Cancer Imaging最新文献

{"title":"Glymphatic system dysfunction and cerebrospinal fluid retention in gliomas: evidence from perivascular space diffusion and volumetric analysis.","authors":"Weiqiang Liang, Wenbo Sun, Chunyan Li, Jie Zhou, Changyou Long, Huan Li, Dan Xu, Haibo Xu","doi":"10.1186/s40644-025-00868-y","DOIUrl":"10.1186/s40644-025-00868-y","url":null,"abstract":"<p><strong>Background: </strong>Gliomas may impair glymphatic function and alter cerebrospinal fluid (CSF) dynamics through structural brain changes, potentially affecting peritumoral brain edema (PTBE) and fluid clearance. This study investigated the impact of gliomas on glymphatic system function and CSF volume via diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) and volumetric magnetic resonance imaging (MRI), which clarified the relationships between tumor characteristics and glymphatic system disruption.</p><p><strong>Methods: </strong>In this prospective study, 112 glioma patients and 56 healthy controls underwent MRI to calculate DTI-ALPS indices and perform volumetric analyses of CSF, tumor, and PTBE. Statistical analyses were used to assess the relationships between the DTI-ALPS index, tumor volume, PTBE volume, and clinical characteristics.</p><p><strong>Results: </strong>Glioma patients had significantly lower DTI-ALPS indices (1.266 ± 0.258 vs. 1.395 ± 0.174, p < 0.001) and greater CSF volumes (174.53 ± 34.89 cm³ vs. 154.25 ± 20.89 cm³, p < 0.001) than controls did. The DTI-ALPS index was inversely correlated with tumor volume (r = -0.353, p < 0.001) and PTBE volume (r = -0.266, p = 0.015). High-grade gliomas were associated with lower DTI-ALPS indices and larger PTBE volumes (all p < 0.001). Tumor grade emerged as an independent predictor of the DTI-ALPS index in multivariate analysis (β = -0.244, p = 0.011).</p><p><strong>Conclusion: </strong>Gliomas are associated with significant glymphatic dysfunction, as evidenced by reduced DTI-ALPS indices and increased CSF and PTBE volumes. The DTI-ALPS index serves as a potential biomarker of glymphatic disruption in glioma patients, offering insights into tumor-related fluid changes and the pathophysiology of brain-tumor interactions.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"51"},"PeriodicalIF":3.5,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802612","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":"PET/MRI is superior to PET/CT in detecting oesophago and gastric carcinomas: a meta-analysis.","authors":"Bo Peng, Hui Sun, Jian Hou, Jian-Xing Luo","doi":"10.1186/s40644-025-00871-3","DOIUrl":"10.1186/s40644-025-00871-3","url":null,"abstract":"<p><strong>Objectives: </strong>To compare the accuracy rates of the detection and staging of oesophago and gastric carcinomas between PET/MRI and PET/CT.</p><p><strong>Methods: </strong>An extensive librarian-led literature search of PubMed, Embase, Web of Science, the Cochrane Central Library, and CNKI was performed and a meta-analysis was done.</p><p><strong>Results: </strong>Six studies, including 123 participants, were analyzed. PET/MRI had a comparatively high sensitivity in primary lesion detection compared with PET/CT. (RR = 1.14, 95% CI 1.01-1.29, P = 0.036).PET/MRI had no significant statistical differences in all aspects of TNM staging compared with PET/CT.</p><p><strong>Conclusions: </strong>This systematic review confirmed the advantage of PET/MRI in detecting oesophago and gastric carcinomas.Compared with PET/CT, it can reduce unnecessary radiation exposure and can be used in relevant patients without contraindications of MRI.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"50"},"PeriodicalIF":3.5,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974111/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802614","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":"Correction: Total lesion Glycolysis of primary tumor and lymphnodes is a strong predictor for development of distant metastases in oropharyngeal carcinoma patients with independent validation in automatically delineated lesions.","authors":"Sebastian Zschaeck, Marina Hajiyianni, Patrick Hausmann, Pavel Nikulin, Emily Kukuk, Christian Furth, Paulina Cegla, Elia Lombardo, Joanna Kazmierska, Adrien Holzgreve, Iosif Strouthos, Carmen Stromberger, Claus Belka, Michael Baumann, Mechthild Krause, Guillaume Landry, Witold Cholewinski, Jorg Kotzerke, Daniel Zips, Jörg van den Hoff, Frank Hofheinz","doi":"10.1186/s40644-025-00870-4","DOIUrl":"10.1186/s40644-025-00870-4","url":null,"abstract":"","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"52"},"PeriodicalIF":3.5,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974116/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802610","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":"Predictive value of extracellular volume fraction determined using enhanced computed tomography for pathological grading of clear cell renal cell carcinoma: a preliminary study.","authors":"Jian Liu, Xunlan Zhang, Rui Lv, Xiaoyong Zhang, Rongpin Wang, Xianchun Zeng","doi":"10.1186/s40644-025-00866-0","DOIUrl":"10.1186/s40644-025-00866-0","url":null,"abstract":"<p><strong>Objective: </strong>To explore the potential of using the extracellular volume fraction (ECV), measured through enhanced computed tomography (CT), as a tool for determining the pathological grade of clear cell renal cell carcinoma (ccRCC).