British Journal of Radiology最新文献

{"title":"The clinical and pathological evaluation of patients with immunoglobulin A nephropathy by diffusion tensor imaging and intravoxel incoherent motion diffusion-weighted imaging.","authors":"Huan Zhou, Yi Si, Ling Yang, Yi Wang, Yitian Xiao, Yi Tang, Wei Qin","doi":"10.1093/bjr/tqae132","DOIUrl":"10.1093/bjr/tqae132","url":null,"abstract":"<p><strong>Objectives: </strong>To explore the efficacy of diffuse magnetic resonance imaging (MRI) for identifying clinicopathological changes in immunoglobulin A nephropathy (IgAN) patients.</p><p><strong>Methods: </strong>The study enrolled IgAN patients and healthy volunteers. IgAN patients were divided into Group 1 [estimated glomerular filtration rate (eGFR) ≥ 90 mL/min/1.73 m2], Group 2 (60 ≤ eGFR < 90 mL/min/1.73 m2), and Group 3 (eGFR < 60 mL/min/1.73 m2). Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion tensor imaging (DTI) were performed via 3.0 T magnetic resonance. Diffuse MRI, clinical, and pathological indicators were collected and analysed. P < .05 was considered statistically significant.</p><p><strong>Results: </strong>Forty-six IgAN patients and twenty-seven volunteers were enrolled. The apparent diffusion coefficient, diffusion coefficient (D), perfusion fraction (f), and fractional anisotropy (FA) were significantly different among IgAN subgroups and controls. These parameters were positively correlated with eGFR and negatively with creatinine, and inversely correlated with glomerular sclerosis, interstitial fibrosis, and tubular atrophy (all P < .05). They had significantly high area under the curve (AUC) for distinguishing IgAN patients from controls, while FA had the highest AUC in identifying Group 1 IgAN patients from volunteers.</p><p><strong>Conclusions: </strong>DTI and IVIM-DWI had the advantage of evaluating clinical and pathological changes in IgAN patients. DTI was superior at distinguishing early IgAN patients and might be a noninvasive marker for screening early IgAN patients from healthy individuals.</p><p><strong>Advances in knowledge: </strong>DTI and IVIM-DWI could evaluate clinical and pathological changes and correlated with Oxford classification in IgAN patients. They could also identify IgAN patients from healthy populations, while DTI had superiority in differentiating early IgAN patients.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1577-1587"},"PeriodicalIF":1.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11332673/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141791975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of machine learning models for predicting HER2-zero and HER2-low breast cancers.","authors":"Xu Huang, Lei Wu, Yu Liu, Zeyan Xu, Chunling Liu, Zaiyi Liu, Changhong Liang","doi":"10.1093/bjr/tqae124","DOIUrl":"10.1093/bjr/tqae124","url":null,"abstract":"<p><strong>Objectives: </strong>To develop and validate machine learning models for human epidermal growth factor receptor 2 (HER2)-zero and HER2-low using MRI features pre-neoadjuvant therapy (NAT).</p><p><strong>Methods: </strong>Five hundred and sixteen breast cancer patients post-NAT surgery were randomly divided into training (n = 362) and internal validation sets (n = 154) for model building and evaluation. MRI features (tumour diameter, enhancement type, background parenchymal enhancement, enhancement pattern, percentage of enhancement, signal enhancement ratio, breast oedema, and apparent diffusion coefficient) were reviewed. Logistic regression (LR), support vector machine (SVM), k-nearest neighbour (KNN), and extreme gradient boosting (XGBoost) models utilized MRI characteristics for HER2 status assessment in training and validation datasets. The best-performing model generated a HER2 score, which was subsequently correlated with pathological complete response (pCR) and disease-free survival (DFS).</p><p><strong>Results: </strong>The XGBoost model outperformed LR, SVM, and KNN, achieving an area under the receiver operating characteristic curve (AUC) of 0.783 (95% CI, 0.733-0.833) and 0.787 (95% CI, 0.709-0.865) in the validation dataset. Its HER2 score for predicting pCR had an AUC of 0.708 in the training datasets and 0.695 in the validation dataset. Additionally, the low HER2 score was significantly associated with shorter DFS in the validation dataset (hazard ratio: 2.748, 95% CI, 1.016-7.432, P = .037).</p><p><strong>Conclusions: </strong>The XGBoost model could help distinguish HER2-zero and HER2-low breast cancers and has the potential to predict pCR and prognosis in breast cancer patients undergoing NAT.</p><p><strong>Advances in knowledge: </strong>HER2-low-expressing breast cancer can benefit from the HER2-targeted therapy. Prediction of HER2-low expression is crucial for appropriate management. MRI features offer a solution to this clinical issue.