Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Diagnostic value of deep learning reconstruction-based subtraction CT-FFR in patients with calcified-related stenosis or stent implantation.","authors":"Cheng Xu, Yan Yi, Min Xu, Li-Miao Zou, Ming Wang, Yun Wang, Zheng-Yu Jin, Yi-Ning Wang","doi":"10.21037/qims-24-1366","DOIUrl":"10.21037/qims-24-1366","url":null,"abstract":"<p><strong>Background: </strong>The application of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) is limited due to severe coronary calcium burden or stent implantation. This study aimed to explore the diagnostic value of subtraction CT-FFR with deep learning reconstruction (DLR) or hybrid iterative reconstruction (HIR) in detecting calcified-related hemodynamically significant stenosis, and the feasibility in the application of coronary stents.</p><p><strong>Methods: </strong>Between March 2020 and January 2022, consecutive patients with calcified-related stenosis or previous stent treatment who had undergone subtraction coronary computed tomography angiography (CTA) and invasive fractional flow reserve (FFR) were included in this prospective study. CT image data were reconstructed using HIR and DLR. The diagnostic performance of CT-FFR, and subtraction CT-FFR were evaluated. An FFR value of 0.8 or less was considered hemodynamically significant.</p><p><strong>Results: </strong>A total of 30 patients with 52 calcified-related lesions and 14 coronary stents were included in this study. Subtraction CT-FFR outperformed the corresponding CT-FFR in detecting calcified-related hemodynamically significant stenosis and in the application of coronary stents, while there was no significant difference when subtraction CT-FFR_DLR was compared with subtraction CT-FFR_HIR (P>0.05). Lesion-based analysis showed the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy for subtraction CT-FFR_DLR were 100.0%, 71.4%, 63.0%, 100% and 80.8%, respectively in detecting calcified-related hemodynamically significant stenosis, and were 100.0%, 83.3%, 88.9%, 100% and 92.9%, respectively in the application of coronary stents.</p><p><strong>Conclusions: </strong>Subtraction CT-FFR yielded optimal diagnostic performance for hemodynamically significant calcified-related stenosis, and the application of subtraction CT-FFR in the evaluation of coronary stents was feasible. The diagnostic performance of subtraction CT-FFR_DLR was better than that of subtraction CT-FFR_HIR, but there was no significant difference.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1599-1612"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494587","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":"Enhancing diagnostic accuracy of American College of Radiology TI-RADS 4 nodules: nomogram models based on MRI morphological features.","authors":"Bin Song, Qiaohui Chen, Hao Wang, Lang Tang, Xiaoli Xie, Qingyin Fu, Anwei Mao, Mengsu Zeng","doi":"10.21037/qims-24-1427","DOIUrl":"10.21037/qims-24-1427","url":null,"abstract":"<p><strong>Background: </strong>Thyroid nodules classified as American College of Radiology Thyroid Imaging Reporting and Data System category 4 (ACR-TR4) present a diagnostic challenge due to their undetermined nature. This study aimed to develop and validate nomogram models using magnetic resonance imaging (MRI) morphological features to enhance the diagnostic accuracy of ACR-TR4 thyroid nodules, thereby reducing unnecessary fine-needle aspiration (FNA) and minimizing missed cancers.</p><p><strong>Methods: </strong>We retrospectively analyzed 229 ACR-TR4 nodules from 184 patients who underwent preoperative MRI and surgical thyroidectomy between January 2017 and December 2022 in Minhang Hospital, Fudan University. All nodules were pathologically confirmed and randomly divided into training (n=166) and validation (n=63) cohorts. We recorded MRI morphological features of the nodules, performed logistic regression analysis to identify independent predictors of malignancy, and developed a nomogram and improved models. The performance of the nomogram was assessed for discrimination, calibration, and clinical utility. The diagnostic performance of the improved models was compared with that of the ACR-TR4.</p><p><strong>Results: </strong>Among the 229 ACR-TR4 thyroid nodules, there were 140 benign and 89 malignant nodules, with 46 males and 183 females, and a mean age of 51.2±13.5 years. Diffusion restriction and reversed halo sign in the delayed phase were identified as independent predictors of malignancy and included in the nomogram. The nomogram showed robust discrimination and calibration in distinguishing malignant and benign ACR-TR4 nodules in both the training and validation cohorts, with areas under the curve (AUC) of 0.928 [95% confidence interval (CI): 0.887-0.970] and 0.904 (95% CI: 0.825-0.984), respectively. Four improved models were constructed using the two independent predictors either individually or collectively (OR or AND). The unnecessary FNA (21.1%, 11.7%, 5%, and 23.4%, respectively) and missed cancer rates (12.9%, 13.8%, 18.9%, and 5.7, respectively) were significantly lower than those of the ACR-TR4 system (64% and 43%, respectively).