Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Dual-layer spectral detector computed tomography for adrenal adenoma characterization: radiation dose reduction and quantitative agreement of multiphase virtual noncontrast with true noncontrast imaging.","authors":"Deying Wen, Wen Li, Ling Zhao, Qinglin Du, Xiaoyu Tong, Ailin Liang, Tengxin Wang, Zheng Li, Xiaodi Zhang, Haiwei Liu, Yan Ren, Jiayu Sun","doi":"10.21037/qims-2025-854","DOIUrl":"10.21037/qims-2025-854","url":null,"abstract":"<p><strong>Background: </strong>Computed tomography (CT) is the preferred imaging modality for evaluating adrenal lesions; however, the associated radiation exposure remains a significant concern. Dual-layer spectral detector CT (SDCT)-derived virtual noncontrast (VNC) images may reduce radiation exposure by eliminating dedicated noncontrast scans, yet their agreement with true noncontrast (TNC) imaging remains debated. This study aimed to quantitatively evaluate the agreement and image quality of VNC images [reconstructed from the arterial phase (VNCa) and portal venous phase (VNCp)] compared to TNC images in adrenal adenomas stratified by lipid content, and to assess the radiation dose reduction.</p><p><strong>Methods: </strong>A total of 103 patients with adrenal adenomas treated at the Adrenal Disease Center of West China Hospital of Sichuan University between March 2023 and September 2024 were enrolled in this prospective study. All patients underwent dual-layer SDCT examination, including TNC and arterial and venous phase scans. VNC images were reconstructed from contrast-enhanced phases. Objective metrics, including CT attenuation value [Hounsfield units (HU)], noise (standard deviation), signal-to-noise ratio (SNR), contrast-to-noise ratio, and absolute attenuation error, and subjective image quality were compared. Interobserver agreement was assessed through the calculation of interclass correlation coefficients. For objective and subjective comparisons between TNC and VNC images, statistical analyses were performed with paired <i>t</i>-tests and Wilcoxon signed-rank tests. The radiation dose with and without TNC was calculated.</p><p><strong>Results: </strong>This study included 103 patients (48 males and 55 females) with a mean age of 51.33±12.55 years. A total of 123 adrenal adenomas were identified, including 28 lipid-rich adenomas and 95 lipid-poor adenomas. For lipid-poor adenomas, VNC and TNC images showed excellent agreement in CT attenuation values (P>0.05), and compared to VNCp images, VNCa images exhibited significantly lower noise (17.44±3.39 <i>vs.</i> 18.64±2.91 HU; P<0.001) and higher SNR (1.68±0.76 <i>vs.</i> 1.55±0.67; P<0.001). In lipid-rich adenomas, VNC images overestimated CT attenuation, showing high absolute attenuation errors (VNCaerror: 9.92±6.49 HU; VNCperror: 8.50±5.17 HU), although these remained within the acceptable threshold of ≤10 HU. In the subjective scores of image quality, TNC images outperformed VNC images [TNC: median 5, interquartile range (IQR) 5-5; VNC: median 5 (IQR 4-5); P<0.001], although VNC scores remained high. No significant statistical difference was observed between the VNCa and VNCp scores (P>0.05). For most of the surrounding nonadenoma tissues, VNC and TNC images demonstrated good agreement, with attenuation differences consistently within ≤10 HU. Replacing TNC images with VNCa images could reduce the effective dose by approximately 32.63% for lipid-poor adenomas.</p><p><strong>Conclus","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7935-7950"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397641/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978588","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":"Comparison of [⁶⁸Ga]Ga-FAPI-04 and [¹⁸F]FDG PET/CT for detection of bone metastases of lung cancer.","authors":"Ji Wu, Yang Meng, Qinyao Li, Chunyin Zhang, Guohao Jiang","doi":"10.21037/qims-2025-234","DOIUrl":"10.21037/qims-2025-234","url":null,"abstract":"<p><strong>Background: </strong>Bone metastases of lung cancer typically indicate disease progression and poor prognosis. Early and accurate detection is crucial for staging, treatment planning, and prognostic evaluation. This study aimed to compare the diagnostic value of gallium 68-labeled fibroblast-activation protein inhibitor-04 ([<sup>68</sup>Ga]Ga-FAPI-04) and fluorine 18-labeled fluorodeoxyglucose ([<sup>18</sup>F]FDG) positron-emission tomography/computed tomography (PET/CT) imaging in detecting bone metastases in lung cancer.