Radiology. Imaging cancer最新文献

{"title":"Molecular Breast Imaging Biopsy with a Dual-Detector System.","authors":"Katie N Hunt, Amy Lynn Conners, Lacey Gray, Carrie B Hruska, Michael K O'Connor","doi":"10.1148/rycan.230186","DOIUrl":"10.1148/rycan.230186","url":null,"abstract":"<p><p>Purpose To develop a molecular breast imaging (MBI)-guided biopsy system using dual-detector MBI and to perform initial testing in participants. Materials and Methods The Stereo Navigator MBI Accessory biopsy system comprises a lower detector, upper fenestrated compression paddle, and upper detector. The upper detector retracts, allowing craniocaudal, oblique, or medial or lateral biopsy approaches. The compression paddle allows insertion of a needle guide and needle. Lesion depth is calculated by triangulation of lesion location on the upper detector at 0° and 15° and relative lesion activity on upper and lower detectors. In a prospective study (July 2022-June 2023), participants with Breast Imaging Reporting and Data System category 2, 3, 4, or 5 breast lesions underwent MBI-guided biopsy. After injection of 740 MBq technetium 99m sestamibi, craniocaudal and mediolateral oblique MBI (2-minute acquisition per view) confirmed lesion visualization. A region of interest over the lesion permitted depth calculation in the system software. Upper detector retraction allowed biopsy device placement. Specimen images were obtained on the retracted upper detector, confirming sampling of the target. Results Of 21 participants enrolled (mean age, 50.6 years ± 10.1 [SD]; 21 [100%] women), 17 underwent MBI-guided biopsy with concordant pathology. No lesion was observed at the time of biopsy in four participants. Average lesion size was 17 mm (range, 6-38 mm). Average procedure time, including preprocedure imaging, was 55 minutes ± 13 (range, 38-90 minutes). Pathology results included invasive ductal carcinoma (<i>n</i> = 1), fibroadenoma (<i>n</i> = 4), pseudoangiomatous stromal hyperplasia (<i>n</i> = 6), and fibrocystic changes (<i>n</i> = 6). Conclusion MBI-guided biopsy using a dual-head system with retractable upper detector head was feasible, well tolerated, and efficient. <b>Keywords:</b> Breast Biopsy, Molecular Breast Imaging, Image-guided Biopsy, Molecular Breast Imaging-guided Biopsy, Breast Cancer Clinical trial registration no. NCT06058650 © RSNA, 2024.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 4","pages":"e230186"},"PeriodicalIF":5.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11287224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141284609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Lung-RADS Version 2022 in Classifying Airway Nodules.","authors":"Cristina Marrocchio, Carlotta Zilioli","doi":"10.1148/rycan.249012","DOIUrl":"10.1148/rycan.249012","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e249012"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148832/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141180281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Update on MR Spectroscopy in Cancer Management: Advances in Instrumentation, Acquisition, and Analysis.","authors":"Eva Martinez Luque, Zexuan Liu, Dongsuk Sung, Rachel M Goldberg, Rishab Agarwal, Aditya Bhattacharya, Nadine S Ahmed, Jason W Allen, Candace C Fleischer","doi":"10.1148/rycan.230101","DOIUrl":"10.1148/rycan.230101","url":null,"abstract":"<p><p>MR spectroscopy (MRS) is a noninvasive imaging method enabling chemical and molecular profiling of tissues in a localized, multiplexed, and nonionizing manner. As metabolic reprogramming is a hallmark of cancer, MRS provides valuable metabolic and molecular information for cancer diagnosis, prognosis, treatment monitoring, and patient management. This review provides an update on the use of MRS for clinical cancer management. The first section includes an overview of the principles of MRS, current methods, and conventional metabolites of interest. The remainder of the review is focused on three key areas: advances in instrumentation, specifically ultrahigh-field-strength MRI scanners and hybrid systems; emerging methods for acquisition, including deuterium imaging, hyperpolarized carbon 13 MRI and MRS, chemical exchange saturation transfer, diffusion-weighted MRS, MR fingerprinting, and fast acquisition; and analysis aided by artificial intelligence. The review concludes with future recommendations to facilitate routine use of MRS in cancer management. <b>Keywords:</b> MR Spectroscopy, Spectroscopic Imaging, Molecular Imaging in Oncology, Metabolic Reprogramming, Clinical Cancer Management © RSNA, 2024.