</p><p><strong>Conclusions: </strong>The nomogram model using MRI features such as restricted diffusion and reversed halo sign in the delayed phase improved the accuracy of diagnosing benign versus malignant ACR-TR4 thyroid nodules, potentially reducing unnecessary FNA and minimizing missed cancers.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1679-1693"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494602","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":"Impact of corneal sub-basal nerve plexus on epithelial thickness after small incision lenticule extraction (SMILE): a quantitative assessment using in vivo confocal microscopy and optical coherence tomography.","authors":"Ying Xu, Fei Li, Yuanyuan Qi, Yue Huang, Ruibo Yang, Chen Zhang, Shaozhen Zhao","doi":"10.21037/qims-24-1887","DOIUrl":"10.21037/qims-24-1887","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Quantitative assessment of corneal epithelial thickness (CET) has attracted a great attention for its wide application in refractive surgeries. The corneal nerves are crucial for epithelial homeostasis, and nerve injury due to corneal refractive surgery may affect the epithelia; however, few clinical studies have investigated this relationship. Our study aimed to observe changes in epithelial thickness and sub-basal nerve plexus (SNP) profile after small incision lenticule extraction (SMILE) for low-to-moderate myopia [spherical refraction of -6.0 to 0 diopters (D)], and investigate the relationship between them.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This prospective observational study included 52 eyes treated with SMILE from March to May 2023 at Tianjin Medical University Eye Hospital. The epithelial thickness was measured across the central and concentric (paracentral, mid-peripheral, and peripheral) regions using spectral-domain optical coherence tomography (SD-OCT). SNPs were observed in the central and peripheral (temporal, superior, nasal, and inferior) areas using in vivo confocal microscopy (IVCM), and seven nerve parameters were assessed. All eyes were examined preoperatively and 1 week, 1 month, and 6 months postoperatively. Pearson's correlation was employed to investigate the association between anterior Q-value (corneal asphericity) and epithelial thickness. Partial correlation was adopted to examine the relationship between epithelial thickness and corresponding nerve parameters.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Both epithelial thickness and SNP exhibited changes after SMILE. Six months postoperatively, epithelial thickness in the central and paracentral regions increased (all P&lt;0.05), with thickening particularly pronounced in the inferotemporal, temporal, and inferior sections of the paracentral region, and the anterior Q-value was positively correlated with epithelial thickness in the inferonasal, inferior, and inferotemporal sections (inferonasal section: r=0.293, P=0.035; inferior section: r=0.396, P=0.004; inferotemporal section: r=0.374, P=0.006). Furthermore, most central, superior, and nasal nerve parameters had still not reached preoperative levels, while most temporal and inferior nerve parameters had reached or exceeded preoperative levels, and epithelial thickness was positively correlated with corresponding nerve parameters [corneal nerve fiber density (CNFD): r=0.171, P=0.006; corneal nerve branch density (CNBD): r=0.137, P=0.028; corneal nerve fiber length (CNFL): r=0.172, P=0.006; corneal nerve fiber total branch density (CNTB): r=0.141, P=0.024; corneal nerve fiber area (CNFA): r=0.164, P=0.008].&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Uneven epithelial thickness changes were observed after SMILE, regional epithelial thickening increased corneal oblateness. Non-uniform SNP regeneration was also observed, positive correlation between epithelial thickness and nerve parameters indicated the impac","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1254-1264"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494612","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":"Predicting joint space changes in knee osteoarthritis over 6 years: a combined model of TransUNet and XGBoost.","authors":"Jiangrong Guo, Pengfei Yan, Hao Luo, Yingkai Ma, Yuchen Jiang, Chaojie Ju, Wang Chen, Meina Liu, Songcen Lv, Yong Qin","doi":"10.21037/qims-24-1397","DOIUrl":"10.21037/qims-24-1397","url":null,"abstract":"<p><strong>Background: </strong>The progression of knee osteoarthritis is mainly characterized by the reduction in joint space width (JSW). The goal of this study was to build a knee joint space segmentation model through deep learning (DL) methods and develop a model for automatically measuring JSW. Furthermore, we predicted JSW changes in the sixth year based on regression models.