Insights into Imaging最新文献

{"title":"Risk factor analysis of iodinated contrast medium-related hypersensitivity reactions.","authors":"Lukas Beiner, Ingrid Boehm","doi":"10.1186/s13244-025-02099-y","DOIUrl":"10.1186/s13244-025-02099-y","url":null,"abstract":"<p><p>Hypersensitivity reactions caused by iodinated contrast media (ICM) are by definition type B adverse reactions and therefore, they are not predictable. To partially limit this uncertainty, since the 1980s, risk factors have been defined and published. Currently, there are so many risks that any patient undergoing a contrast-enhanced imaging examination would have at least one risk. This is not helpful and instead leads to uncertainty again. From both studies and clinical experience, we know that only a small percentage of patients develop hypersensitivity reactions after ICM administration. Therefore, we subjected the risks published to a critical analysis. Based on 126 publications, we identified 43 risks, which were divided into three categories (patient-related, contrast agent-related and management-related risks). We have also mentioned the appropriate management for each risk. After critical assessment, the risk status remains with a history of an ICM-hypersensitivity reaction, acute allergic symptoms, the culprit ICM and documentation errors (e.g., if an iodine allergy is mentioned, a latex allergy is incorrectly suspected as an ICM-allergy or the wrong trigger is documented). In addition, we found that several risks have been named differently, although they cover the same risk situation (e.g., chronic/severe disease and frequent ICM applications). Furthermore, for several of the published risks, no mitigation measures are available. Taken together, of the large number of published risks, only those with risk status should be used clinically in the future. Known risk factors do not influence the nature of type B reactions. Critical relevance statement For patient safety, it would be advisable in the future to consider the following three risks: a history of an ICM-hypersensitivity reaction, acute allergic symptoms and documentation errors (e.g., if an iodine allergy is mentioned, a latex allergy is incorrectly suspected as an ICM-allergy or the wrong trigger is documented). KEY POINTS: Risk factors are intended to limit the unpredictability of ICM hypersensitivity reactions. Currently, risks are nonspecific and ultimately apply to all patients. We found that identical factors are published under different names. Four risks are relevant: history of ICM-HSR, acute allergy, the culprit ICM and documentation/management errors.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"216"},"PeriodicalIF":4.5,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12514124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145274658","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":"CT-based radiomics nomogram to predict response of advanced adenocarcinoma of esophagogastric junction to neoadjuvant chemotherapy.","authors":"Chuan-Qinyuan Zhou, Yue-Su Wang, Wen-Han Liao, Jing-Ke Li, Xin-Yi Liao, Yan Gui, Xiao-Ming Zhang, Tian-Wu Chen","doi":"10.1186/s13244-025-02103-5","DOIUrl":"10.1186/s13244-025-02103-5","url":null,"abstract":"<p><strong>Objective: </strong>To establish and validate a CT-based radiomics model to predict the response of adenocarcinoma of the esophagogastric junction (AEG) to neoadjuvant chemotherapy (NAC).</p><p><strong>Methods: </strong>259 consecutive AEG patients, receiving 3 cycles of NAC with docetaxel, oxaliplatin and S-1, were retrospectively retrieved from two centers. Patients from center 1 were randomly divided into training (n = 139) and internal validation (n = 60) cohorts. Patients from center 2 were assigned to the external validation cohort (n = 60). In the training cohort, tumour-region-based radiomics features were selected, and a radiomics model was established to differentiate between patients with disease control and those with disease progression. Clinical factors were selected to develop a clinical model, and were incorporated with radiomics features to develop a radiomics-clinical model. Models' predictive performance and calibration ability were assessed with the area under the ROC curve (AUC) and calibration curve analysis, respectively. Decision curve analysis was used to evaluate the net clinical benefit of the models.</p><p><strong>Results: </strong>The radiomics model was developed with 9 core radiomics features, the clinical model was established by incorporating gross tumor volume, cT stage and Siewert type, and the clinical-radiomics model was established and plotted the nomogram. The clinical-radiomics model obtained better performance than the clinical or radiomics model (AUCs: 0.903 vs. 0.824 or 0.823, 0.899 vs. 0.813 or 0.800, and 0.895 vs. 0.804 or 0.719) in training, internal validation and external validation sets, respectively. The clinical-radiomics model showed the best calibration ability and the highest net benefit.</p><p><strong>Conclusion: </strong>The clinical-radiomics model can well predict the response of AEG to NAC.