</p><p><strong>Methods: </strong>This retrospective study, approved by the institutional review board, included 65 patients (median age: 58.40 ± 10.84 years) who were diagnosed with ccRCC based on the nucleolar grading of the International Society of Urological Pathology (ISUP). All patients underwent preoperative abdominal enhanced CT between January 2022 and August 2024. CT features from the unenhanced, corticomedullary, nephrographic, and delayed phases were analyzed, and the extracellular volume fraction (ECV) of ccRCC was calculated by measuring CT values from regions of interest in both the unenhanced and nephrographic phases. Statistical significance was evaluated for differences in these parameters across the four ISUP grades. Additionally, diagnostic efficiency was assessed using receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>The ECV showed significant differences across the four ISUP grades of ccRCC, its potential as an important predictor of high-grade ccRCC (P = 0.035). The ROC curve analysis indicated that ECV exhibited the highest diagnostic efficacy for assessing the lower- and higher- pathological grade of ccRCC, with an area under the ROC curve of 0.976. The optimal diagnostic threshold for ECV was determined to be 41.64%, with a sensitivity of 91.31% and a specificity of 97.62%.</p><p><strong>Conclusions: </strong>ECV derived from enhanced CT has the potential to function as an in vivo biomarker for distinguishing between lower- and higher-grade ccRCC. This quantitative measure provides diagnostic value that extends beyond traditional qualitative CT features, offering a more precise and objective assessment of tumor grade.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"49"},"PeriodicalIF":3.5,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787980","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 the diagnostic accuracy of enhanced-CT and double contrast-enhanced ultrasound for preoperative T-staging of gastric cancer: a meta-analysis.","authors":"MingYue Lv, Xu Hui, Xin Yang, SuSu Li, ZhiGuo Mao, XinHua Zhang, KeHu Yang","doi":"10.1186/s40644-025-00861-5","DOIUrl":"10.1186/s40644-025-00861-5","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Accurate preoperative staging of gastric cancer (GC) depends on effective diagnostic methods. Enhanced computed tomography (enhanced-CT) is a widely used and reliable preoperative assessment tool for GC, Double Contrast-Enhanced Ultrasound (DCEUS) can display the structure and layers of the gastric wall more accurately, and has high sensitivity (SE) and specificity (SP).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The present study aims to conduct a comprehensive meta-analysis comparing the preoperative T-staging accuracy of DCEUS and enhanced-CT.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A systematic literature search was conducted across PubMed, Embase, Web of Science, and Cochrane Library to identify eligible articles from inception to February 19, 2024. The study included both prospective and retrospective studies involving patients with GC who underwent DCEUS or enhanced-CT. This encompassed studies utilizing comparative diagnostic test accuracy (CDTA) with both DCEUS and enhanced-CT, as well as studies employing single diagnostic test accuracy (SDTA) with either DCEUS or enhanced-CT alone. Risk of bias was assessed using the Quality Assessment Of Diagnostic Accuracy Studies-C (QUADAS-C) and Assessment Of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. The quality of evidence for each outcome was assessed using GRADE (Grading of Recommendations Assessment, Development and Evaluation).