</p><p><strong>Methods: </strong>The data for this study was sourced from the Osteoarthritis Initiative database. We filtered knee X-ray images from 1,947 participants and tested six neural networks for segmentation to build an automatic JSW measurement model. Subsequently, we combined the clinical data with the JSW measurement results to predict the sixth-year knee JSW using six different regression models.</p><p><strong>Results: </strong>The segmentation results showed that TransUNet performed the best, with an overall Dice coefficient of 0.889. The intraclass correlation coefficient (ICC) between manually measured and TransUNet's automatically measured JSW reached 0.927 (P<0.01). Among the regression models, eXtreme Gradient Boosting (XGBoost) demonstrated the best predictive performance, with a mean absolute error (MAE) of 0.48 and an ICC of 0.887 (P<0.01). To better align with clinical practice, we reduced the prediction model to utilize only 2 years of JSW images. The results showed that using the 0- and 12-month X-ray images still achieved high accuracy, with an MAE of 0.585 (P<0.05) and an ICC of 0.805 (P<0.01).</p><p><strong>Conclusions: </strong>We developed a novel JSW measurement model that significantly improves accuracy compared to previous methods and identified the best prediction model by combining TransUNet and XGBoost. Additionally, in our built model, predicting the 72-month JSW using only 2 years of knee X-ray images and several clinical features achieved high accuracy.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1396-1410"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494613","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":"Improved image quality and micronodule detection in thyroid spectral computed tomography using modified swimmer's position.","authors":"Shuting Liao, Nan Zheng, Dan Li, Chen Liu, Haidong Chen, Min Cui, Xiangrong Yu, Chuanmiao Xie","doi":"10.21037/qims-24-1119","DOIUrl":"10.21037/qims-24-1119","url":null,"abstract":"<p><strong>Background: </strong>Spectral computed tomography (CT) can be used as a valuable complement to ultrasound (US) in the detection of thyroid nodules. This study sought to investigate the effects of various arm positions during thyroid spectral CT scans in terms of radiation exposure, image quality, and micronodule detection (≤10 mm).</p><p><strong>Methods: </strong>A total of 180 patients (mean age: 48 years; 136 females) who underwent thyroid spectral CT were assigned to the traditional position (TDN; n=60), swimmer's position (SWIM; n=60), and modified swimmer's position (M-SWIM; n=60) groups. Image quality in the plain, arterial, and venous phases was assessed using a 4-point grading scale, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR). Radiation exposure was assessed using the volume computed tomography dose index (CTDI_vol), dose-length product (DLP), effective dose of the neck (ED_N), and effective dose of the thyroid (ED_T). The micronodule detection rates for spectral CT and US were compared using the pathology detection rate as a reference.</p><p><strong>Results: </strong>The M-SWIM group had a significantly higher proportion of 4-point grading, SNR, and CNR than the TDN and SWIM groups (all P<0.001). The CTDI_vol, DLP, ED_N, and ED_T were similar among the three groups (all P>0.05). The micronodule detection rate was higher in the M-SWIM group than the TDN and SWIM groups (total: 90.6% <i>vs.</i> 70.1% <i>vs.</i> 46.8%; benign: 89.1% <i>vs.</i> 66.7% <i>vs.</i> 45.5%; malignant: 94.3% <i>vs.</i> 79.5% <i>vs.</i> 51.5%; all P<0.001), but comparable to that of the US group (total: 90.6% <i>vs.</i> 91.2%; benign: 89.1% <i>vs.</i> 90.6%; malignant: 94.3% <i>vs.</i> 92.5%; all P>0.05).</p><p><strong>Conclusions: </strong>The proposed M-SWIM improved the image quality of thyroid spectral CT without increasing the radiation dose, and significantly enhanced the micronodule detection rate.