Academic Radiology最新文献

{"title":"Factors associated with malignant biopsy results for newly detected lesions within one year after breast cancer surgery.","authors":"Arim Yeom, Eun Young Ko, Chorong Seo, Haejung Kim, Myoung Kyoung Kim, Boo-Kyung Han, Eun Sook Ko, Ji Soo Choi","doi":"10.1016/j.acra.2024.10.044","DOIUrl":"https://doi.org/10.1016/j.acra.2024.10.044","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>This study aimed to identify the factors associated with malignant biopsy results for new lesions within one year after breast cancer surgery.</p><p><strong>Materials and methods: </strong>This retrospective study included 192 lesions from 186 patients who underwent biopsy for newly developed breast lesions within one year of breast cancer surgery. All patients underwent breast ultrasound (US) at 6 months and breast US with mammography one year after surgery. We analyzed the biopsy results, patient age, characteristics of previous cancers (histologic type, stage, molecular subtype, histologic and nuclear grade, Ki-67 index, extensive intraductal component, lymphovascular invasion (LVI)), history of neoadjuvant chemotherapy (NAC), adjuvant therapy, and characteristics of biopsied lesions (location, mode of detection, imaging features, and Breast Imaging Reporting and Data System category). Multivariate logistic regression was performed to predict malignant results after a biopsy of the new lesion in the early postoperative period.</p><p><strong>Results: </strong>The mean patient age was 49.0 (range, 28-82) years. During follow-up, 137 lesions developed in the ipsilateral remnant breast or mastectomy bed, and 55 lesions developed in the contralateral breast. In total, 37 (19.3%) of the biopsied lesions were malignant, and the following conditions were associated with malignant results in the newly detected lesions: irregularly shaped hypoechoic mass with increased vascularity, presence of previous LVI, history of NAC, and no history of adjuvant radiotherapy or hormone therapy in the indicated patients.</p><p><strong>Conclusion: </strong>Active biopsy may be warranted for new lesions with suspicious imaging findings in the breast or operation bed of patients with LVI, a history of NAC, and no history of adjuvant radiotherapy or hormone therapy, even within one year of breast cancer surgery.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of predictive performance for new vertebral compression fracture between Hounsfield units value and vertebral bone quality score following percutaneous vertebroplasty or kyphoplasty.","authors":"Zhengbo Wang, Lingzhi Li, Tianyou Zhang, Ruya Li, Wei Ren, Helong Zhang, Zhiwen Tao, Yongxin Ren","doi":"10.1016/j.acra.2024.11.039","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.039","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>New vertebral compression fractures (NVCF) are very common in patients following percutaneous vertebroplasty (PVP) or kyphoplasty (PKP). The study aims to evaluate the comparative predictive performance of vertebral bone quality (VBQ) score and Hounsfield units (HU) value in forecasting NVCF after surgery.</p><p><strong>Materials and methods: </strong>This study retrospectively analyzed patients who underwent PVP/PKP at our institution between 2020 and 2021. The VBQ score and HU value were obtained from preoperative magnetic resonance imaging (MRI) and computed tomography (CT) scans, respectively. Subsequently, the forecasting capabilities of these two parameters were assessed by contrasting their receiver operating characteristic (ROC) curve.</p><p><strong>Results: </strong>A total of 303 eligible patients (56 with NVCF and 247 without) were identified in the study. Six relevant literature factors were identified and included in the multivariate analysis revealed that lower HU value (OR = 0.967, 95% CI = 0.953-0.981, P < 0.001) and higher VBQ score (OR = 3.964, 95% CI = 2.369-6.631, P < 0.001) emerged as independent predictors of NCVF occurrence. Compared to the ROC curve of the HU value, demonstrating a diagnostic accuracy of 83.2% (95% CI = 77.5%-88.9%, P < 0.001), the VBQ score was 85.8%. And, a statistically significant negative correlation was observed between the VBQ score and the T-score (r = -0.529, P < 0.001).</p><p><strong>Conclusion: </strong>In patients undergoing PVP/PKP, VBQ score, and HU value are independently associated with the occurrence of NVCF. Assessing the HU value and the VBQ score could play an effective role in planning PVP/PKP operations.