</p><p><strong>Critical relevance statement: </strong>We provided a radiomics-clinical model to well predict the response of adenocarcinoma of the esophagogastric junction to neoadjuvant chemotherapy, which can help select appropriate patients to undergo chemotherapy, avoiding inappropriate patients from enduring toxic side-effects due to chemotherapy and delaying other treatments.</p><p><strong>Key points: </strong>A radiomics model for adenocarcinoma of the esophagogastric junction can predict the response to neoadjuvant chemotherapy. A combined model integrating clinical and radiomics features can improve predictive performance. The combined model is helpful for clinicians to develop individualized treatment regimens.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"215"},"PeriodicalIF":4.5,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12508337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145250956","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":"Creeping fat is associated with transmural healing in patients with Crohn's disease receiving ustekinumab.","authors":"Fangling Zhang, Minyi Guo, Pan Zhu, Kexin Niu, Jie Zhou, Ling Wang, Peiyi Xie, Lishuo Shi, Xiaochun Meng","doi":"10.1186/s13244-025-02101-7","DOIUrl":"10.1186/s13244-025-02101-7","url":null,"abstract":"<p><strong>Objectives: </strong>We investigated whether body composition parameters assessed on baseline computed tomography enterography (CTE) could predict transmural healing (TH) in patients with Crohn's disease (CD) receiving Ustekinumab (UST).</p><p><strong>Materials and methods: </strong>Adult patients with active CD treated with standard UST from August 2020 to August 2022 were enrolled. Body composition, including creeping fat (CF, mesenteric creeping fat index (MCFI) and fibrofatty proliferation score), skeletal muscle, visceral adipose, and subcutaneous adipose-related parameters were assessed on baseline CTE. Cox regression analysis was performed to identify independent predictors of TH.</p><p><strong>Results: </strong>This study included 113 patients, and TH occurred in 26 (23. 0%) patients. The results of the univariable analysis indicated a statistically significant association of the presence of sarcopenia, higher MCFI score, and higher fibrofatty proliferation score with an increased failure rate of TH. We found no evidence that skeletal muscle index, subcutaneous adipose index, visceral adipose index, and visceral adipose/subcutaneous adipose area ratio were associated with TH. Multivariable analysis revealed that sarcopenia (Hazard ratio (HR): 0.35, 95% CI: 0.14-0.87, p = 0.023), MCFI score (HR: 0.67, 95% CI: 0.49-0.91, p = 0.010) and fibrofatty proliferation score (HR: 0.50, 95% CI: 0.29-0.85, p = 0.011) remained significant. MCFI score (χ²-df = 5.58) was the most critical factor for TH prediction, followed by fibrofatty proliferation score (χ²-df = 5.43) and sarcopenia (χ²-df = 4.12).</p><p><strong>Conclusions: </strong>Among all the body composition parameters, MCFI and fibrofatty proliferation score assessed on baseline CTE were independently associated with TH, and they demonstrated greater predictive efficacy compared to sarcopenia.</p><p><strong>Critical relevance statement: </strong>Creeping fat on baseline CTE was an important predictive factor for transmural healing in patients with Crohn's disease receiving Ustekinumab, which enables early risk stratification of patients and has potential implications for decision-making.</p><p><strong>Key points: </strong>Identifying predictors of transmural healing may provide insight into earlier dose optimization to improve the rate of transmural healing. Higher creeping fat scores (mesenteric creeping fat index and fibrofatty proliferation) were independently associated with a lower rate of transmural healing. Mesenteric creeping fat index and fibrofatty proliferation score demonstrated greater predictive efficacy compared to sarcopenia.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"214"},"PeriodicalIF":4.5,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12496395/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228429","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":"MRI analysis of distal tibiofibular joint and ankle anatomy to assess lateral ankle sprain risk.","authors":"João Vieira, Ana Catarina Vieira, Alberto Vieira","doi":"10.1186/s13244-025-02102-6","DOIUrl":"10.1186/s13244-025-02102-6","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the risk of lateral ankle sprain (LAS) related to bone anatomical variations of the distal tibiofibular syndesmosis (DTS) and the height of both malleolar articular surfaces.