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1571-1581"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494617","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":"Spinal sagittal and coronal morphology characteristics in children with short stature.","authors":"Tian-Hao Wu, Lin-Lin Chen, Jin-Xu Wen, Shu-Man Han, Zhi-Wei Zhong, Zhe Guo, Lei Cao, Hui-Zhao Wu, Bao-Hai Yu, Bu-Lang Gao, Wen-Juan Wu, Ji-Cun Liu","doi":"10.21037/qims-24-992","DOIUrl":"10.21037/qims-24-992","url":null,"abstract":"<p><strong>Background: </strong>The characteristics of total sagittal and coronal plane parameters in children with short stature (SS) and the correlations between these parameters are currently unknown. This case-control study sought to retrospectively investigate the characteristics of total sagittal and coronal plane parameters in children with SS and examine the correlations between these parameters.</p><p><strong>Methods: </strong>The data of children aged 3-15 years with SS and normal heights were collected, and the children were allocated to the observation and control groups, respectively. The following parameters were analyzed: coronal Cobb angle, cervical lordosis (CL) angle, T1 slope (T1S), thoracic kyphosis (TK) angle, lumbar lordosis (LL) angle, sacral inclination angle, pelvic inclination angle, pelvic incidence angle, cervical sagittal axis, spinal sagittal axis, trunk pelvic angle (TPA), and spino-sacral angle (SSA).</p><p><strong>Results: </strong>In total, 41 children with SS were enrolled in this study, and 80 age- and sex-matched children with normal heights were included as the controls. The CL angle, T1S, and TPA were significantly greater (P<0.050) in the children with SS than those with normal heights. The children with SS were further divided into group A with CL (a positive CL angle) and group B without CL (a negative CL angle), while the children with normal heights were further divided into group A' with CL and group B' without CL. The CL angle, T1S, and TK angle were significantly greater (P<0.05), but the Cobb angle and spinal sagittal axis were significantly smaller (P<0.05) in group A than group B, while the CL angle, T1S, and TK angle were significantly greater (P<0.05) in group A than group A'. The Cobb angle was significantly smaller (P=0.024), and the spinal sagittal axis and TPA were significantly greater (P=0.013 and 0.005, respectively) in group B than group B'. Different correlations were found among the spinal parameters.</p><p><strong>Conclusions: </strong>SS children have a significantly larger CL angle, T1S, TPA, and TK angle, and a tendency toward a hunchback posture. When scoliosis occurs in the coronal plane in children with SS, the degree of scoliosis is relatively small, and the spine tilts toward the dorsal side.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1383-1395"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847212/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494750","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":"Robotic navigation-assisted percutaneous liver puncture: a pilot study.","authors":"Milan Sigdel, Yi Fang, Zhanguo Sun, Madan Sigdel, Dechao Jiao","doi":"10.21037/qims-24-1584","DOIUrl":"10.21037/qims-24-1584","url":null,"abstract":"<p><strong>Background: </strong>Liver cancer is often diagnosed at an advanced stage, rendering many cases unresectable and necessitating minimally invasive treatments such as ablation, for which accurate puncture is essential. Manual techniques are limited by steep learning curves, frequent needle adjustments, and increased radiation exposure. Robotic navigation-assisted puncture (RNAP) offers improved precision, efficiency, and safety, but its efficacy compared to that of manual puncture (MP) remains unclear. This study aimed to assess the safety and efficacy of RNAP in the treatment of liver tumors.</p><p><strong>Methods: </strong>From October 2023 to February 2024, 65 patients with liver tumors underwent percutaneous puncture procedures (ablation, iodine-125 implantation, and biopsy) at department of interventional radiology. They were divided into two groups: the RNAP group (n=29) and the MP group (n=36). Two techniques were compared in terms of technical success (TS), clinical success (CS), puncture scoring (PS), number of computed tomography (CT) scans, total procedure time (TPT), puncture time (PT), irradiation dose (ID), and puncture-related complications.</p><p><strong>Results: </strong>There were significant differences between patients in the RNAP group and those in the MP group in terms of PS (3.02±0.68 <i>vs.</i> 2.24±0.73; P=0.01), PT (8.86±1.91 <i>vs.</i> 13.44±3.66 min; P=0.01), number of CT scans (7.03±2.30 <i>vs.</i> 11.58±4.25; P=0.01), and ID (160.76±40.60 <i>vs.</i> 230.06±86.46 mGy·cm; P=0.01); meanwhile, TS (100% <i>vs.</i> 100%; P>0.99), CS (91.50% <i>vs.</i> 91.40%; P=0.81), TPT (33.22±7.80 <i>vs.</i> 32.13±5.50 min; P=0.52), and complications (10.30% <i>vs.</i> 5.56%; P=0.47) showed no differences.</p><p><strong>Conclusions: </strong>RNAP is a useful tool for performing puncture procedures on liver tumors, which can decrease PT, CT scan times, and ID.