</p><p><strong>Methods: </strong>A retrospective analysis was conducted on patients with pathologically confirmed lung cancer and clinically suspected bone metastases. These patients underwent both [<sup>68</sup>Ga]Ga-FAPI-04 and [<sup>18</sup>F]FDG PET/CT imaging. Initially, all patient images were visually evaluated, and the diagnostic efficacy of the two imaging methods was compared at both the patient and lesion levels for detecting bone metastases from lung cancer. Additionally, a semi-quantitative analysis was performed to compare the optimal maximum standardized uptake value (SUVmax) threshold and diagnostic efficacy of the two examinations for diagnosing benign and malignant bone lesions.</p><p><strong>Results: </strong>A total of 25 lung cancer patients were included in the study, with nine confirmed cases and 133 lesions of bone metastases. At the patient level, there were no statistically significant differences in the detection rate, sensitivity, specificity, positive predictive value, negative predictive value, or accuracy between [<sup>68</sup>Ga]Ga-FAPI-04 and [<sup>18</sup>F]FDG PET/CT for identifying patients with bone metastases (P>0.05). At the lesion level, the detection rate, sensitivity, negative predictive value, and accuracy of [<sup>68</sup>Ga]Ga-FAPI-04 PET/CT for detecting bone metastases were higher than those of [<sup>18</sup>F]FDG PET/CT (81.37% <i>vs.</i> 57.14%, 98.50% <i>vs.</i> 69.17%, 88.24% <i>vs.</i> 34.92%, 90.68% <i>vs.</i> 70.81%), with statistically significant differences (P<0.01). The SUVmax of malignant bone lesions on both [<sup>68</sup>Ga]Ga-FAPI-04 and [<sup>18</sup>F]FDG PET/CT was significantly higher than those of benign bone lesions, with statistically significant differences (P<0.05). Moreover, the SUVmax of benign and malignant bone lesions on [<sup>68</sup>Ga]Ga-FAPI-04 PET/CT was significantly higher than those on [<sup>18</sup>F]FDG PET/CT, with statistically significant differences (P<0.01). In [<sup>68</sup>Ga]Ga-FAPI-04 and [<sup>18</sup>F]FDG PET/CT imaging, the area under the curves (AUCs) of SUVmax for diagnosing bone metastases were 0.856 and 0.724, respectively, with statistically significant differences (P<0.05); the optimal diagnostic thresholds were 5.38 and 3.77, respectively. The sensitivity, negative predictive value, and accuracy of SUVmax based on [<sup>68</sup>Ga]Ga-FAPI-04 PET/CT for diagnosing lung cancer bone metastases were higher than thos","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8627-8640"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978552","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":"Artificial intelligence-enhanced ultrasound imaging for thyroid nodule detection and malignancy classification: a study on YOLOv11.","authors":"Jiaqi Yang, Zhigang Luo, Yanting Wen, Jing Zhang","doi":"10.21037/qims-2025-257","DOIUrl":"10.21037/qims-2025-257","url":null,"abstract":"<p><strong>Background: </strong>Thyroid nodules are a common clinical concern, with accurate diagnosis being critical for effective treatment and improved patient outcomes. Traditional ultrasound examinations rely heavily on the physician's experience, which can lead to diagnostic variability. The integration of artificial intelligence (AI) into medical imaging offers a promising solution for enhancing diagnostic accuracy and efficiency. This study aimed to evaluate the effectiveness of the You Only Look Once v. 11 (YOLOv11) model in detecting and classifying thyroid nodules through ultrasound images, with the goal of supporting real-time clinical decision-making and improving diagnostic workflows.</p><p><strong>Methods: </strong>We used the YOLOv11 model to analyze a dataset of 1,503 thyroid ultrasound images, divided into training (1,203 images), validation (150 images), and test (150 images) sets, comprising 742 benign and 778 malignant nodules. Advanced data augmentation and transfer learning techniques were applied to optimize model performance. Comparative analysis was conducted with other YOLO variants (YOLOv3 to YOLOv10) and residual network 50 (ResNet50) to assess their diagnostic capabilities.