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e230101"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148681/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140864152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Whole-Slide Imaging and MRI Data for Outcome Prediction after Prostatectomy in Localized Prostate Cancer.","authors":"Stephanie A Harmon, Baris Turkbey","doi":"10.1148/rycan.240095","DOIUrl":"10.1148/rycan.240095","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e240095"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141087072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of AI Risk Scores on Screening Mammograms Preceding Breast Cancer Diagnosis.","authors":"Sneha Mittal, Maggie Chung","doi":"10.1148/rycan.249011","DOIUrl":"10.1148/rycan.249011","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e249011"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141180172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Validation of a Multimodality Model Based on Whole-Slide Imaging and Biparametric MRI for Predicting Postoperative Biochemical Recurrence in Prostate Cancer.","authors":"Chenhan Hu, Xiaomeng Qiao, Renpeng Huang, Chunhong Hu, Jie Bao, Ximing Wang","doi":"10.1148/rycan.230143","DOIUrl":"10.1148/rycan.230143","url":null,"abstract":"<p><p>Purpose To develop and validate a machine learning multimodality model based on preoperative MRI, surgical whole-slide imaging (WSI), and clinical variables for predicting prostate cancer (PCa) biochemical recurrence (BCR) following radical prostatectomy (RP). Materials and Methods In this retrospective study (September 2015 to April 2021), 363 male patients with PCa who underwent RP were divided into training (<i>n</i> = 254; median age, 69 years [IQR, 64-74 years]) and testing (<i>n</i> = 109; median age, 70 years [IQR, 65-75 years]) sets at a ratio of 7:3. The primary end point was biochemical recurrence-free survival. The least absolute shrinkage and selection operator Cox algorithm was applied to select independent clinical variables and construct the clinical signature. The radiomics signature and pathomics signature were constructed using preoperative MRI and surgical WSI data, respectively. A multimodality model was constructed by combining the radiomics signature, pathomics signature, and clinical signature. Using Harrell concordance index (C index), the predictive performance of the multimodality model for BCR was assessed and compared with all single-modality models, including the radiomics signature, pathomics signature, and clinical signature. Results Both radiomics and pathomics signatures achieved good performance for BCR prediction (C index: 0.742 and 0.730, respectively) on the testing cohort. The multimodality model exhibited the best predictive performance, with a C index of 0.860 on the testing set, which was significantly higher than all single-modality models (all <i>P</i> ≤ .01). Conclusion The multimodality model effectively predicted BCR following RP in patients with PCa and may therefore provide an emerging and accurate tool to assist postoperative individualized treatment. <b>Keywords:</b> MR Imaging, Urinary, Pelvis, Comparative Studies <i>Supplemental material is available for this article</i>. © RSNA, 2024.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e230143"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140959278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum for: The Era of ChatGPT and Large Language Models: Can We Advance Patient-centered Communications Appropriately and Safely?","authors":"Wendy Tu, Bonnie N Joe","doi":"10.1148/rycan.249009","DOIUrl":"10.1148/rycan.249009","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e249009"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148822/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140959281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic Value of Preoperative MRI-derived 3D Quantitative Tumor Arterial Burden in Patients with Hepatocellular Carcinoma Receiving Transarterial Chemoembolization.","authors":"Gang Peng, Xiao-Yu Huang, Ya-Nan Wang, Xiao-Jing Cao, Xiang Zhou","doi":"10.1148/rycan.230167","DOIUrl":"10.1148/rycan.230167","url":null,"abstract":"<p><p>Purpose To investigate the association of tumor arterial burden (TAB) on preoperative MRI with transarterial chemoembolization refractoriness (TACER) and progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC). Materials