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1543-1554"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494744","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":"Background suppression single-shot electrocardiogram trigger non-enhanced magnetic resonance angiography in lower extremity blood vessels: a comparative study.","authors":"Qian Zhang, He Cao, Xin-Qiang Han, Xiu-Zheng Yue, Wen-Ming Wang, Lu-Ying Ni, Wen-Ju Cui, Chang-Jin Bao, Xing-Yue Jiang","doi":"10.21037/qims-24-1120","DOIUrl":"10.21037/qims-24-1120","url":null,"abstract":"<p><strong>Background: </strong>Background suppression single-shot electrocardiogram trigger non-contrast-enhanced magnetic resonance angiography (BASS-TRANCE) is a recently introduced non-contrast-enhanced magnetic resonance angiography (NCE-MRA) technique. It was reported to be a practical test for the evaluation of peripheral artery disease (PAD) with an imaging performance comparable to that of the known NCE-MRA technique quiescent interval single-shot (QISS). However, its performance compared to the most commonly used diagnostic methods for digital subtraction angiography (DSA) and computed tomography angiography (CTA) remains unclear. Using DSA as the test standard, this study evaluated the image quality and clinical diagnostic accuracy of BASS-TRANCE and CTA in PAD patients.</p><p><strong>Methods: </strong>BASS-TRANCE, CTA, and DSA were examined successively in 30 patients with PAD. Two senior physicians scored the image quality of CTA and BASS-TRANCE using the 3-point method, and the images of both were evaluated according to the 5-level stenosis evaluation method. Either paired <i>t</i>-test or Wilcoxon signed-rank test was used to compare the difference of image quality between the two groups. Using DSA results as the gold standard, the sensitivity and specificity of CTA and BASS-TRANCE for lower limb artery stenosis >50% were calculated by McNemar's test.</p><p><strong>Results: </strong>Of 570 segments, 12 (2.1%) and 42 (7.4%) inconclusive segments were excluded from BASS-TRANCE and CTA analysis, respectively (P<0.05). The DSA results were available for 392 of the remaining segments. Among the 516 vessels with reliable image quality, there was no significant difference in scores between BASS-TRANCE {2.42 [95% confidence interval (CI): 2.36-2.47]} and CTA [2.39 (95% CI: 2.33-2.45); P>0.05]. Furthermore, BASS-TRANCE demonstrated significant efficacy in detecting vascular stenosis with a sensitivity of 92.8% and specificity of 96.1%, which were comparable to those achieved by CTA (94.9% and 96.8%, respectively).</p><p><strong>Conclusions: </strong>As an NCE-MRA technique, BASS-TRANCE can display the lower extremity vessels in a short time; it is expected to replace CTA as a safe and effective examination method for PAD patients in the future.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1312-1323"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494564","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":"Combining pelvic floor ultrasonography with deep learning to diagnose anterior compartment organ prolapse.","authors":"Fan Yang, Rong Hu, Hongjie Wu, Shichang Li, Shiyun Peng, Hong Luo, Jiancheng Lv, Yueyue Chen, Ling Mei","doi":"10.21037/qims-24-772","DOIUrl":"10.21037/qims-24-772","url":null,"abstract":"<p><strong>Background: </strong>Anterior compartment prolapse is a common pelvic organ prolapse (POP), which occurs frequently among middle-aged and elderly women and can cause urinary incontinence, perineal pain and swelling, and seriously affect their physical and mental health. At present, pelvic floor ultrasound is the primary examination method, but it is not carried out by many primary medical institutions due to the significant shortcomings of training in the early stage and the variable image quality. There has been great progress in the application of deep learning (DL) in image-based diagnosis in various clinical contexts. The main purpose of this study was to improve the speed and reliability of pelvic floor ultrasound diagnosis of POP by training neural networks to interpret ultrasound images, thereby facilitating the diagnosis and treatment of POP in primary care.</p><p><strong>Methods: </strong>This retrospective study analyzed medical records of women with anterior compartment organ prolapse (n=1,605, mean age 45.1±12.2 years) or without (n=200, mean age 38.1±13.4 years), who were examined at West China Second University Hospital between March 2019 and September 2021. Static ultrasound images of the anterior chamber of the pelvic floor (5,281 abnormal, 535 normal) were captured at rest and at maximal Valsalva motion, and four convolutional neural network (CNN) models, AlexNet, VGG-16, ResNet-18, and ResNet-50, were trained on 80% of the images, then internally validated on the other 20%. Each model was trained in two ways: through a random initialization parameter training method and through a transfer learning method based on ImageNet pre-training. The diagnostic performance of each network was evaluated according to accuracy, precision, recall and F1-score, and the receiver operating characteristic (ROC) curve of each network in the training set and validation set was drawn and the area under the curve (AUC) was obtained.