwent 256-detector CT with single-heartbeat acquisition were included. Images were reconstructed at 45% and 75% R-R intervals using STD, MC1, and MC2 algorithms. Image quality for MB-MCA was assessed by two observers on a four-point scale (1 = poor and 4 = excellent) and compared among STD, MC1, and MC2. Depth and length of MB, lumen area, and minimal diameter of MCA were measured and compared. RESULTS: At 45% R-R interval, image quality scores were 1.59 +/- 0.78, 2.21 +/- 0.97, and 3.21 +/- 0.62 for MCA, and 2.48 +/- 0.79, 2.76 +/- 0.75, and 3.58 +/- 0.58 for MB with STD, MC1 and MC2, respectively. At 75% R-R interval, these values were 2.26 +/- 0.60, 3.03 +/- 0.89, and 3.59 +/- 0.55 for MCA and 3.00 +/- 0.93, 3.17 +/- 0.83, and 3.80 +/- 0.44 for MB. Although MC1 was superior to STD in displaying MCA, there was no statistical difference between the two algorithms for MB (p>0.05). Compared with STD and MC1, MC2 statistically improved image quality and interpretability for both MCA and MB and had narrower limits in interobserver agreement for measurements at both 45% and 75% R-R intervals. CONCLUSION: MC2 improves CT image quality and measurement reproducibility in patients with MB-MCA compared to STD and MC1. (c) 2023 Published by Elsevier Ltd on behalf of The Royal College of Radiologists.
To retrospectively analyze the computed tomography (CT) features in patients with pre-invasive lesions and early-stage lung adenocarcinoma and to explore the correlation between tumor morphological changes and pathological diagnoses. CT morphological characteristics in 2106 patients with pre-invasive (stage 0) and early-stage (stage I) lung adenocarcinoma were analyzed; lesions were confirmed by surgical pathology. Based on the morphological characteristics, the lesions were divided into eight types: I (cotton ball, ground-glass nodules), II (solid fill), III (granular), IV (dendriform), V (bubble-like lucencies), VI (alveolate or honeycomb), VII (scar-like), and VIII (notched or umbilication). The different distributions of eight morphological types in pathological types of the lesions and subtypes of invasive adenocarcinoma were analyzed by chi-squared or Fisher’s exact test. Correlation between the percentage of ground-glass opacity in the lesions and pathology types were analyzed by two-tailed Pearson’s test. A negative correlation was observed between the pathological types and proportion of ground-glass component in the lesions (p < 0.001 and r = − 0.583). Significant differences in morphological characteristics among various pathological types of pre-invasive lesions and early lung adenocarcinomas were observed (p < 0.05). Furthermore, among the different pathological subtypes of stage I invasive adenocarcinoma, the differences in their manifestation as morphological types I, II, III, and VI were statistically significant (p < 0.05). The eight types of morphological classification of pre-invasive lesions and early-stage (stage 0 or stage I) lung adenocarcinoma has different pathological bases, and morphological classification may be useful for the diagnosis and differential diagnosis of lung adenocarcinoma. • CT morphological classification of pre-invasive lesions and lung adenocarcinoma is intuitive. • CT morphological classification characterizes morphological changes of the entire lesion. • Different pathological types of lung adenocarcinoma have different morphological features.
医学论文中正确、合理使用专业名词可以精简文字,节省篇幅,使文章精炼易懂.现将放射学专业领域为大家所熟知的专业名词缩略语公布如下(按照英文首字母顺序排列),以后本刊在论文中将对这一类缩略语不再注释其英文全称和中文.
