Purpose: As diagnostic X-ray imaging remains a fundamental pillar of modern medicine, the imperative to manage ionizing radiation doses—particularly for vulnerable populations—has never been greater. This study explores the role of VirtualDoseDX, an advanced software-based estimation tool, in overcoming the limitations of traditional dose metrics and fulfilling global radiation protection mandates. Methods and Materials: The limitations of conventional indices, such as Dose Area Product (DAP) and Entrance Skin Dose (ESD), are analyzed in the context of their inability to reflect organ-specific absorbed doses and patient-specific anatomical variations. The study evaluates the VirtualDoseDX ecosystem, which utilizes high-fidelity computational phantoms and Monte Carlo simulations to provide precise, personalized dosimetry across multiple modalities including CT and Interventional Radiology (IR). Results: The integration of VirtualDoseDX facilitates a comprehensive dose management strategy that aligns with the ICRP’s pillars of Justification, Optimization (ALARA), and Dose Management. By providing granular data on internal energy deposition, the software enables standardized reporting and inter-institutional comparability. Furthermore, its application extends to large-scale epidemiological research and the establishment of evidence-based Diagnostic Reference Levels (DRLs), supporting a data-driven approach to patient safety. Conclusion: VirtualDoseDX transcends simple technical utility to serve as an essential framework for standardized medical radiation management. As healthcare shifts toward personalized care and quantitative safety assessments, such integrated multi-modal solutions are becoming indispensable cornerstones of radiological practice. This technology ensures that diagnostic efficacy is maintained while maximizing patient safety through rigorous, high-fidelity radiation monitoring.

Background: Reducing radiation dose in Computed Tomography (CT) is a clinical imperative, yet current low-dose CT (LDCT) protocols are inherently limited by noise and artifacts that obscure critical diagnostic details. While traditional iterative reconstruction and standard deep learning models have been proposed, they often introduce undesirable "waxy" textures and loss of fine structural edges. Methods: This study presents a high-fidelity image enhancement framework based on Generative Adversarial Networks (GANs) specifically optimized for LDCT denoising. Our approach integrates a multi-scale U-Net generator with a discriminator that evaluates both global structure and local texture. To ensure clinical reliability, we utilize a composite loss function comprising pixel-wise MSE, adversarial loss, and VGG-based perceptual loss, which encourages the model to preserve biologically relevant high-frequency details. Results: Experimental evaluation on the AAPM-Mayo Clinic dataset demonstrates that our proposed model significantly outperforms state-of-the-art methods, achieving a Peak Signal-to-Noise Ratio (PSNR) of 32.56 dB and a Structural Similarity Index (SSIM) of 0.912. Qualitative assessments confirm that our framework effectively suppresses quantum noise while maintaining the natural stochastic texture of CT images, facilitating better visualization of subtle lesions compared to standard CNN-based denoising. Conclusion: The proposed GAN-based framework bridges the gap between dose reduction and image quality, providing a viable pathway for high-quality diagnostic imaging at a fraction of the standard radiation exposure. This method holds significant potential for routine clinical use, particularly in screening scenarios where repeated exposure is a concern.

Classical Hodgkin Lymphoma (cHL) often presents in young adults with mediastinal involvement and characteristic systemic symptoms. We report a case of a 23-year-old male presenting with fever, cough, and significant weight loss. Initial imaging revealed a large anterior mediastinal mass. Diagnostic confirmation was achieved via core biopsy showing CD30 and CD15 positivity. Positron emission tomography/computed tomography (PET/CT) played a crucial role in staging and assessing treatment response, showing significant metabolic improvement after chemotherapy. This case highlights the importance of multimodality imaging in the diagnosis and management of cHL.

Background: Perforated duodenal ulcer is a potentially life-threatening gastrointestinal emergency. While free intraperitoneal perforation typically presents with overt peritonitis, contained or retroperitoneal perforation may show subtle and atypical clinical and radiologic features, posing a diagnostic challenge. Case Presentation: We report the case of a 64-year-old man presenting with progressively worsening abdominal pain. Contrast-enhanced computed tomography (CT) and upper gastrointestinal (GI) series demonstrated retroperitoneal air and focal contrast leakage from the third portion of the duodenum, consistent with a contained duodenal perforation. Prompt diagnosis based on imaging findings enabled successful conservative management. Conclusion: This case highlights the critical role of multimodality imaging in the early diagnosis of contained duodenal perforation. Recognition of characteristic CT and fluoroscopic findings is essential for timely clinical decision-making and favorable patient outcomes.

Medical imaging has rapidly evolved from a purely diagnostic discipline into a central pillar of predictive, preventive, and precision medicine. Recent advances in artificial intelligence (AI), molecular imaging, quantitative biomarkers, and radiation dose optimization have reshaped the clinical role of imaging across neurology, oncology, and population health. This review synthesizes high-impact evidence from international SCI-indexed journals published over the past decade, with particular emphasis on studies reported in 2024–2025. We examine how contemporary imaging enables early disease prediction, personalized therapeutic stratification, and outcome-driven clinical decision-making, while also addressing ethical and legal challenges associated with AI-assisted diagnostics. These developments collectively mark a strategic shift in modern radiology—from image interpretation to precision-guided clinical intelligence.

Purpose: To describe the imaging features, clinical course, and management of gallbladder perforation presenting with septic shock, and to emphasize the diagnostic value of computed tomography (CT). Materials and Methods: We retrospectively reviewed the clinical and radiologic findings of a 68-year-old woman who presented with acute abdominal pain and septic shock. Contrast-enhanced abdominal CT was performed and correlated with clinical progression. Results: CT demonstrated focal discontinuity of the gallbladder wall, pericholecystic fluid collection, extraluminal gallstones, and diffuse inflammatory fat stranding—findings diagnostic of gallbladder perforation. Despite aggressive supportive care and percutaneous drainage, the patient succumbed to septic shock. Conclusion: Gallbladder perforation is a life-threatening complication of acute cholecystitis. Early CT diagnosis is critical for guiding prompt surgical or interventional management and improving survival outcomes.

Background: Corrosive esophagitis is a potentially life-threatening condition resulting from the ingestion of caustic substances. Prompt radiologic assessment is critical for evaluating disease severity, guiding management, and predicting long-term complications. Case Presentation: We report a case of a 27-year-old male who presented with acute respiratory distress following accidental ingestion of an alkaline cleaning agent. Initial chest radiography and computed tomography (CT) demonstrated characteristic imaging features of corrosive esophagitis, including circumferential esophageal wall thickening and aspiration-related pulmonary changes. Subsequent fluoroscopic evaluation revealed progressive esophageal stricture formation during the chronic phase. Conclusion: This case highlights the dynamic radiologic manifestations of corrosive esophageal injury across acute and chronic phases and underscores the essential role of multimodal imaging in diagnosis, staging, and long-term management.