</p><p><strong>Results: </strong>All four models, regardless of training method, achieved recognition accuracy of >91%, whereas transfer learning led to more stable and effective feature extraction. Specifically, ResNet-18 and ResNet-50 performed better than AlexNet and VGG-16. However, the four networks learned by transfer all showed fairly high AUCs, with the ResNet-18 network performing the best: it read images in 13.4 msec and provided recognition an accuracy of 93.53% along with an AUC of 0.852.</p><p><strong>Conclusions: </strong>Combining DL with pelvic floor ultrasonography can substantially accelerate diagnosis of anterior compartment organ prolapse in women while improving accuracy.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1265-1274"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847209/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494566","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":"Development and validation of a robust MRI-based nomogram incorporating radiomics and deep features for preoperative glioma grading: a multi-center study.","authors":"Salar Bijari, Seyed Masoud Rezaeijo, Sahar Sayfollahi, Ali Rahimnezhad, Sahel Heydarheydari","doi":"10.21037/qims-24-1543","DOIUrl":"10.21037/qims-24-1543","url":null,"abstract":"<p><strong>Background: </strong>Gliomas, the most common primary brain tumors, are classified into low-grade glioma (LGG) and high-grade glioma (HGG) based on aggressiveness. Accurate preoperative differentiation is vital for effective treatment and prognosis, but traditional methods like biopsy have limitations, such as sampling errors and procedural risks. This study introduces a comprehensive model that combines radiomics features (RFs) and deep features (DFs) from magnetic resonance imaging (MRI) scans, integrating clinical factors with advanced imaging features to enhance diagnostic precision for preoperative glioma grading.</p><p><strong>Methods: </strong>In this retrospective multi-center study [2017-2022], 582 patients underwent preoperative contrast-enhanced T1-weighted (CE-T1w) and T2-weighted fluid-attenuated inversion recovery (T2w FLAIR) MRI. The dataset, divided into 407 training and 175 testing cases, included 340 LGGs and 242 HGGs. RFs and DFs were extracted from CE-T1w images, and radiomic scores (rad-score) and deep scores (deep-score) were calculated. Additionally, a clinical model based on demographics and MRI findings (CE-T1w and T2w FLAIR imaging) was developed. A nomogram model integrating rad-score, deep-score, and clinical factors was constructed using multivariate logistic regression analysis. Decision curve analysis (DCA) was employed to evaluate the nomogram's clinical utility in distinguishing between HGGs and LGGs.</p><p><strong>Results: </strong>The study included 582 patients (mean age: 52±14 years; 57.91% male). No significant differences in age or sex were found between the training and testing groups (P>0.05). For RFs, 73.02% of the 215 extracted features were selected based on inter-class correlation coefficients (ICCs), while for DFs, 38.27% of the 15,680 extracted features were selected. Optimal penalization coefficients lambda (λ) for RFs and DFs were determined using a five-fold cross-validation and minimal criteria process. The resulting receiver operating characteristic-area under the curve (ROC-AUC) values were 0.93 [95% confidence interval (CI): 0.91-0.94] for the training set and 0.91 (95% CI: 0.89-0.93) for the testing set. The Hosmer-Lemeshow test yielded P values of 0.619 and 0.547 for the training and testing sets, respectively, indicating satisfactory calibration. The nomogram demonstrated the highest net benefit (NB) up to a threshold of 0.7, followed by DFs and RFs.</p><p><strong>Conclusions: </strong>This study underscores the efficacy of integrating RFs and DFs alongside clinical data to accurately predict the pathological grading of HGGs and LGGs, offering a comprehensive approach for clinical decision-making.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 2","pages":"1125-1138"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11847178/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494582","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}