The spleen hosts both benign and malignant lesions. Despite multiple imaging modalities, the distinction between these lesions poses a diagnostic challenge, marked by varying diagnostic accuracy levels across methods. In this study, we aimed to evaluate and compare the diagnostic performance of various imaging techniques for detecting malignant splenic lesions. Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Sciences databases for studies evaluating imaging techniques in detecting malignant splenic lesions. Data extraction included diagnostic accuracy metrics, and methodological quality was assessed using QUADAS-2. Diagnostic Test Accuracy meta-analyses were conducted using R (version: 4.2.1). Subgroup analyses and meta-regression were performed to compare different modalities and clinical settings. Our study included 28 studies (pooled sample size: 2358), primarily using retrospective designs with histopathology as the reference standard. PET scan demonstrated the highest diagnostic accuracy (AUC: 92 %), demonstrating a sensitivity of 93 % (95 % CI: 80.4 % - 97.7 %) and a specificity of 82.8 % (95 % CI: 71.1 % - 90.4 %). Contrast-enhanced ultrasound (CEUS), Contrast-enhanced CT scan, and contrast-enhanced MRI also showed impressive performance with AUCs of 91.4 %, 90.9 %, and 85.3 %, respectively. Differences among these modalities were not statistically significant, but they outperformed non-contrast-enhanced methods. PET and CEUS exhibited higher specificity for lymphoma cases compared to studies including other malignancies. Overall, PET emerges as the best modality for splenic malignancies, and CEUS and CE-MRI show promise as potential alternatives, notably due to their reduced radiation exposure. Further research is essential for precise malignancy differentiation.

Neoadjuvant chemotherapy is a standard treatment approach for locally advanced breast cancer. Conventional imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound, have been used for axillary lymph node evaluation which is crucial for treatment planning and prognostication. This systematic review aims to comprehensively examine the current research on applying machine learning algorithms for predicting positive axillary lymph nodes following neoadjuvant chemotherapy utilizing imaging modalities, including MRI, CT, and ultrasound. A systematic search was conducted across databases, including PubMed, Scopus, and Web of Science, to identify relevant studies published up to December 2023. Articles employing machine learning algorithms to predict positive axillary lymph nodes using MRI, CT, or ultrasound data after neoadjuvant chemotherapy were included. The review follows the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, encompassing data extraction and quality assessment. Seven studies were included, comprising 1502 patients. Four studies used MRI, two used CT, and one applied ultrasound. Two studies developed deep-learning models, while five used classic machine-learning models mainly based on multiple regression. Across the studies, the models showed high predictive accuracy, with the best-performing models combining radiomics and clinical data. This systematic review demonstrated the potential of utilizing advanced data analysis techniques, such as deep learning radiomics, in improving the prediction of positive axillary lymph nodes in breast cancer patients following neoadjuvant chemotherapy.

Crohn's disease (CD) is a chronic disorder that often starts at a young age and involves periods of remission and relapse. Prompt diagnosis of relapses through screening is crucial due to the potential morbid complications of untreated active inflammation. Magnetic resonance enterography (MRE) is a noninvasive technique to screen for active inflammation. The standard protocol involves intravenous injection of contrast agents with potential side effects. Some abbreviated non-contrast-enhanced MRE protocols are proposed as alternatives for conventional MRE to identify active inflammation. Currently, there is controversy regarding the applicability and accuracy of these protocols. This study aims to describe and compare these protocols and evaluate their accuracy in detecting active inflammation and CD complications. Results from a systematic search of three databases in August 2022 were queried and screened by abstract and full text. Eligible studies were qualitatively and quantitatively analyzed by diagnostic test accuracy meta-analysis. 59 studies entered the systematic review, and 37 were eligible for meta-analysis. Diffusion-weighted imaging (DWI) and fast T2-weighted (T2w) sequences were most frequently used in abbreviated protocols and showed non-inferior accuracy compared to the full protocol in detecting active inflammation. ADC and qualitative DWI had pooled sensitivity of 90% (CI: 82–95%) and 89% (CI:82–93%) and pooled specificity of 94% (CI: 88–97%) and 89% (CI: 79–94%), respectively for detecting active inflammation. Moreover, T2w and combined T2w+DWI sequences had pooled sensitivity of 80% (CI: 64–90%) and 76% (CI: 61–86%) and pooled specificity of 90% (CI: 80–95%) and 87% (CI: 74 – 94%), respectively. Unenhanced protocols show relatively poor diagnostic accuracy in detecting penetrating complications of CD. Magnetization transfer imaging (MTI) has demonstrated excellent accuracy in detecting fibrosis. High heterogeneity was observed in all subgroups, and accuracy was reported to be highly operator dependent in most studies. An abbreviated protocol consisting of DWI and fast T2w imaging can potentially replace the full protocol MRE. Full protocol MRE will still have its role in identifying penetrating complications. MTI should be indicated in case of suspected fibrostenotic disease.

Background: Breast intraductal lesions present a diagnostic challenge due to the diverse spectrum of histologic changes. Vacuum-assisted biopsy (VAB) has evolved as a pivotal diagnostic and therapeutic modality. Yet, concerns about the underestimation of malignancy using VAB persist. This review examines the underestimation rates of Ultrasound-guided VAB (US-VAB) for intraductal lesions and evaluates the effectiveness of VAB in addressing pathological nipple discharge (PND). Methods: Following PRISMA guidelines, a comprehensive search was performed across Scopus, PubMed, and Web of Science. Studies detailing the underestimation rates of intraductal breast lesions diagnosed by US-VAB and cure rates for PND post-VAB excision were selected. Statistical analysis comprised a random effects proportion meta-analysis. Results: In this research, 31 studies were deemed eligible: 26 for underestimation and 5 for PND cure rates post-US-VAB. Quantitative synthesis focused on studies reporting data on atypical ductal hyperplasia (ADH) or ductal carcinoma in situ (DCIS) due to limited availability for other pathologies. The pooled underestimation rate for ADH was 6.14% (95% CI: 1.59%-12.43%). The pooled underestimation rate for DCIS was 13.26% (95% CI: 6.69%-21.08%). PND's pooled cure rate post-US-VAB was 93.32% (95% CI: 82.34%-99.70%). Conclusion: This systematic review and meta-analysis show that US-VAB delivers low ADH underestimation rates, moderate DCIS underestimation rates, and acceptable PND cure rates in breast intraductal lesions.