</p><p><strong>Results: </strong>The YOLOv11 model exhibited superior performance in thyroid nodule detection as compared to other YOLO variants (from YOLOv3 to YOLOv10) and ResNet50. At an intersection over union (IoU) of 0.5, YOLOv11 achieved a precision (P) of 0.841 and recall (R) of 0.823, outperforming ResNet50's P of 0.8333 and R of 0.8025. Among the YOLO variants, YOLOv11 consistently achieved the highest P and R values. For benign nodules, YOLOv11 obtained a P of 0.835 and R of 0.833, while for malignant nodules, it reached a P of 0.846 and a R of 0.813. Within the YOLOv11 model itself, performance varied across different IoU thresholds (0.25, 0.5, 0.7, and 0.9). Lower IoU thresholds generally resulted in better performance metrics, with P and R values decreasing as the IoU threshold increased.</p><p><strong>Conclusions: </strong>YOLOv11 proved to be a powerful tool for thyroid nodule detection and malignancy classification, offering high P and real-time performance. These attributes are vital for dynamic ultrasound examinations and enhancing diagnostic efficiency. Future research will focus on expanding datasets and validating the model's clinical utility in real-time settings.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7964-7976"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397667/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978563","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":"Association analysis of intratumoral metabolic heterogeneity assessed by the hottest lesion based on ¹⁸F-FDG PET/CT with immunochemotherapy response in diffuse large B-cell lymphoma.","authors":"Wenchong Xin, Fei Wang, Weiying Gu, Yuetao Wang","doi":"10.21037/qims-2024-2699","DOIUrl":"10.21037/qims-2024-2699","url":null,"abstract":"<p><strong>Background: </strong>Intratumoral metabolic heterogeneity (MH) assessed by 18-fluorine fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) has been recognized as a potential marker for chemotherapy resistance in solid tumors. However, research on MH in diffuse large B-cell lymphoma (DLBCL) is limited, and its specific relationship with the response to immunochemotherapy (IC) remains unclear. The objective of this study was to investigate optimal approaches for assessing intratumoral MH, and to analyze the association between PET/CT-based MH and end of treatment (EOT) response to IC in DLBCL.</p><p><strong>Methods: </strong>This study retrospectively enrolled 304 newly diagnosed patients with DLBCL who underwent baseline ¹⁸F-FDG PET/CT scanning. Intratumoral MH was assessed by the method of the area under the curve of cumulative standardized uptake value (SUV) histogram (AUC-CSH), heterogeneity index (HI), and coefficient of variation (COV) of target lesion. Both univariate and multivariate logistic regression analyses were employed to investigate the association between intratumoral MH and the response to IC at the EOT. After adjusting for confounding factors, we utilized generalized additive model (GAM) and smooth curve fitting to explore potential nonlinear associations, and a binary logistic regression model was used to assess interactions within subgroups.</p><p><strong>Results: </strong>A total of 70 patients (23%) developed primary progressive disease (PPD) at the EOT. Both AUC-CSH^hottest and HI^hottest were associated with the IC response in DLBCL, with AUC-CSH^hottest slightly superior to HI^hottest. No significant statistical difference was observed for COV. Univariate regression analysis revealed a significant association between AUC-CSH^hottest and the response to IC [odds ratio (OR)/per standard deviation (SD): 0.53; 95% confidence interval (CI): 0.38-0.73; P<0.001]. After adjusting for risk factors, this association remained significant (OR/per SD: 0.58; 95% CI: 0.40-0.85; P=0.006). The GAM indicated a negative linear association between AUC-CSH^hottest and the probability of developing PPD, with the top tertile group having the lowest likelihood of developing PPD (14.8%).</p><p><strong>Conclusions: </strong>In Chinese patients with DLBCL, an approximately negative linear correlation was observed between the AUC-CSH^hottest and the probability of developing PPD at the EOT of frontline IC. In simpler terms, as the degree of intratumoral MH increases, the probability of developing PPD also increases.