</p><p><strong>Materials and methods: </strong>This retrospective cohort study included patients undergoing evaluation and assessment of quantitative parameters of the DTS and height of both malleolar articular surfaces in ankle MRI. Of the 216 patients included, 116 suffered LAS (53.7%). The measurements of the DTS were: anterior facet length of the fibular notch (a), posterior facet length of the fibular notch (b), angle between the anterior and posterior facets (c), fibular notch depth (d), tibial thickness (e), and fibular thickness (f). A subjective morphological analysis of the DTS was also assessed. The measurements of the malleolar articular surface length were: medial malleolar articular surface height (h), lateral malleolar articular surface height (i), and width of the talar dome articular surface (j).</p><p><strong>Results: </strong>Evaluating the DTS, patients with LAS showed a greater c (p < 0.001), a higher a/b (p = 0.013), and a lower d/e (p < 0.001). A plane DTS was also found to be a risk factor for sprain. Additionally, patients with LAS exhibited a lower i/j (p = 0.003). Indeed, the values of c, a/b, and i/j were independent predictors of LAS (p < 0.001, p = 0.015, p = 0.011).</p><p><strong>Conclusion: </strong>Anatomical factors of the DTS and lateral malleolus articular surface were predictors of the presence of LAS, mainly the angle and ratio between the anterior and the posterior facets and the ratio between the lateral malleolar height and the width of the talar articular surface.</p><p><strong>Critical relevance statement: </strong>Lateral ankle sprains are one of the most common musculoskeletal injuries, and the predisposing anatomical factors are not clear. This study correlates anatomical variants of the distal tibiofibular syndesmosis and the height of both malleoli with lateral ankle sprain.</p><p><strong>Key points: </strong>What specific bony variations in the distal tibiofibular syndesmosis and malleolar-talus relationship may predispose individuals to lateral ankle sprains? A shallow fibular notch, flat-type syndesmosis, and a lower lateral malleolar height/talar width ratio are more often found in first lateral ankle sprains. Understanding these anatomical variations may aid in injury prevention and improve risk assessment.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"213"},"PeriodicalIF":4.5,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12496334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225322","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":"3D T1 turbo spin echo improves detection of gadolinium-enhancing multiple-sclerosis lesions.","authors":"Pablo Naval-Baudin, William F Bermúdez Bravo, Vanessa I Pineda-Borja, Pablo Arroyo-Pereiro, Ignacio Martínez-Zalacaín, Lucía Romero-Pinel, Paloma Mora, Nahum Calvo, Antonio Martínez-Yélamos, Sergio Martínez-Yélamos, Mònica Cos, Albert Pons-Escoda, Carles Majós","doi":"10.1186/s13244-025-02093-4","DOIUrl":"10.1186/s13244-025-02093-4","url":null,"abstract":"<p><strong>Objectives: </strong>To compare the performance of 3D T1 turbo spin echo (3DT1TSE) and 3D T1 turbo field echo (3DT1TFE) MRI in detecting gadolinium-enhancing lesions in multiple sclerosis (MS).</p><p><strong>Materials and methods: </strong>We retrospectively analyzed 255 3-T MRIs from MS patients, each including post-contrast 3DT1TSE and 3DT1TFE sequences. Two blinded readers independently assessed enhancing lesions per sequence. A consensus review, incorporating longitudinal imaging and additional sequences, served as the reference standard.</p><p><strong>Results: </strong>The consensus identified 70 enhancing lesions in 31 patients. All 70 were visible on 3DT1TSE, while 64 (91%) were detectable on 3DT1TFE. Reader sensitivity was higher for 3DT1TSE (84% and 90%) than 3DT1TFE (45% and 40%) (p < 0.01). Inter-reader agreement was excellent for 3DT1TSE (ICC = 0.90) and moderate for 3DT1TFE (intraclass correlation coefficient = 0.69). Although false positives were more common with 3DT1TSE, they were readily excluded during consensus reading. In six patients, enhancing lesions were detected only on 3DT1TSE, with treatment escalation in two.</p><p><strong>Conclusion: </strong>3DT1TSE outperformed 3DT1TFE in sensitivity and reader agreement for enhancing lesion detection in MS. Incorporating 3DT1TSE into standard MRI protocols may improve disease activity assessment and clinical decision-making.</p><p><strong>Critical relevance statement: </strong>Replacing 3D gradient-echo with post-contrast 3D T1 turbo spin-echo brain MRI greatly improves the detection of gadolinium-enhancing multiple-sclerosis lesions, boosting diagnostic sensitivity and reader agreement and directly influencing treatment-escalation decisions in routine practice.</p><p><strong>Key points: </strong>Detecting and enhancing MS lesions is limited by standard 3D T1 turbo field echo (3DT1TFE) MRI. 3D T1 turbo spin echo detects significantly more gadolinium-enhancing MS lesions than conventional 3DT1TFE. Greater lesion detection allows more precise activity assessment and optimal treatment management.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"212"},"PeriodicalIF":4.