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 39 studies involving 6,374 patients were included in this meta-analysis. Among these, 3 studies (319 patients) directly compared dynamic contrast-enhanced ultrasound (DCEUS) and enhanced computed tomography (CT), while 31 studies (5,180 patients) evaluated enhanced CT alone, and 5 studies (875 patients) assessed DCEUS alone. For the direct comparison studies (CDTA), DCEUS demonstrated higher sensitivity (SE) and specificity (SP) for T1-T4 staging compared to enhanced CT, with moderate to low certainty of evidence. Specifically, DCEUS showed superior performance in detecting early-stage (T1) and advanced-stage (T4) tumors. Enhanced CT, while effective, had lower sensitivity across all stages, particularly for T1 tumors. In the single-modality studies (SDTA), DCEUS consistently showed higher sensitivity for T2-T4 staging compared to enhanced CT, with comparable specificity. However, the certainty of evidence for indirect comparisons was very low, highlighting the need for further high-quality comparative studies. Overall, DCEUS appears to be a promising modality for gastric cancer T staging, particularly for early-stage detection, but the limited number of direct comparative studies underscores the need for more robust evidence.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Current evidence indicates that DCEUS significantly outperforms enhanced-CT in terms of SE and diagnostic accuracy for preoperative T-staging of GC, while maintaining comparable SP. However, these findings require further validation through rigorous s","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"48"},"PeriodicalIF":3.5,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11966938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143779251","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 reconstruction and superresolution for MR-guided thermal ablation of malignant liver lesions.","authors":"Moritz T Winkelmann, Jens Kübler, Sebastian Gassenmaier, Dominik M Nickel, Antonia Ashkar, Konstantin Nikolaou, Saif Afat, Rüdiger Hoffmann","doi":"10.1186/s40644-025-00869-x","DOIUrl":"10.1186/s40644-025-00869-x","url":null,"abstract":"<p><strong>Objective: </strong>This study evaluates the impact of deep learning-enhanced T1-weighted VIBE sequences (DL-VIBE) on image quality and procedural parameters during MR-guided thermoablation of liver malignancies, compared to standard VIBE (SD-VIBE).</p><p><strong>Methods: </strong>Between September 2021 and February 2023, 34 patients (mean age: 65.4 years; 13 women) underwent MR-guided microwave ablation on a 1.5 T scanner. Intraprocedural SD-VIBE sequences were retrospectively processed with a deep learning algorithm (DL-VIBE) to reduce noise and enhance sharpness. Two interventional radiologists independently assessed image quality, noise, artifacts, sharpness, diagnostic confidence, and procedural parameters using a 5-point Likert scale. Interrater agreement was analyzed, and noise maps were created to assess signal-to-noise ratio improvements.</p><p><strong>Results: </strong>DL-VIBE significantly improved image quality, reduced artifacts and noise, and enhanced sharpness of liver contours and portal vein branches compared to SD-VIBE (p < 0.01). Procedural metrics, including needle tip detectability, confidence in needle positioning, and ablation zone assessment, were significantly better with DL-VIBE (p < 0.01). Interrater agreement was high (Cohen κ = 0.86). Reconstruction times for DL-VIBE were 3 s for k-space reconstruction and 1 s for superresolution processing. Simulated acquisition modifications reduced breath-hold duration by approximately 2 s.</p><p><strong>Conclusion: </strong>DL-VIBE enhances image quality during MR-guided thermal ablation while improving efficiency through reduced processing and acquisition times.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"47"},"PeriodicalIF":3.5,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11966842/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143771419","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":"Diagnostic model using LI-RADS v2018 for predicting early recurrence of microvascular invasion-negative solitary hepatocellular carcinoma.","authors":"Yingying Liang, Xiaorui Han, Tingwen Zhou, Chuyin Xiao, Changzheng Shi, Xinhua Wei, Hongzhen Wu","doi":"10.1186/s40644-025-00865-1","DOIUrl":"10.1186/s40644-025-00865-1","url":null,"abstract":"<p><strong>Objectives: </strong>To develop a diagnostic model for predicting the early recurrence of microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) after surgical resection, using the Liver Imaging Reporting and Data System (LI-RADS) version 2018.</p><p><strong>Methods: </strong>This retrospective study included 73 patients with MVI-negative HCC who underwent Gadoxetic acid-enhanced MRI (EOB-MRI) scanning before surgical resection. The clinical factors and LI-RADS v2018 MRI features associated with early recurrence were determined using univariable and multivariable analyses. A diagnostic model predicting early recurrence after surgical resection was developed, and its predictive ability was evaluated via a receiver operating characteristic curve. Then, the recurrence-free survival (RFS) rates were analyzed by Kaplan-Meier method.