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1568-1576"},"PeriodicalIF":1.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11332671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141589676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-energy computed tomography iodine quantification combined with laboratory data for predicting microvascular invasion in hepatocellular carcinoma: a two-centre study.","authors":"Huan Li, Dai Zhang, Jinxia Pei, Jingmei Hu, Xiaohu Li, Bin Liu, Longsheng Wang","doi":"10.1093/bjr/tqae116","DOIUrl":"10.1093/bjr/tqae116","url":null,"abstract":"<p><strong>Objectives: </strong>Microvascular invasion (MVI) is a recognized biomarker associated with poorer prognosis in patients with hepatocellular carcinoma. Dual-energy computed tomography (DECT) is a highly sensitive technique that can determine the iodine concentration (IC) in tumour and provide an indirect evaluation of internal microcirculatory perfusion. This study aimed to assess whether the combination of DECT with laboratory data can improve preoperative MVI prediction.</p><p><strong>Methods: </strong>This retrospective study enrolled 119 patients who underwent DECT liver angiography at 2 medical centres preoperatively. To compare DECT parameters and laboratory findings between MVI-negative and MVI-positive groups, Mann-Whitney U test was used. Additionally, principal component analysis (PCA) was conducted to determine fundamental components. Mann-Whitney U test was applied to determine whether the principal component (PC) scores varied across MVI groups. Finally, a general linear classifier was used to assess the classification ability of each PC score.</p><p><strong>Results: </strong>Significant differences were noted (P < .05) in alpha-fetoprotein (AFP) level, normalized arterial phase IC, and normalized portal phase IC between the MVI groups in the primary and validation datasets. The PC1-PC4 accounted for 67.9% of the variance in the primary dataset, with loadings of 24.1%, 16%, 15.4%, and 12.4%, respectively. In both primary and validation datasets, PC3 and PC4 were significantly different across MVI groups, with area under the curve values of 0.8410 and 0.8373, respectively.</p><p><strong>Conclusions: </strong>The recombination of DECT IC and laboratory features based on varying factor loadings can well predict MVI preoperatively.</p><p><strong>Advances in knowledge: </strong>Utilizing PCA, the amalgamation of DECT IC and laboratory features, considering diverse factor loadings, showed substantial promise in accurately classifying MVI. There have been limited endeavours to establish such a combination, offering a novel paradigm for comprehending data in related research endeavours.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1467-1475"},"PeriodicalIF":1.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11256957/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141316788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abdominal CT findings characteristic of Castleman disease: multi-centre review of 76 adult cases with abdominopelvic nodal involvement.","authors":"Perry J Pickhardt, Vincenzo K Wong, Vincent Mellnick, Mark Sugi, Yashant Aswani","doi":"10.1093/bjr/tqae111","DOIUrl":"10.1093/bjr/tqae111","url":null,"abstract":"<p><strong>Objective: </strong>Characterize the CT findings of abdominopelvic Castleman disease, including a new observation involving the perinodal fat.</p><p><strong>Methods: </strong>Multi-centre search at 5 institutions yielded 76 adults (mean age, 42.1 ± 14.3 years; 38 women/38 men) meeting inclusion criteria of histopathologically proven Castleman disease with nodal involvement at abdominopelvic CT. Retrospective review of the dominant nodal mass was assessed for size, attenuation, and presence of calcification, and for prominence and soft-tissue infiltration of the perinodal fat. Hypervascular nodal enhancement was based on both subjective and objective comparison with aortic blood pool attenuation.</p><p><strong>Results: </strong>Abdominal involvement was unicentric in 48.7% (37/76) and multicentric in 51.3% (39/76), including 31 cases with extra-abdominal involvement. Histopathologic subtypes included hyaline vascular variant (HVV), plasma cell variant (PCV), mixed HVV/PCV, and HHV-8 variant in 39, 25, 3 and 9 cases, respectively. The dominant nodal mass measured 4.4 ± 1.9 cm and 3.2 ± 1.7 cm in mean long- and short-axis, respectively, and appeared hypervascular in 58.6% (41/70 with IV contrast). Internal calcification was seen in 22.4% (17/76). Infiltration of the perinodal fat, with or without hypertrophy, was present in 56.6% (43/76), more frequent with hypervascular vs non-hypervascular nodal masses (80.5% vs 20.7%; P < .001). Among HVV cases, 76.9% were unicentric, 71.1% appeared hypervascular, and 69.2% demonstrated perinodal fat infiltration.