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494509/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225293","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":"Machine learning combined with CT-based radiomics predicts the prognosis of oesophageal squamous cell carcinoma.","authors":"Mingyu Liu, Rongxin Lu, Bo Wang, Jun Fan, Yuheng Wang, Jiashan Zhu, Jinhua Luo","doi":"10.1186/s13244-025-02049-8","DOIUrl":"10.1186/s13244-025-02049-8","url":null,"abstract":"<p><strong>Objectives: </strong>This retrospective study aims to develop a machine learning model integrating preoperative CT radiomics and clinicopathological data to predict 3-year recurrence and recurrence patterns in postoperative oesophageal squamous cell carcinoma.</p><p><strong>Materials and methods: </strong>Tumour regions were segmented using 3D-Slicer, and radiomic features were extracted via Python. LASSO regression selected prognostic features for model integration. Clinicopathological data include tumour length, lymph node positivity, differentiation grade, and neurovascular infiltration. Ultimately, a machine learning model was established by combining the screened imaging feature data and clinicopathological data and validating model performance. A nomogram was constructed for survival prediction, and risk stratification was carried out through the prediction results of the machine learning model and the nomogram. Survival analysis was performed for stage-based patient subgroups across risk stratifications to identify adjuvant therapy-benefiting cohorts.</p><p><strong>Results: </strong>Patients were randomly divided into a 7:3 ratio of 368 patients in the training cohorts and 158 patients in the validation cohorts. The LASSO regression screens out 6 recurrence prediction and 9 recurrence pattern prediction features, respectively. Among 526 patients (mean age 63; 427 males), the model achieved high accuracy in predicting recurrence (training cohort AUC: 0.826 [logistic regression]/0.820 [SVM]; validation cohort: 0.830/0.825) and recurrence patterns (training:0.801/0.799; validation:0.806/0.798). Risk stratification based on a machine learning model and nomogram predictions revealed that adjuvant therapy significantly improved disease-free survival in stages II-III patients with predicted recurrence and low survival (HR 0.372, 95% CI: 0.206-0.669; p < 0.001).</p><p><strong>Conclusion: </strong>Machine learning models exhibit excellent performance in predicting recurrence after surgery for squamous oesophageal cancer.</p><p><strong>Critical relevance statement: </strong>Radiomic features of contrast-enhanced CT imaging can predict the prognosis of patients with oesophageal squamous cell carcinoma, which in turn can help clinicians stratify risk and screen out patient populations that could benefit from adjuvant therapy, thereby aiding medical decision-making.</p><p><strong>Key points: </strong>There is a lack of prognostic models for oesophageal squamous cell carcinoma in current research. The prognostic prediction model that we have developed has high accuracy by combining radiomics features and clinicopathologic data. This model aids in risk stratification of patients and aids clinical decision-making through predictive outcomes.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"211"},"PeriodicalIF":4.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12488548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145199320","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":"Representation of women authorship in the top-cited articles published in the medical imaging literature.","authors":"Hyung Jin Lee, Dae Young Yoon, Sora Baek, Kyoung Ja Lim, Young Lan Seo, Eun Joo Yun","doi":"10.1186/s13244-025-02085-4","DOIUrl":"10.1186/s13244-025-02085-4","url":null,"abstract":"<p><strong>Objective: </strong>To investigate the representation of women among the authors of top-cited articles published in the medical imaging literature.</p><p><strong>Materials and methods: </strong>This retrospective bibliometric study queried the Web of Science database to identify the top-cited articles (citation number ≥ 300) in the medical imaging literature. The gender of the first and last (senior) authors was determined based on online databases. The year of publication, country of origin, document type, and subspecialty for each article were also collected. We analyzed the proportion of women authors and the relationships between author gender and article characteristics.</p><p><strong>Results: </strong>Among 596 top-cited articles, women accounted for 132 (22.1%) of first authors and 84 (14.1%) of last authors. Women as last authors were more likely to publish with women first authors compared to male first authors (odds ratio: 1.35). Women's first authorship was significantly more frequent in articles from South Korea (44.4%; phi = 0.095) and in radiation oncology (38.1%; phi = 0.106) and significantly less frequent in articles from France (0.0%; phi = -0.102). Women's last authorship was significantly more frequent in articles from the Netherlands (30.6%; phi = 0.120), in breast (38.9%; phi = 0.126), and in radiation oncology (28.6%; phi = 0.115), and significantly less frequent in nuclear medicine (4.3%; phi = -0.083).