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual MR Elastography and Multi-b-value DWI Models for Predicting Microvascular Invasion in Solitary BCLC Stage A Hepatocellular Carcinoma.","authors":"Zhaowei Chen, Yongjian Zhu, Leyao Wang, Rong Cong, Bing Feng, Wei Cai, Meng Liang, Dengfeng Li, Shuang Wang, Mancang Hu, Yongtao Mi, Sicong Wang, Xiaohong Ma, Xinming Zhao","doi":"10.1016/j.acra.2024.11.027","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.027","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To evaluate the performance of virtual MR elastography (vMRE) for predicting microvascular invasion (MVI) in Barcelona Clinic Liver Cancer (BCLC) stage A (≤ 5.0 cm) hepatocellular carcinoma (HCC) and to construct a combined nomogram based on vMRE, multi-b-value DWI models, and clinical-radiological (CR) features.</p><p><strong>Methods: </strong>Consecutive patients with suspected HCC who underwent multi-b-value DWI examinations were prospectively collected. Quantitative parameters from vMRE, mono-exponential, intravoxel incoherent motion, and diffusion kurtosis imaging models were obtained. Multivariate logistic regression was used to identify independent MVI predictors and build prediction models. A combined MRI_Score was constructed using independent quantitative parameters. A visualized nomogram was built based on significant CR features and MRI_Score. The predictive performance of quantitative parameters and models was evaluated.</p><p><strong>Results: </strong>The study included 103 patients (median age: 56 years; range: 35-70 years; 87 males and 16 females). Diffusion-based shear modulus (μ_Diff) exhibited a predictive performance for MVI with area under the curve (AUC) of 0.735. The MRI_Score was developed employing true diffusion coefficient (D), mean kurtosis (MK), and μ_Diff. CR model and MRI_Score achieved AUCs of 0.787 and 0.840, respectively. The combined nomogram based on AFP, corona enhancement, tumor capsule, TTPVI, and MRI_Score significantly improved the predictive performance to an AUC of 0.931 (Delong test p < 0.05).</p><p><strong>Conclusion: </strong>vMRE exhibited great potential for predicting MVI in BCLC stage A HCC. The combined nomogram integrating CR features, vMRE, and quantitative diffusion parameters significantly improved the predictive accuracy and could potentially assist clinicians in identifying appropriate treatment options.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing High Clinical Volumes and Non-RVU Generating Activities in Radiology, Part ll: Future Directions.","authors":"Parisa Mazaheri, Gary J Whitman, Ariadne K DeSimone, Pablo R Ros, Gregory D Avey, Mohiuddin Hadi, Jay P Narula, Clinton R Williamson, George Vilanilam, Vahid Yaghmai","doi":"10.1016/j.acra.2024.11.007","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.007","url":null,"abstract":"<p><p>The Radiology Research Alliance (RRA) of the Association of Academic Radiology (AAR) creates task forces to study emerging trends shaping the future of radiology. This article highlights the findings of the AAR-RRA Task Force on Balancing High Clinical Volumes and non-relative value unit (Non-RVU)-Generating Activities. The Task Force's mission was to evaluate and emphasize the value of non-RVU-generating activities that academic radiologists perform. The work of this Task Force is presented in two separate manuscripts: Part I outlines the current landscape, while this manuscript, Part II, explores future directions for academic radiology departments seeking a better balance between high clinical workloads and non-RVU-generating opportunities for their faculty.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory Development of a Prognostic Model for Coronary Artery Disease Utilizing CT-FFR Derived Functional Duke Jeopardy Score.","authors":"Li-Na Ouyang, Rui Wang, Qian Wu, Pei Wang, Huai-Rong Zhang, Yuan Li, Li Zhu","doi":"10.1016/j.acra.2024.11.038","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.038","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To explore the prognostic value of the functional Duke Jeopardy Score based on CT-FFR(fDJS_CTA) in assessing major adverse cardiovascular events (MACE) in patients with coronary artery disease (CAD).</p><p><strong>Materials and methods: </strong>A total of 894 patients with stable CAD with stenosis ranging from 30% to 90%, who underwent CCTA were included in the study. Follow-up was performed to record MACE. The patients were randomly divided into training and validation sets in a 7:3 ratio. In the training set, prognostic analysis was performed and predictive model was constructed using univariable and multivariable Cox regressions and compared the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) of different indicators. The receiver operating characteristic curve, calibration curve and clinical decision curve were used to evaluate the model's discrimination, calibration and clinical efficacy.