Radiomics and deep learning models for CT pre-operative lymph node staging in pancreatic ductal adenocarcinoma: A systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic accuracy of computed tomography (CT)-based radiomic algorithms and deep learning models to preoperatively identify lymph node metastasis (LNM) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: PubMed, CENTRAL, Scopus, Web of Science and IEEE databases were searched to identify relevant studies published up until February 11, 2024. Two reviewers screened all papers independently for eligibility. Studies reporting the accuracy of CT-based radiomics or deep learning models for detecting LNM in PDAC, using histopathology as the reference standard, were included. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2, the Radiomics Quality Score (RQS) and the the METhodological RadiomICs Score (METRICS). Overall sensitivity (SE), specificity (SP), diagnostic odds ratio (DOR), and the area under the curve (AUC) were calculated. RESULTS: Four radiomics studies comprising 213 patients and four deep learning studies with 272 patients were included. The average RQS total score was 12.00 ± 3.89, corresponding to an RQS percentage of 33.33 ± 10.80, while the average METRICS score was 63.60 ± 10.88. A significant and strong positive correlation was found between RQS and METRICS (p = 0.016; r = 0.810). The pooled SE, SP, DOR, and AUC of all the studies were 0.83 (95 %CI = 0.77-0.88), 0.76 (95 %CI = 0.62-0.86), 15.70 (95 %CI = 8.12-27.50) and 0.85 (95 %CI = 0.77-0.88). Meta-regression analysis results indicated that neither the study type (radiomics vs deep learning) nor the dataset size of the studies had a significant effect on the DOR (p = 0.09 and p = 0.26, respectively). CONCLUSION: Based on our meta-analysis findings, preoperative CT-based radiomics algorithms and deep learning models demonstrate favorable performance in predicting LNM in patients with PDAC, with a strong correlation between RQS and METRICS of the included studies.

Evaluation of Interstitial Lung Disease in Idiopathic Inflammatory Myopathies Through Semiquantitative and Quantitative Analysis of Lung Computed Tomography.

PURPOSE: To perform a semiquantitative and quantitative analysis of interstitial lung disease (ILD), through computed tomography (CT), in different serological subgroups of idiopathic inflammatory myopathies (IIM) patients, to find radiologic and clinical differences of disease related to serology. MATERIALS AND METHODS: This was a prospective study, which included 98 IIM patients, divided into serological subgroups: anti-aminoacyl-transfer-RNA-synthetases (anti-ARS) positive and myositis-specific autoantibodies (MSA) negative.For each baseline CT the total semiquantitative score of Warrick (WS) and the automated software (Computer-Aided Lung Informatics for Pathology Evaluation and Rating) quantitative scores interstitial lung disease % (ILD%) and vascular-related structure % (VRS%) were calculated. Pulmonary function tests included total lung capacity % (TLC%), forced vital capacity % (FVC%), and diffusing capacity of the lung for carbon monoxide % (DLCO%). RESULTS: Inverse correlations ( P <0.001) between the radiologic scores and the functional scores DLCO% and TLC% were found, the most relevant being between ILD% and DLCO% (ρ=-0.590), VRS% and DLCO% (ρ=-0.549), and WS and DLCO% (ρ=-0.471).Positive correlations between ILD% and VRS% (ρ=0.916; P <0.001), WS and ILD% (ρ=0.663; ρ<0.001), and WS and VRS% (ρ=0.637; P <0.001) were obtained.Statistically significant higher values of WS, ILD%, and VRS% were found in the anti-ARS group (WS=15; ILD%=11; VRS%=3.5) compared with the MSA negative one (WS=2.5; ILD%=0.84; VRS%=2.2).The nonspecific interstitial pneumonia pattern was dominant. No statistically significant differences emerged at pulmonary function tests. CONCLUSIONS: In this study, ILD in anti-ARS-positive and MSA-negative groups was defined through semiquantitative and quantitative analysis of lung CT. The inverse correlations between the radiologic scores and TLC% and DLCO% ( P <0.001) confirm the role of lung CT in the evaluation of ILD in IIM.

Metastatic BRAF K601E-mutated melanoma reaches complete response to MEK inhibitor trametinib administered for over 36 months.

BACKGROUND: The BRAF K601E mutation occurs in 5% of patients with melanoma, and is the third most common type of BRAF mutation. However, treatment with BRAF and mitogen-activated extracellular signal-regulated kinase (MEK) inhibitors is only approved in patients with BRAF V600-positive melanoma, and patients with K601E-mutated melanoma do not have access to such drugs. CASE PRESENTATION: A female patient was diagnosed with high tumor burden metastatic melanoma harboring the BRAF K601E mutation. After chemotherapy failure, she underwent compassionate treatment with trametinib. Trametinib showed good activity and efficacy, with 48% shrinkage of a metastatic lymphadenopathy after 4 months' treatment. However, the patient reported treatment-related skin toxicity that required dosage reduction and a personalized intermittent trametinib dosing schedule. After over 36 months from the first trametinib administration, and resection of a metastatic lymphadenopathy, the patient experienced complete response. CONCLUSIONS: This case report shows that trametinib could be a valid therapeutic option in patients with metastatic melanoma harboring the rare BRAF K601E mutation.