</p><p><strong>Conclusion: </strong>Women authors remain underrepresented in top-cited articles published in the medical imaging literature, with country of origin and subspecialty identified as factors of influence.</p><p><strong>Critical relevance statement: </strong>Women are still underrepresented among the authors of the top-cited articles in the medical imaging literature. The findings highlight the gender disparities in the highest academic achievement in this biomedical field and provide valuable insight into this ongoing issue.</p><p><strong>Key points: </strong>Women authors remain underrepresented in top-cited articles in the medical imaging literature. Women accounted for 22.1% of first authors and 14.1% of last authors. There were variations in the proportion of women authors between countries and subspecialties.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"210"},"PeriodicalIF":4.5,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12476343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145175095","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":"Intratumoral heterogeneity score enhances invasiveness prediction in pulmonary ground-glass nodules via stacking ensemble machine learning.","authors":"Zhichao Zuo, Ying Zeng, Jinqiu Deng, Shanyue Lin, Wanyin Qi, Xiaohong Fan, Yujie Feng","doi":"10.1186/s13244-025-02097-0","DOIUrl":"10.1186/s13244-025-02097-0","url":null,"abstract":"<p><strong>Objectives: </strong>The preoperative differentiation of adenocarcinomas in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma using computed tomography (CT) is crucial for guiding clinical management decisions. However, accurately classifying ground-glass nodules poses a significant challenge. Incorporating quantitative intratumoral heterogeneity scores may improve the accuracy of this ternary classification.</p><p><strong>Materials and methods: </strong>In this multicenter retrospective study, we developed ternary classification models by leveraging insights from both base and stacking ensemble machine learning models, incorporating intratumoral heterogeneity scores along with clinical-radiological features to distinguish adenocarcinomas in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma. The machine learning models were trained, and final model selection depended on maximizing the macro-average area under the curve (macro-AUC) in both the internal and external validation sets.</p><p><strong>Results: </strong>Data from 802 patients from three centers were divided into a training set (n = 477) and an internal test set (n = 205), in a 7:3 ratio, with an additional external validation set comprising 120 patients. The stacking classifier exhibited superior performance relative to the other models, achieving macro-AUC values of 0.7850 and 0.7717 for the internal and external validation sets, respectively. Moreover, an interpretability analysis utilizing the Shapley Additive Explanation identified four key features of this ternary classification: intratumoral heterogeneity score, nodule size, nodule type, and age.</p><p><strong>Conclusion: </strong>The stacking classifier, recognized as the optimal algorithm for integrating the intratumoral heterogeneity score and clinical-radiological features, effectively served as a ternary classification model for assessing the invasiveness of lung adenocarcinoma in chest CT images.</p><p><strong>Critical relevance statement: </strong>Our stacking classifier integrated intratumoral heterogeneity scores and clinical-radiological features to improve the ternary classification of lung adenocarcinoma invasiveness (adenocarcinomas in situ/minimally invasive adenocarcinoma/invasive adenocarcinoma), aiding in precise diagnosis and clinical decision-making for ground-glass nodules.</p><p><strong>Key points: </strong>The intratumoral heterogeneity score effectively assessed the invasiveness of lung adenocarcinoma. The stacking classifier outperformed other methods for this ternary classification task. Intratumoral heterogeneity score, nodule size, nodule type, and age predict invasiveness.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"209"},"PeriodicalIF":4.5,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474818/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145175027","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":"Image-guided biopsy of breast lesions-when to use what biopsy technique.","authors":"Wendelien B G Sanderink, Julia Camps-Herrero, Alexandra Athanasiou, Henrique L Couto, Kirti Mehta, Popat Palak Bhavesh Thakkar, Pooja Jagmohan, Sara E Vázquez-Manjarrez, Seigo Nakamura, Jelle Wesseling, Ritse M Mann","doi":"10.1186/s13244-025-02084-5","DOIUrl":"10.1186/s13244-025-02084-5","url":null,"abstract":"<p><p>In recent years, minimally invasive diagnostic options for breast lesions have expanded, but consensus on optimal biopsy techniques and imaging combinations remains lacking. This study, driven by an adapted RAND-UCLA Appropriateness Method and insights from eight experts in breast biopsy from across the world, aims to create consensus for selecting biopsy techniques. Highlighted