OBJECTIVES: This study aims to assess the accuracy of generative pre-trained transformer 4o (GPT-4o) in answering multiple response questions from the European Diploma in Radiology (EDiR) examination, comparing its performance to that of human candidates. MATERIALS AND METHODS: Results from 42 EDiR candidates across Europe were compared to those from 26 fourth-year medical students who answered exclusively using the ChatGPT-4o in a prospective study (October 2024). The challenge consisted of 52 recall or understanding-based EDiR multiple-response questions, all without visual inputs. RESULTS: The GPT-4o achieved a mean score of 82.1 ± 3.0%, significantly outperforming the EDiR candidates with 49.4 ± 10.5% (p < 0.0001). In particular, chatGPT-4o demonstrated higher true positive rates while maintaining lower false positive rates compared to EDiR candidates, with a higher accuracy rate in all radiology subspecialties (p < 0.0001) except informatics (p = 0.20). There was near-perfect agreement between GPT-4 responses (κ = 0.872) and moderate agreement among EDiR participants (κ = 0.334). Exit surveys revealed that all participants used the copy-and-paste feature, and 73% submitted additional questions to clarify responses. CONCLUSIONS: GPT-4o significantly outperformed human candidates in low-order, text-based EDiR multiple-response questions, demonstrating higher accuracy and reliability. These results highlight GPT-4o's potential in answering text-based radiology questions. Further research is necessary to investigate its performance across different question formats and candidate populations to ensure broader applicability and reliability. CRITICAL RELEVANCE STATEMENT: GPT-4o significantly outperforms human candidates in factual radiology text-based questions in the EDiR, excelling especially in identifying correct responses, with a higher accuracy rate compared to radiologists. KEY POINTS: In EDiR text-based questions, ChatGPT-4o scored higher (82%) than EDiR participants (49%). Compared to radiologists, GPT-4o excelled in identifying correct responses. GPT-4o responses demonstrated higher agreement (κ = 0.87) compared to EDiR candidates (κ = 0.33).

• Publication type
• Journal Article MeSH

Colorectal cancer (CRC) is a leading global cause of illness and death. There is a need for identification of better prognostic markers beyond traditional clinical variables like grade and stage. Previous research revealed that abnormal expression of cytokeratin 7 (CK7) and loss of the intestinal-specific Special AT-rich sequence-binding protein 2 (SATB2) are linked to poor CRC prognosis. This study aimed to explore these markers' prognostic significance alongside two extraintestinal mucins (MUC5AC, MUC6), claudin 18, and MUC4 in 285 CRC cases using immunohistochemistry on tissue microarrays (TMAs). CK7 expression and SATB2-loss were associated with MUC5AC, MUC6, and claudin 18 positivity. These findings suggest a distinct "non-intestinal" immunohistochemical profile in CRC, often right-sided, SATB2-low, with atypical expression of CK7 and non-colorectal mucins (MUC5AC, MUC6). Strong MUC4 expression negatively impacted cancer-specific survival (hazard ratio = 2.7, p = 0.044). Genetic analysis via next-generation sequencing (NGS) in CK7 + CRCs and those with high MUC4 expression revealed prevalent mutations in TP53, APC, BRAF, KRAS, PIK3CA, FBXW7, and SMAD4, consistent with known CRC mutation patterns. NGS also identified druggable variants in BRAF, PIK3CA, and KRAS. CK7 + tumors showed intriguingly common (31.6%) BRAF V600E mutations corelating with poor prognosis, compared to the frequency described in the literature and databases. Further research on larger cohorts with a non-colorectal immunophenotype and high MUC4 expression is needed.