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8096-8111"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978569","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":"Deep learning-based automated assessment of hepatic fibrosis via magnetic resonance images and nonimage data.","authors":"Weixia Li, Yajing Zhu, Gangde Zhao, Xiaoyan Chen, Xiangtian Zhao, Haimin Xu, Yingyu Che, Yinan Chen, Yuxiang Ye, Xin Dou, Hui Wang, Jingliang Cheng, Qing Xie, Kemin Chen","doi":"10.21037/qims-2024-2506","DOIUrl":"10.21037/qims-2024-2506","url":null,"abstract":"<p><strong>Background: </strong>Accurate staging of hepatic fibrosis is critical for prognostication and management among patients with chronic liver disease, and noninvasive, efficient alternatives to biopsy are urgently needed. This study aimed to evaluate the performance of an automated deep learning (DL) algorithm for fibrosis staging and for differentiating patients with hepatic fibrosis from healthy individuals via magnetic resonance (MR) images with and without additional clinical data.</p><p><strong>Methods: </strong>A total of 500 patients from two medical centers were retrospectively analyzed. DL models were developed based on delayed-phase MR images to predict fibrosis stages. Additional models were constructed by integrating the DL algorithm with nonimaging variables, including serologic biomarkers [aminotransferase-to-platelet ratio index (APRI) and fibrosis index based on four factors (FIB-4)], viral status (hepatitis B and C), and MR scanner parameters. Diagnostic performance, was assessed via the area under the receiver operating characteristic curve (AUROC), and comparisons were through use of the DeLong test. Sensitivity and specificity of the DL and full models (DL plus all clinical features) were compared with those of experienced radiologists and serologic biomarkers via the McNemar test.</p><p><strong>Results: </strong>In the test set, the full model achieved AUROC values of 0.99 [95% confidence interval (CI): 0.94-1.00], 0.98 (95% CI: 0.93-0.99), 0.90 (95% CI: 0.83-0.95), 0.81 (95% CI: 0.73-0.88), and 0.84 (95% CI: 0.76-0.90) for staging F0-4, F1-4, F2-4, F3-4, and F4, respectively. This model significantly outperformed the DL model in early-stage classification (F0-4 and F1-4). Compared with expert radiologists, it showed superior specificity for F0-4 and higher sensitivity across the other four classification tasks. Both the DL and full models showed significantly greater specificity than did the biomarkers for staging advanced fibrosis (F3-4 and F4).</p><p><strong>Conclusions: </strong>The proposed DL algorithm provides a noninvasive method for hepatic fibrosis staging and screening, outperforming both radiologists and conventional biomarkers, and may facilitate improved clinical decision-making.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8250-8264"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397629/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978736","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 models based on clinical and CT features: multivariate analysis for predicting vascular invasion in non-small cell lung cancer.","authors":"Jieling Zhu, Fengjuan Tian, Zongyu Xie, Hengfeng Shi, Ting Yang, Xiaoyu Han, Cheng Yan, Fuquan Wei, Jian Wang","doi":"10.21037/qims-24-1886","DOIUrl":"10.21037/qims-24-1886","url":null,"abstract":"<p><strong>Background: </strong>Lymphovascular invasion (LVI) is a high-risk pathological marker for the evaluation of metastasis and prognosis of non-small cell lung cancer (NSCLC). Preoperative computed tomography (CT) prediction of vascular invasion in NSCLC is essential for clinical identification of high-risk patients and development of treatment strategies. This study aimed to develop and validate a model for predicting LVI in NSCLC based on clinical and CT features.