</p><p><strong>Results: </strong>The median follow-up period was 33 (16-36) months, during which 167 cases (18.68%) of MACE occurred. Males accounted for 61.52% (550/894) of the cohort, with a median age of 61.92 years. The multivariate Cox regression analysis indicated that DJS_CTA (HR: 2.07, 95% CI: 1.17 ∼ 3.68) and fDJS_CTA (HR: 4.68, 95% CI: 2.97 ∼ 7.38) were independent predictors of MACE. Using MACE as a standard, fDJS_CTA improved the risk re-stratification ability of CT-FFR (NRI:0.993, P < 0.001) and the predictive ability of CT-FFR (IDI:0.101, P < 0.001) and DJS_CTA (IDI:0.079, P < 0.001). The prediction model demonstrated high discrimination (training AUC: 0.84 [0.80-0.89]; validation AUC: 0.82 [0.75-0.89]), good calibration and clinical efficacy.</p><p><strong>Conclusion: </strong>The fDJS_CTA was the strongest predictor of MACE. The model constructed based on fDJS_CTA has certain clinical utility in prognostic evaluation for CAD.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Prostate Cancer Growth Patterns Impact Detection and Interreader Agreement on Multiparametric MRI.","authors":"Daniel Hausmann, N Rupp, B Kuzmanic, N Spielhofer, J Heimer, V Koelzer, M Nowak, C Gampp, L Hefermehl, R A Kubik-Huch, G Singer, I A Burger","doi":"10.1016/j.acra.2024.10.040","DOIUrl":"https://doi.org/10.1016/j.acra.2024.10.040","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>Multiparametric MRI (mpMRI) substantially improves the detection of significant prostate carcinoma (PCa) compared to systematic biopsy. Nevertheless, mpMRI can overlook aggressive forms of PCa. Recent studies showed, that infiltrative growth (INF) has less restricted diffusion. This study aims to explore the impact of growth patterns on the detection of lesions.</p><p><strong>Materials and methods: </strong>This retrospective study analyzed 52 patients who underwent radical prostatectomy, with preoperative mpMRI. For each patient, one dominant lesion was identified on one whole-mount prostatectomy section. Two pathologists (P1, P2) independently classified the growth pattern whether as expansive (EXP) being defined with at least three 5mm² regions of interest consisting entirely of carcinoma without benign glands or else as infiltrative (INF). Two radiologists (R1, R2) independently classified selected lesions according to PI-RADSv2.1. based on pathological localization. Apparent diffusion coefficient (ADC) values were measured in correlation with matched histopathology slides. Interreader-agreement was evaluated using weighted Cohen's Kappa. The relationship between PI-RADS scores and pathological diagnoses was analyzed using logistic regression.</p><p><strong>Results: </strong>Pathologic lesion characterization regarding growth patterns achieved almost perfect agreement (κ = 0.88), so did PI-RADS classification of mpMRI (κ = 0.90). PI-RADS scores correlated significantly with EXP growth patterns. Average ADC values were lower for EXP lesions (0.83×10^-3 mm²/s, CI: 0.72-0.94×10^-3 mm²/s) compared to INF lesions (0.97×10^-3 mm²/s, CI: 0.86-1.07×10^-3 mm²/s; p = 0.08). On T2 images, 8 of 28 (29%) INF lesions and 1 of 24 (4%) EXP lesions were not visible.</p><p><strong>Conclusion: </strong>PCa missed on mpMRI more frequently demonstrate INF growth patterns. Lesions with EXP growth patterns show lower ADC values and have higher PI-RADS scores.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics Model Based on Contrast-enhanced CT Intratumoral and Peritumoral Features for Predicting Lymphovascular Invasion in Hypopharyngeal Squamous Cell Carcinoma.","authors":"Chenyang Xu, Yifan Ju, Zhiwei Liu, Changling Li, Shengda Cao, Tongliang Xia, Dongmin Wei, Wenming Li, Ye Qian, Dapeng Lei","doi":"10.1016/j.acra.2024.11.017","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.017","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>Patients with Hypopharyngeal Squamous Cell Carcinoma (HSCC) exhibiting lymphovascular invasion (LVI) frequently demonstrate a poor prognosis. We aim to determine whether contrast-enhanced computed tomography (CECT)-derived intratumoral and peritumoral radiomic features could predict the LVI status of HSCC patients.</p><p><strong>Materials and methods: </strong>166 patients with pathologically confirmed HSCC were included in this study, 47 of whom were LVI positive. Preoperative CECT data were randomly divided into a training dataset and a validation dataset in an 8:2 ratio. A total of 1648 radiomics features were extracted from the total tumor volume (GTV) and the surrounding 1- to 5-mm-wide tumor margins (labeled as Peri1V-5V). A deep learning model based on the GTV was also constructed. Radiomics nomograms were established by integrating deep learning model features and clinical features. Receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) were utilized to evaluate and compare the predictive performance of all models.</p><p><strong>Results: </strong>Peri1V-Radscore showed the best prediction efficiency in the validation dataset among all peritumoral models. Among the clinical variables, the upper tumor boundaries and clinical N stage were independent predictors. Compared with the clinical predictor model, Peri1V-Radscore, deep learn model and Nomogram model can improve prediction efficiency in LVI status. Their respective AUC values were 0.94, 0.84, and 0.96. The results of DCA showed that a good net benefit could be obtained from the Peri1V-Radscore model.