and Methods This retrospective study included patients with HCC who underwent repeated transarterial chemoembolization (TACE) treatments between January 2013 and December 2020. HCC was confirmed with pathology or imaging, and patients with other tumors, lost follow-up, or with a combination of other treatments were excluded. TACER was defined as viable lesions of more than 50% or increase in tumor number after two or more consecutive TACE treatments, continuous elevation of tumor markers, extrahepatic spread, or vascular invasion. TAB assessed with preoperative MRI was divided into high and low groups according to the median. A Cox proportional hazards model was used to determine the predictors of TACER and PFS. Results A total of 355 patients (median age, 61 years [IQR, 54-67]; 306 [86.2%] men, 49 [13.8%] women) were included. During a median follow-up of 32.7 months, the high TAB group had significantly faster TACER and decreased PFS than the low TAB group (all log-rank <i>P</i> < .001). High TAB was the strongest independent predictor of TACER and PFS in multivariable Cox regression analyses (hazard ratio [HR], 2.23 [95% CI: 1.51, 3.29]; HR, 2.30 [95% CI: 1.61, 3.27], respectively), especially in patients with Barcelona Clinic Liver Cancer stage A or a single tumor. The restricted cubic spline plot demonstrated that the HR of TACER and PFS continuously increased with increasing TAB. Conclusion High preoperative TAB at MRI was a risk factor for faster refractoriness and progression in patients with HCC treated with TACE. <b>Keywords:</b> Interventional-Vascular, MR Angiography, Hepatocellular Carcinoma, Transarterial Chemoembolization, Progression-free Survival, MRI <i>Supplemental material is available for this article.</i> © RSNA, 2024.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e230167"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148827/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140851189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Individual Participant Data Meta-Analyses for Diagnostic Accuracy Research: Challenges and Lessons Learned from the LI-RADS IPD Group.","authors":"Andreu F Costa, Matthew D F McInnes, Christian B van der Pol, Eric Lam, Haben Dawit, Jean-Paul Salameh, Brooke Levis, Mustafa R Bashir","doi":"10.1148/rycan.240015","DOIUrl":"10.1148/rycan.240015","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e240015"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140851188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in Tumor Management: Harnessing the Potential of Histotripsy.","authors":"Yash Verma, Arosh S Perera Molligoda Arachchige","doi":"10.1148/rycan.230159","DOIUrl":"10.1148/rycan.230159","url":null,"abstract":"<p><p>Tissue ablation techniques have long been used in clinical settings to treat various oncologic diseases. However, many of these techniques are invasive and can cause substantial adverse effects. Histotripsy is a noninvasive, nonionizing, nonthermal tissue ablation technique that has the potential to replace surgical interventions in various clinical settings. Histotripsy works by delivering high-intensity focused ultrasound waves to target tissue. These waves create cavitation bubbles within tissues that rapidly expand and collapse, thereby mechanically fractionating the tissue into acellular debris that is subsequently absorbed by the body's immune system. Preclinical and clinical studies have demonstrated the efficacy of histotripsy in treating a range of diseases, including liver, pancreatic, renal, and prostate tumors. Safety outcomes of histotripsy have been generally favorable, with minimal adverse effects reported. However, further studies are needed to optimize the technique and understand its long-term effects. This review aims to discuss the importance of histotripsy as a noninvasive tissue ablation technique, the preclinical and clinical literature on histotripsy and its safety, and the potential applications of histotripsy in clinical practice. <b>Keywords:</b> Tumor Microenvironment, Ultrasound-High-Intensity Focused (HIFU), Ablation Techniques, Abdomen/GI, Genital/Reproductive, Nonthermal Tissue Ablation, Histotripsy, Clinical Trials, Preclinical Applications, Focused Ultrasound © RSNA, 2024.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"6 3","pages":"e230159"},"PeriodicalIF":5.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148838/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140864151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}