</p><p><strong>Methods: </strong>A total of 2,830 patients with NSCLC confirmed by pathology and with complete clinical data were retrospectively enrolled. Among them, 2,663 were negative cases and 167 were positive cases. CT imaging and pathological data of these patients from Tongde Hospital of Zhejiang Province (center 1) and Anqing Municipal Hospital (center 2), from January 2015 to December 2023, were randomly divided into a training set and a validation set in a ratio of 7:3. Additionally, 275 patients from Taizhou Municipal Hospital (center 3) were assigned to the external validation set, including 242 negative cases and 33 positive cases. After screening for potential risk factors by univariate analysis, the selected risk factors were included in the multivariate binary logistic regression model to determine the independent risk factors of LVI in NSCLC to construct a prediction model and draw a nomogram, and the receiver operating characteristic (ROC) curve, calibration curve, and clinical impact curve (CIC) were used to evaluate the predictive power, discrimination, and clinical benefit of the model.</p><p><strong>Results: </strong>A total of 2,830 patients with NSCLC were included, including 1,190 (42.1%) males and 1,640 (57.9%) females, with a mean age of 61.15±10.83 years. Independent risk factors for LVI of NSCLC included the history of smoking, the history of diabetes mellitus, laboratory tumor indices, mixed ground-glass nodule (mGGN) consolidation/tumor ratio (CTR), and vacuole signs. The area under the curve (AUC), accuracy, sensitivity, and specificity for the training set were 0.836 [95% confidence interval (CI): 0.806-0.867], 65.2%, 92.1%, and 63.5%; those for the validation set were 0.803 (95% CI: 0.755-0.852), 71.6%, 82.7%, and 70.9%; and those for the external validation set were 0.845 (95% CI: 0.775-0.916), 70.9%, 87.8%, and 68.6%, respectively.</p><p><strong>Conclusions: </strong>We developed and validated a model for predicting LVI in NSCLC based on clinical and CT image features. The model developed in this study has potential application value in predicting LVI in NSCLC. It provides a new, operable, and non-invasive technique for clinical identification of high-risk patients and may help clinical selection of appropriate treatment.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8515-8528"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978739","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":"Primary tracheal meningiomas treated with endoscopy: a case description.","authors":"Xiao Li, Jinbing Pan, Jie Zhang","doi":"10.21037/qims-2025-879","DOIUrl":"10.21037/qims-2025-879","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8684-8687"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978712","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":"Prenatal discovery of hereditary hemorrhagic telangiectasia-associated hepatic arteriovenous malformations by multimodal ultrasound and whole-exome sequencing: a rare case description and literature analysis.","authors":"Xiaotian Liu, Guishuang Xiang, Qin Wen, Yitian Long, Yanting Wen","doi":"10.21037/qims-2025-645","DOIUrl":"10.21037/qims-2025-645","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8678-8683"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397690/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978611","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":"Dual-volume reconstruction technology in the detection and classification of recurrent aneurysms following intracranial aneurysm embolization.","authors":"Rui Wang, Shuo Leng, Han Xu, Zhiming Tian, Shujuan Xu, Yi Zhang","doi":"10.21037/qims-2025-303","DOIUrl":"10.21037/qims-2025-303","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Accurate detection of recurrent intracranial aneurysms (ICAs) after embolization is critical for guiding clinical management and preventing re-rupture. Although two-dimensional digital subtraction angiography (2D-DSA) remains the gold standard, its invasive nature limits routine use. Non-invasive imaging modalities such as computed tomography angiography (CTA) and magnetic resonance angiography (MRA) have limitations in detecting small or morphologically complex recurrent aneurysms. This study aimed to evaluate the diagnostic performance of dual-volume reconstruction technology (DVRT) in comparison to CTA and MRA for detecting recurrent ICA and to explore the correlation between aneurysm imaging characteristics and clinical outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This retrospective study included 152 patients who underwent ICA embolization and subsequent follow-up imaging with CTA, MRA, and DVRT. All patients received standardized pre-procedural imaging (CTA, MRA, and DVRT) within 48 hours before intervention to document baseline aneurysm characteristics including size, morphology, and location. Postoperative surveillance was systematically performed using triple-modality imaging (CTA, MRA, and DVRT) at 3- and 12-month intervals to monitor treatment efficacy and detect potential recurrence. For the classification of recurrent aneurysms, post-embolization imaging attributes (size, morphology, location) were compared to pre-embolization baseline data to confirm recurrence. Multivariable logistic regression analysis was applied to pre-embolization characteristics to predict recurrence risk. Visualization techniques, including heatmaps and forest plots, were used to illustrate comparative detection performance.