</p><p><strong>Conclusion: </strong>Hypervascular nodal masses demonstrating prominence and infiltration of perinodal fat at CT can suggest the specific diagnosis of Castleman disease, especially the HVV.</p><p><strong>Advances in knowledge: </strong>Abdominopelvic nodal masses that demonstrate hypervascular enhancement and prominent infiltration of the perinodal fat at CT can suggest the diagnosis of Castleman disease, but nonetheless requires tissue sampling.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1431-1436"},"PeriodicalIF":1.8,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11256932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141236876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 and BI-RADS guided radiomics model for automatic tumor-infiltrating lymphocytes evaluation in breast cancer.","authors":"Xiangyu Lu, Yingying Jia, Hongjuan Zhang, Ruichao Wu, Wuyuan Zhao, Zihuan Yao, Fang Nie, Yide Ma","doi":"10.1093/bjr/tqae129","DOIUrl":"https://doi.org/10.1093/bjr/tqae129","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate an interpretable radiomics model consistent with clinical decision-making process and realize automatic prediction of tumor-infiltrating lymphocytes (TILs) levels in breast cancer (BC) from ultrasound (US) images.</p><p><strong>Methods: </strong>A total of 378 patients with invasive BC confirmed by pathological results were retrospectively enrolled in this study. Radiomics features were extracted guided by the BI-RADS lexicon from the regions of interest(ROIs) segmented with deep learning models. After features selected using the least absolute shrinkage and selection operator(LASSO) regression, four machine learning classifiers were used to establish the radiomics signature(Rad-score). Then, the integrated model was developed on the basis of the best Rad-score incorporating the independent clinical factors for TILs levels prediction.</p><p><strong>Results: </strong>Tumors were segmented using the deep learning models with accuracy of 97.2%, sensitivity of 93.4%, specificity of 98.1%, and the posterior areas were also obtained. Eighteen morphology and texture related features were extracted from the ROIs and fourteen features were selected to construct the Rad-score models. Combined with independent clinical characteristics, the integrated model achieved an area under the curve (AUC) of 0.889(95% CI,0.739,0.990) in the validation cohort and outperformed the traditional radiomics model with AUC of 0.756(0.649-0862) depended on hundreds of feature items.</p><p><strong>Conclusions: </strong>This study established a promising model for TILs levels prediction with numerable interpretable features and showed great potential to help decision-making and clinical applications.</p><p><strong>Advances in knowledge: </strong>Imaging-based biomarkers has provides non-invasive ways for TILs levels evaluation in BC. Our model combining the BI-RADS guided radiomics features and clinical data outperformed the traditional radiomics approaches.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141598531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Desmoid fibromatosis: IR (sometimes) to the rescue for an atypical disease.","authors":"Julien Garnon, Roberto Luigi Cazzato, Pierre-Alexis Autrusseau, Guillaume Koch, Julia Weiss, Justine Gantzer, Jean-Emmanuel Kurtz, Afshin Gangi","doi":"10.1093/bjr/tqae128","DOIUrl":"https://doi.org/10.1093/bjr/tqae128","url":null,"abstract":"<p><p>Desmoid fibromatosis is a rare locally aggressive soft tissue tumor that is characterized as benign as it cannot metastasize. It was managed until recently like sarcomas, i.e with radical surgical resection combined or not with radiotherapy. However, this approach was associated with a high rate of recurrence and significant morbidity. The management of this disease has progressively changed to a more conservative approach given the fact that desmoid fibromatosis may spontaneously stop to grow or even shrink in more than half of the cases. Should treatment be required, recent guidelines recommend choosing between systemic therapies, which include principally chemotherapy and tyrosine kinase inhibitors, and local treatments. And this is where the interventional radiologist may have an important role to treat the disease. Various ablation modalities have been reported in the literature to treat desmoid fibromatosis, notably high-intensity focused ultrasound and cryoablation. Results are promising and cryoablation is now mentioned in recent guidelines. The interventional radiologist should nevertheless apprehend the disease in its globality to understand the place of percutaneous treatments among the other therapeutic options. The goal of this review is therefore to present and discuss the role of interventional radiology (IR) in the management of DF.