• MeSH
• Adult MeSH
• Phenotype MeSH
• Class I Phosphatidylinositol 3-Kinases genetics   metabolism   MeSH
• Immunohistochemistry * MeSH
• Keratin-7 metabolism   genetics   MeSH
• Colorectal Neoplasms * genetics   pathology   metabolism   mortality   MeSH
• Middle Aged MeSH
• Humans MeSH
• Mucin-4 genetics   metabolism   MeSH
• Mucin 5AC genetics   metabolism   MeSH
• Mucin-6 genetics   metabolism   MeSH
• Mutation MeSH
• Biomarkers, Tumor * genetics   metabolism   MeSH
• Prognosis MeSH
• Proto-Oncogene Proteins B-raf genetics   MeSH
• Proto-Oncogene Proteins p21(ras) genetics   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Transcription Factors MeSH
• Matrix Attachment Region Binding Proteins * genetics   metabolism   MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Undifferentiated carcinoma with osteoclast-like giant cells (UCOGC) of the pancreas represents a rare subtype of pancreatic ductal adenocarcinoma (PDAC). Despite a distinct morphology and specific clinical behavior, UCOGCs exhibit unexpected similarities in regard to DNA mutational profiles with conventional PDAC. Treating pancreatic ductal adenocarcinoma is particularly challenging, with limited prospects for cure. As with many other malignant neoplasms, the exploration of microRNAs (miRNAs, miRs) in regulating the biological characteristics of pancreatic cancer is undergoing extensive investigation to enhance tumor diagnostics and unveil the therapeutic possibilities. Herein, we evaluated the expression of miR-21, -96, -148a, -155, -196a, -210, and -217 in UCOGCs and poorly differentiated (grade 3, G3) PDACs. The expression of miR-21, miR-155, and miR-210 in both UCOGCs and G3 PDACs was significantly upregulated compared to the levels in normal tissue, while the levels of miR-148a and miR-217 were downregulated. We did not find any significant differences between cancerous and normal tissues for the expression of miR-96 and miR-196a in G3 PDACs, whereas miR-196a was slightly, but significantly, downregulated in UCOGCs. On the other hand, we have not observed significant differences in the expression of the majority of miRNAs between UCOGC and G3 PDAC, with the exception of miR-155. UCOGC samples demonstrated lower mean levels of miR-155 in comparison with those in G3 PDACs.

• Publication type
• Journal Article MeSH

Oxidative stress has been implied in cellular injury even in the early phases of multiple sclerosis (MS). In this study, we quantified levels of biomarkers of oxidative stress and antioxidant capacity in cerebrospinal fluid (CSF) in newly diagnosed MS patients and their associations with brain atrophy and iron deposits in the brain tissue. Consecutive treatment-naive adult MS patients (n = 103) underwent brain MRI and CSF sampling. Healthy controls (HC, n = 99) had brain MRI. CSF controls (n = 45) consisted of patients with non-neuroinflammatory conditions. 3T MR included isotropic T1 weighted (MPRAGE) and gradient echo (GRE) images that were processed to quantitative susceptibility maps. The volume and magnetic susceptibility of deep gray matter (DGM) structures were calculated. The levels of 8-hydroxy-2'-deoxyguanosine (8-OHdG), 8-iso prostaglandin F2α (8-isoPG), neutrophil gelatinase-associated lipocalin (NGAL), peroxiredoxin-2 (PRDX2), and malondialdehyde and hydroxyalkenals (MDA + HAE) were measured in CSF. Compared to controls, MS patients had lower volumes of thalamus, pulvinar, and putamen, higher susceptibility in caudate nucleus and globus pallidus, and higher levels of 8-OHdG, PRDX2, and MDA + HAE. In MS patients, the level of NGAL correlated negatively with volume and susceptibility in the dentate nucleus. The level of 8-OHdG correlated negatively with susceptibility in the caudate, putamen, and the red nucleus. The level of PRDX2 correlated negatively with the volume of the thalamus and both with volume and susceptibility of the dentate nucleus. From MRI parameters with significant differences between MS and HC groups, only caudate susceptibility and thalamic volume were significantly associated with CSF parameters. Our study shows that increased oxidative stress in CSF detected in newly diagnosed MS patients suggests its role in the pathogenesis of MS.

• Publication type
• Journal Article MeSH