</p><p><strong>Results: </strong>In total, 26 (35.6%) patients were diagnosed with early recurrence according to the follow-up results. Infiltrative appearance and targetoid hepatobiliary phase (HBP) appearance were independent predictors associated with early recurrence (p < 0.05). For the established diagnostic model that incorporated these two significant predictors, the AUC value was 0.76 (95% CI: 0.64-0.85) for predicting early recurrence after resection, which was higher than the infiltrative appearance (AUC: 0.67, 95% CI: 0.55-0.78, p = 0.019) and targetoid HBP appearance (AUC: 0.68, 95% CI:0.57-0.79, p = 0.028). In the RFS analysis, patients with infiltrative appearance and targetoid HBP appearance showed significantly lower RFS rates than those without infiltrative appearance (2-year RFS rate, 48.0% vs. 72.0%; p = 0.009) and targetoid HBP appearance (2-year RFS rate, 60.0% vs. 35.0%; p = 0.003).</p><p><strong>Conclusion: </strong>An EOB-MRI model based on infiltrative appearance and targetoid HBP appearance showed good performance in predicting early recurrence of HCC after surgery, which may provide personalized guidance for clinical treatment decisions in patients with MVI-negative HCC.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"46"},"PeriodicalIF":3.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11956464/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143750951","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 breast MRI for predicting axillary lymph node metastasis: a systematic review and meta-analysis.","authors":"Chia-Fen Lee, Joseph Lin, Yu-Len Huang, Shou-Tung Chen, Chen-Te Chou, Dar-Ren Chen, Wen-Pei Wu","doi":"10.1186/s40644-025-00863-3","DOIUrl":"10.1186/s40644-025-00863-3","url":null,"abstract":"<p><strong>Background: </strong>To perform a systematic review and meta-analysis that assesses the diagnostic performance of deep learning algorithms applied to breast MRI for predicting axillary lymph nodes metastases in patients of breast cancer.</p><p><strong>Methods: </strong>A systematic literature search in PubMed, MEDLINE, and Embase databases for articles published from January 2004 to February 2025. Inclusion criteria were: patients with breast cancer; deep learning using MRI images was applied to predict axillary lymph nodes metastases; sufficient data were present; original research articles. Quality Assessment of Diagnostic Accuracy Studies-AI and Checklist for Artificial Intelligence in Medical Imaging was used to assess the quality. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. A summary receiver operating characteristic curve (SROC) was performed. R statistical software (version 4.4.0) was used for statistical analyses.</p><p><strong>Results: </strong>A total of 10 studies were included. The pooled sensitivity and specificity were 0.76 (95% CI, 0.67-0.83) and 0.81 (95% CI, 0.74-0.87), respectively, with both measures having moderate between-study heterogeneity (I² = 61% and 60%, respectively; p < 0.01). The SROC analysis yielded a weighted AUC of 0.788.</p><p><strong>Conclusion: </strong>This meta-analysis demonstrates that deep learning algorithms applied to breast MRI offer promising diagnostic performance for predicting axillary lymph node metastases in breast cancer patients. Incorporating deep learning into clinical practice may enhance decision-making by providing a non-invasive method to more accurately predict lymph node involvement, potentially reducing unnecessary surgeries.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"44"},"PeriodicalIF":3.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11956454/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143750360","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":"The prognostic significance of semi-quantitative metabolic parameters and tumoral metabolic activity based on ¹²³I-MIBG SPECT/CT in pretreatment neuroblastoma patients.","authors":"Ziang Zhou, Xu Yang, Guanyun Wang, Xiaoya Wang, Jun Liu, Yanfeng Xu, Kan Ying, Wei Wang, Jigang Yang","doi":"10.1186/s40644-025-00858-0","DOIUrl":"10.1186/s40644-025-00858-0","url":null,"abstract":"<p><strong>Purpose: </strong>To assess the prognosis predictive value of semi-quantitative metabolic parameters and tumoral metabolic activity based on ¹²³I-meta-iodobenzylguanidine (MIBG) SPECT/CT in pretreatment neuroblastoma (NB) patients.</p><p><strong>Methods: </strong>A total of 50 children (25 girls, 25 boys, median age 37 months, range 1-102 months) with newly diagnosed NB, consecutively examined with pretherapeutic ¹²³I-MIBG SPECT/CT between 2018 and 2024, were included in this retrospective study. The semi-quantitative metabolic parameters and activity of primary tumor were measured, including Tmax/Lmax, Tmean/Lmean, Tmax/Lmean, Tmax/Mmax, Tmean/Mmean and asphericity (ASP). The ratio was maximum or mean count of primary tumor, liver and muscle. Clinical data and image-related factors was recorded as well. The outcome endpoint was event-free survival (EFS). Independent predictors were identified through univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) and Kaplan Meier analysis with log-rank test for EFS were performed.