findings suggest Vacuum-Assisted Biopsy (VAB) for lesions visible exclusively at mammography/tomosynthesis (with or without contrast enhancement) or MRI. Core-needle biopsy (CNB) takes precedence for masses over 5 mm visible under US. The selection of other biopsy techniques during US-guided procedures depends on lesion type, size, and sampling indication. VAB is preferred for smaller masses (< 5 mm), complex cystic and solid lesions with small solid parts, small intraductal masses, architectural distortions, and calcifications visible on US. In re-biopsy scenarios for inconclusive findings or high-risk lesions, the panel suggests two VAB extensions: Extended Vacuum-Assisted Biopsy (EVAB) for unambiguous lesion classification and Vacuum-Assisted Excision (VAE) for complete lesion removal. Furthermore, the panel provides detailed input on how to handle specific cases, such as re-biopsy for lobular neoplasia, flat epithelial atypia and atypical ductal hyperplasia. Surgical excision is advised for DCIS and benign or borderline phyllodes tumors found through initial CNB or VAB. In conclusion, an international expert group formulated recommendations on diagnostic breast biopsies under image guidance, aiming to ensure accurate diagnosis worldwide by providing practical advice on needle selection and biopsy approach. KEY POINTS: Evidence-based literature on the preferred biopsy technique and imaging combination for the diagnosis of breast lesions is sparse, and a general consensus is not available. The selection of biopsy technique for different image-guided procedures depends on lesion type, size, and sampling indication. This international expert panel consensus statement addresses standard approaches for varying biopsy indications.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"208"},"PeriodicalIF":4.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12463797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145137361","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":"Preoperative prediction of microvascular invasion in pancreatic neuroendocrine tumors through analysis of portal venous phase CT images.","authors":"Hai-Yan Chen, Yao Pan, Yu-Wei Li, Li-Ting Shi, Jie-Yu Chen, Yun-Ying Liu, Ri-Sheng Yu, Lei Shi","doi":"10.1186/s13244-025-02091-6","DOIUrl":"10.1186/s13244-025-02091-6","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate clinical and CT imaging features on portal venous-phase for predicting microvascular invasion (MVI) in patients with pancreatic neuroendocrine tumors (PNETs) and compare survival outcomes.</p><p><strong>Materials and methods: </strong>In this retrospective study, 160 patients (training group) and 28 (validation group) who underwent surgical resection for PNETs were included. Demographic data and CT features were collected. The independent predictive factors for predicting MVI were confirmed through univariate and multivariate logistic regression analyses. The predictive performance was assessed by employing the receiver operating characteristic curve for predicting MVI. An R/shiny app based on logistic regression was developed. A Kaplan-Meier survival analysis with a log-rank test was conducted.</p><p><strong>Results: </strong>In the training group, invasion of surrounding tissues (odds ratio [OR]: 4.12), absolute enhancement (OR: 0.84), and relative enhancement ratio (OR: 16.1) were identified as independent predictors for predicting MVI in PNET patients, with an area under the curve of 0.819 and 0.891 in the training and validation groups, respectively. We have successfully developed a user-friendly web-based R/shiny app for real-time prediction of MVI in patients with PNETs. The median overall survival for patients with MVI was 12 months, compared to 37.5 months for those without MVI (log-rank p = 0.034).</p><p><strong>Conclusions: </strong>Imaging features from portal venous-phase CT images can be used to accurately predict the presence of MVI in patients with PNETs. Patients with MVI are associated with worse survival compared to those without MVI. The web-based R/shiny app for predicting MVI provides real-time data-driven estimates of predictive value to facilitate informed decision-making.</p><p><strong>Critical relevance statement: </strong>Imaging features can accurately predict MVI in patients with PNETs, and the web-based R/shiny app provides real-time, data-driven estimates to enhance decision-making, thereby streamlining clinical practice.</p><p><strong>Key points: </strong>The presence of microvascular invasion (MVI) in patients was associated with worse survival. Surrounding tissue invasion and absolute/relative enhancement ratio were identified as independent predictors for MVI. This web-based app predicts MVI and provides real-time data-driven estimates of predictive value.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"206"},"PeriodicalIF":4.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12463792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145137325","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}