</p><p><strong>Conclusion: </strong>Intratumoral combined peritumoral radiomics model based on CECT can superior predict LVI status in HSCC patients and may have significant potential for future applications in clinical practice.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response to the letter on prediction tumor and axillary lymph nodes response to Neoadjuvant Chemotherapy based on Ultrasound Deep Learning.","authors":"Yue-Xia Liu, Qing-Hua Liu, Quan-Hui Hu, Jia-Yao Shi, Gui-Lian Liu, Han Liu, Sheng-Chun Shu","doi":"10.1016/j.acra.2024.11.050","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.050","url":null,"abstract":"","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Redesigned American Board of Radiology 16-month Pathway in Nuclear Radiology: Initial Outcomes (2017-2022).","authors":"M Elizabeth Oates, Michelle Brugger, David Laszakovits","doi":"10.1016/j.acra.2024.11.036","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.036","url":null,"abstract":"<p><p>Launched on July 1, 2017, the redesigned American Board of Radiology 16-month Pathway in Nuclear Radiology is flourishing. The original goal of this accelerated training pathway was to help meet the ever-growing demand for nuclear radiology subspecialists in academic and community practices. As of March 1, 2024, 125 graduates of the 16-month pathway had achieved specialty certification in either diagnostic radiology or interventional radiology/diagnostic radiology; nearly 60% had also attained advanced certification in nuclear radiology and/or nuclear medicine. Between March and May 2024, we surveyed this group of 125 specialty board-certified pathway graduates to evaluate the impact of the pathway on their individual careers and on the overall workforce; 69/125 (55%) respondents completed the survey. The vast majority (86%) pursued at least one traditional fellowship after residency, thus becoming multi-subspecialized. The majority (62%) currently work in an academic setting. The vast majority (80%) currently practice nuclear radiology; 40% of those reported that nuclear radiology comprises at least 50% of their time or typical workload. PET/CT represents the predominant modality/service (59%) and a significant minority (11%) perform radiotheranostics/radiopharmaceutical therapies; the vast majority (80%) practice nuclear cardiology. We anticipate that the ABR 16-month pathway will continue to thrive and that its graduates will continue to bring their expertise in this rapidly expanding domain to their clinical practices and research pursuits to the benefit of radiology, medicine, patients, and society.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Growth Prediction of Ground-Glass Nodules Based on Pulmonary Vascular Morphology Nomogram.","authors":"Jingyan Wu, Keying Wang, Lin Deng, Hanzhou Tang, Limin Xue, Ting Yang, Jinwei Qiang","doi":"10.1016/j.acra.2024.11.041","DOIUrl":"https://doi.org/10.1016/j.acra.2024.11.041","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To construct a nomogram combining conventional CT features (CCTFs), morphologically abnormal tumor-related vessels (MATRVs), and clinical features to predict the two-year growth of lung ground-glass nodule (GGN).</p><p><strong>Methods: </strong>High-resolution CT targeted scan images of 158 patients including 167 GGNs from January 2016 to September 2019 were retrospectively analyzed. The CCTF and MATRV of each GGN were recorded. All GGNs were randomly divided into a training set (n = 118) and a validation set (n = 49). Multiple stepwise regression was used to select the features. Multivariate logistic regression was used to construct the CCTF, CCTF-CTRV (category of tumor-related vessel), and CCTF-QTRV (quantity of tumor-related vessel) nomograms. The performance and utility of the nomograms were evaluated using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).</p><p><strong>Results: </strong>The AUC of the CCTF-QTRV nomogram, which included the features of smoking history, nodule pattern, lobulation, and the number of distorted and dilated vessels, was higher than the AUCs of the CCTF and CCTF-CTRV nomograms in both the training set (AUC: 0.906 vs. 0.857; vs. 0.851) and the validation set (AUC: 0.909 vs. 0.796; vs. 0.871). DCA indicated that both patients and clinicians could benefit from using the nomogram.</p><p><strong>Conclusion: </strong>The nomogram constructed by combining MATRV, CCTF, and clinical information can more effectively predict the two-year growth of GGNs. This integrated approach enhances the predictive accuracy, making it a valuable tool for clinicians in managing and monitoring patients with GGNs.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}