</p><p><strong>Results: </strong>Median follow-up was 42 months (range 2.5-74 months; 4 patients showed disease progression/relapse, 7 patients died). The univariate and multivariate Cox regression analysis demonstrated that bone/bone marrow metastasis [95% confidence interval (CI): 1.051, 18.570, p = 0.043], Tmax/Lmax (95% CI: 1.074, 1.459, p = 0.004) and ASP (95% CI: 2.618, 273.477, p = 0.006) were independent predictors of EFS. The Kaplan Meier survival analyses demonstrated that Tmax/Lmax undefined[Formula: see text]]]>6 and ASP [Formula: see text]undefined]]>34% and with bone/bone marrow metastasis had worse outcomes.</p><p><strong>Conclusion: </strong>In this exploratory study, pretherapeutic ¹²³I-MIBG image-derived semi-quantitative metabolic parameters and tumor asphericity provided prognostic value for EFS in NB patients. Tmax/Lmax [Formula: see text]undefined]]>6 and ASP [Formula: see text]undefined]]>34%, along with the presence of bone/bone marrow metastasis, could be considered as supplementary factors alongside existing ones.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"45"},"PeriodicalIF":3.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11956495/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751216","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-based habitat imaging predicts high-risk molecular subtypes and early risk assessment of lower-grade gliomas.","authors":"Xiangli Yang, Wenju Niu, Kai Wu, Guoqiang Yang, Hui Zhang","doi":"10.1186/s40644-025-00838-4","DOIUrl":"10.1186/s40644-025-00838-4","url":null,"abstract":"<p><strong>Background: </strong>In lower-grade gliomas (LrGGs, histological grades 2-3), there exist a minority of high-risk molecular subtypes with malignant transformation potential, associated with unfavorable clinical outcomes and shorter survival prognosis. Identifying high-risk molecular subtypes early in LrGGs and conducting preoperative prognostic evaluations are crucial for precise clinical diagnosis and treatment.</p><p><strong>Materials and methods: </strong>We retrospectively collected data from 345 patients with LrGGs and comprehensively screened key high-risk molecular markers. Based on preoperative MRI sequences (CE-T1WI/T2-FLAIR), we employed seven classifiers to construct models based on habitat, radiomics, and combined. Eventually, we identified Extra Trees based on habitat features as the optimal predictive model for identifying high-risk molecular subtypes of LrGGs. Moreover, we developed a prognostic prediction model based on radiomics score (Radscore) to assess the survival outlook of patients with LrGGs. We utilized Kaplan-Meier (KM) survival analysis alongside the log-rank test to discern variations in survival probabilities among high-risk and low-risk cohorts. The concordance index was employed to gauge the efficacy of habitat, clinical, and amalgamated prognosis models. Calibration curves were utilized to appraise the congruence between the anticipated survival probability and the actual survival probability projected by the models.</p><p><strong>Results: </strong>The habitat model for predicting high-risk molecular subtypes of LrGGs, achieved AUCs of 0.802, 0.771, and 0.768 in the training set, internal test set, and external test set, respectively. Comparison among habitat, clinical, combined prognostic models revealed that the combined prognostic model exhibited the highest performance (C-index = 0.781 in the training set, C-index = 0.778 in the internal test set, C-index = 0.743 in the external test set), followed by the habitat prognostic model (C-index = 0.749 in the training set, C-index = 0.716 in the internal test set, C-index = 0.707 in the external test set), while the clinical prognostic model performed the worst (C-index = 0.717 in the training set, C-index = 0.687 in the internal test set, C-index = 0.649 in the external test set). Furthermore, the calibration curves of the combined model exhibited satisfactory alignment when forecasting the 1-year, 2-year, and 3-year survival probabilities of patients with LrGGs.</p><p><strong>Conclusion: </strong>The MRI-based habitat model simultaneously achieves the objectives of non-invasive prediction of high-risk molecular subtypes of LrGGs and assessment of survival prognosis. This has incremental value for early non-invasive warning of malignant transformation in LrGGs and risk-stratified management.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"25 1","pages":"43"},"PeriodicalIF":3.5,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951782/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143742532","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}