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141598532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sorafenib plus transcatheter arterial chemoembolization with or without camrelizumab for the treatment of intermediate and advanced hepatocellular carcinoma.","authors":"Bo Sun, Lei Chen, Yu Lei, Lijie Zhang, Tao Sun, Yiming Liu, Chuansheng Zheng","doi":"10.1093/bjr/tqae087","DOIUrl":"10.1093/bjr/tqae087","url":null,"abstract":"<p><strong>Objectives: </strong>To compare the efficacy and safety of transcatheter arterial chemoembolization (TACE) combined with sorafenib and camrelizumab or with sorafenib alone in patients with intermediate or advanced hepatocellular carcinoma (HCC).</p><p><strong>Methods: </strong>We retrospectively analysed 78 patients with intermediate or advanced HCC who were treated at our centres between January 2018 and December 2021. Twenty-six of them received sorafenib and camrelizumab plus TACE (the TACE + Sor + C group), while 52 received TACE and sorafenib (the TACE + Sor group). Overall survival (OS), progression-free survival (PFS), and adverse events (AEs) were evaluated. Univariate and multivariate analyses were used to determine the factors affecting survival.</p><p><strong>Results: </strong>The median OS (22 vs 10 months, P < .001) and median PFS (11 vs 6 months, P = .008) of the TACE + Sor + C group were significantly higher than those of the TACE + Sor group. Multivariate analysis showed that compared with TACE + Sor + C, TACE + Sor increased the risk of all-cause mortality and tumour progression. For grade I and II AEs, the incidence of skin capillary hyperplasia and hypothyroidism in the TACE + Sor + C group was significantly higher than that in the TACE + Sor group. For serious AEs (grade III or IV), there was no significant difference in any adverse reaction between the 2 groups (P > .05).</p><p><strong>Conclusion: </strong>Patients with intermediate or advanced HCC appeared to benefit more in terms of survival from TACE + Sor + C than from TACE + Sor, and the AEs were tolerable.</p><p><strong>Advances in knowledge: </strong>(1) Subgroup analysis demonstrated that TACE + sorafenib + camrelizumab could benefit HCC patients regardless of whether they had portal vein tumour thrombosis, Barcelona Clinic Liver Cancer B or C, or CHILD A or B; (2) We reported the immunotherapy-related AEs occurred with a significantly higher incidence in triple treatment, but all the AEs are tolerable.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1320-1327"},"PeriodicalIF":1.8,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140849296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.","authors":"Jae-Kyun Ryu, Ki Hwan Kim, Chuluunbaatar Otgonbaatar, Da Som Kim, Hackjoon Shim, Jung Wook Seo","doi":"10.1093/bjr/tqae094","DOIUrl":"10.1093/bjr/tqae094","url":null,"abstract":"<p><strong>Objectives: </strong>This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, including hybrid iterative reconstruction (HIR) and deep learning-based reconstruction (DLR).</p><p><strong>Methods: </strong>A retrospective analysis included 66 CCTA patients from July to November 2022. Major coronary arteries were evaluated for image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Stent sharpness was quantified using 10%-90% edge rise slope (ERS) and 10%-90% edge rise distance (ERD). Qualitative analysis employed a 5-point scoring system to assess overall image quality, image noise, vessel wall, and stent structure.</p><p><strong>Results: </strong>SR-DLR demonstrated significantly lower image noise compared to HIR and DLR. SNR and CNR were notably higher in SR-DLR. Stent ERS was significantly improved in SR-DLR, with mean ERD values of 0.70 ± 0.20 mm for SR-DLR, 1.13 ± 0.28 mm for HIR, and 0.85 ± 0.26 mm for DLR. Qualitatively, SR-DLR scored higher in all categories.</p><p><strong>Conclusions: </strong>SR-DLR produces images with lower image noise, leading to improved overall image quality, compared with HIR and DLR. SR-DLR is a valuable image reconstruction algorithm for enhancing the spatial resolution and sharpness of coronary artery stents without being constrained by hardware limitations.</p><p><strong>Advances in knowledge: </strong>The overall image quality was significantly higher in SR-DLR, resulting in sharper coronary artery stents compared to HIR and DLR.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1286-1294"},"PeriodicalIF":1.8,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140907792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthetic MRI and diffusion-weighted imaging for differentiating nasopharyngeal lymphoma from nasopharyngeal carcinoma: combination with morphological features.","authors":"Heng Zhang, Lin Hu, Fanghui Qin, Jun Chang, Yanqi Zhong, Weiqiang Dou, Shudong Hu, Peng Wang","doi":"10.1093/bjr/tqae095","DOIUrl":"10.1093/bjr/tqae095","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the feasibility of synthetic MRI (syMRI), diffusion-weighted imaging (DWI), and their combination with morphological features for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC).</p><p><strong>Methods: </strong>Sixty-nine patients with nasopharyngeal tumours (NPL, n = 22; NPC, n = 47) who underwent syMRI and DWI were retrospectively enrolled between October 2020 and May 2022. syMRI and DWI quantitative parameters (T1, T2, PD, ADC) and morphological features were obtained. Diagnostic performance was assessed by independent sample t-test, chi-square test, logistic regression analysis, receiver operating characteristic curve (ROC), and DeLong test.</p><p><strong>Results: </strong>NPL has significantly lower T2, PD, and ADC values compared to NPC (all P < .05), whereas no significant difference was found in T1 value between these two entities (P > .05). The morphological features of tumour type, skull-base involvement, Waldeyer ring involvement, and lymph nodes involvement region were significantly different between NPL and NPC (all P < .05). The syMRI (T2 + PD) model has better diagnostic efficacy, with AUC, sensitivity, specificity, and accuracy of 0.875, 77.27%, 89.36%, and 85.51%. Compared with syMRI model, syMRI + Morph (PD + Waldeyer ring involvement + lymph nodes involvement region), syMRI + DWI (T2 + PD + ADC), and syMRI + DWI + Morph (PD + ADC + skull-base involvement + Waldeyer ring involvement) models can further improve the diagnostic efficiency (all P < .05). Furthermore, syMRI + DWI + Morph model has excellent diagnostic performance, with AUC, sensitivity, specificity, and accuracy of 0.986, 95.47%, 97.87%, and 97.10%, respectively.</p><p><strong>Conclusion: </strong>syMRI and DWI quantitative parameters were helpful in discriminating NPL from NPC. syMRI + DWI + Morph model has the excellent diagnostic efficiency in differentiating these two entities.</p><p><strong>Advances in knowledge: </strong>syMRI + DWI + morphological feature method can differentiate NPL from NPC with excellent diagnostic performance.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1278-1285"},"PeriodicalIF":1.8,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140907797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-accelerated prostate MRI: a systematic review.","authors":"Ciaran Reinhardt, Hayley Briody, Peter J MacMahon","doi":"10.1093/bjr/tqae093","DOIUrl":"10.1093/bjr/tqae093","url":null,"abstract":"<p><strong>Background: </strong>Prostate cancer ranks among the most prevalent cancers affecting men globally. While conventional MRI serves as a diagnostic tool, its extended acquisition time, associated costs, and strain on healthcare systems, underscore the necessity for more efficient methods. The emergence of AI-acceleration in prostate MRI offers promise to mitigate these challenges.</p><p><strong>Methods: </strong>A systematic review of studies looking at AI-accelerated prostate MRI was conducted, with a focus on acquisition time along with various qualitative and quantitative measurements.</p><p><strong>Results: </strong>Two primary findings were observed. Firstly, all studies indicated that AI-acceleration in MRI achieved notable reductions in acquisition times without compromising image quality. This efficiency offers potential clinical advantages, including reduced scan durations, improved scheduling, diminished patient discomfort, and economic benefits. Secondly, AI demonstrated a beneficial effect in reducing or maintaining artefact levels in T2-weighted images despite this accelerated acquisition time. Inconsistent results were found in all other domains, which were likely influenced by factors such as heterogeneity in methodologies, variability in AI models, and diverse radiologist profiles. These variances underscore the need for larger, more robust studies, standardization, and diverse training datasets for AI models.</p><p><strong>Conclusion: </strong>The integration of AI-acceleration in prostate MRI thus far shows some promising results for efficient and enhanced scanning. These advancements may fill current gaps in early detection and prognosis. However, careful navigation and collaborative efforts are essential to overcome challenges and maximize the potential of this innovative and evolving field.</p><p><strong>Advances in knowledge: </strong>This article reveals overall significant reductions in acquisition time without compromised image quality in AI-accelerated prostate MRI, highlighting potential clinical and diagnostic advantages.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"1234-1242"},"PeriodicalIF":1.8,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140890887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}