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;DVRT demonstrated higher detection rates for recurrent aneurysms (94.4%, 17/18) compared to CTA (77.8%, 14/18) and MRA (50.0%, 9/18) (P&lt;0.001), with notable performance for small aneurysms (&lt;5 mm: 80.0% &lt;i&gt;vs.&lt;/i&gt; 60.0% &lt;i&gt;vs.&lt;/i&gt; 40.0%; P=0.317) and medium aneurysms (5-10 mm: 100.0% &lt;i&gt;vs.&lt;/i&gt; 88.9% &lt;i&gt;vs.&lt;/i&gt; 55.6%; P=0.012). Morphological analysis showed that DVRT had high detection rates for saccular (100.0% &lt;i&gt;vs.&lt;/i&gt; 88.9% &lt;i&gt;vs.&lt;/i&gt; 66.7%; P=0.039) and lobulated aneurysms (100.0% &lt;i&gt;vs.&lt;/i&gt; 75.0% &lt;i&gt;vs.&lt;/i&gt; 50.0%; P=0.250), while maintaining detection rates of 92.3% for anterior circulation (&lt;i&gt;vs.&lt;/i&gt; 76.9% &lt;i&gt;vs.&lt;/i&gt; 46.2%; P=0.008) and 100.0% for posterior circulation aneurysms (&lt;i&gt;vs.&lt;/i&gt; 80.0% &lt;i&gt;vs.&lt;/i&gt; 60.0%; P=0.200) compared to CTA and MRA, respectively. Multivariable analysis identified size &gt;10 mm [odds ratio (OR) =2.51, 95% confidence interval (CI): 1.83-3.51, P=0.030], irregular morphology (OR =3.02, 95% CI: 2.15-4.43, P=0.003), and posterior location (OR =2.07, 95% CI: 1.43-2.91, P&lt;0.001) as independent predictors of recurrence. Heatmap and forest plot analyses highlighted DVRT's improved diagnostic consistency and narrower CIs across different aneurysm subt","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8008-8022"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397631/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978633","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":"Factors affecting preoperative sentinel lymph nodes contrast-enhanced ultrasound in breast cancer.","authors":"Yijie Dong, Juan Liu, Wanru Jia, Xiaohong Jia, Jingwen Zhang, Ying Zhu, Minjing Mao, Haifeng Ying, Weiwei Zhan, Jianqiao Zhou","doi":"10.21037/qims-2024-2879","DOIUrl":"10.21037/qims-2024-2879","url":null,"abstract":"<p><strong>Background: </strong>Preoperative evaluation of sentinel lymph nodes is very important in breast cancer patients. This study aimed to explore factors affecting the result of preoperative percutaneous contrast-enhanced ultrasound for sentinel lymph nodes (SLN-CEUS) using Sonovue.</p><p><strong>Methods: </strong>A total of 176 patients with breast cancer who underwent preoperative SLN-CEUS to trace axillary sentinel lymph nodes were included. The positive result of SLN-CEUS was defined as both lymphatic vessels and SLN visible. The negative result was defined as the visible lymphatic vessels but the SLNs invisible, and neither lymphatic vessel nor SLNs invisible. Clinical features, histopathology, ultrasound features and doses of contrast agents were analyzed between the positive and negative groups.</p><p><strong>Results: </strong>The diagnostic sensitivity, specificity, and accuracy of SLN-CEUS were 81.5%, 90.7%, and 87.8% respectively. The false negative and false positive rates were 18.5% and 9.3%. Age, distance from the anterior edge of the mass to the body surface (DTS), tumor location, pathologies and lymph nodes metastasis were significantly correlated with the results of SLN-CEUS between the negative and positive groups (P=0.032, 0.035, 0.036, 0.047 and <0.001). Logistic regression showed that age, location, DTS, and lymph node metastasis were independent factors influencing negative SLN-CEUS.</p><p><strong>Conclusions: </strong>In conclusion, independent factors affecting negative results of SLN-CEUS were lymph node metastasis, age, tumor location and DTS.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8125-8136"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978636","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}