Inferior vena cava (IVC) pathology is often underrecognized on non-dedicated imaging examinations, yet it carries significant diagnostic and clinical implications, particularly in acute emergency settings. This review highlights the complementary roles of ultrasound (US) and computed tomography (CT) in the assessment of IVC abnormalities. The US provides real-time, bedside evaluation of IVC patency, caliber, and hemodynamics, whereas CT offers detailed anatomic and structural characterization critical for diagnosis and management. The review aims to systematically discuss congenital variants, thrombotic, traumatic, systemic conditions, and neoplastic involvement of the IVC, emphasizing their imaging features and clinical relevance.

Amnesia is a well-documented complication following surgical repair of anterior communicating artery (ACoA) aneurysms. 3D MRI has clarified that it is primarily caused by infarction of the subcallosal artery, the largest unpaired perforating branch of the ACoA. Bilateral infarction of the columns of the fornix, a core component of the Papez circuit, has been identified as the anatomical basis of such amnesia. Another perforating artery prone to surgical injury is the recurrent artery of Heubner (RAH), which arises from the A1 to A2 junction of the anterior cerebral artery and is usually present bilaterally. When RAH infarction co-occurs with subcallosal artery infarction during ACoA aneurysm surgery, memory impairment may be accompanied by reduced processing speed and a worse long-term outcome. We report a 63-year-old man who underwent surgical clipping for a ruptured ACoA aneurysm. 3D-MR images obtained 10 months postoperatively revealed bilateral infarctions in the subcallosal artery territory, including the columns of the fornix, as well as a right-sided infarction in the RAH territory. Clinical correlation showed that these findings matched the patient’s paradoxical cognitive profile, confirmed by formal neuropsychological testing 5 years after clipping. He demonstrated a dissociation between exceptionally gifted-level intellectual ability and comparatively lower scores in memory and processing speed. His full-scale intelligence quotient (IQ) was 144, with a verbal IQ of 156 and working memory of 150, while his general memory score was 115 and processing speed was 110. Although these latter scores fell within the high-average range, they represented a meaningful decline relative to his potential. This profile supports a dual circuit model: Subcallosal artery infarction disrupts the Papez circuit, impairing memory, while RAH infarction contributes to inefficiency through frontostriatal disconnection. This case of paradoxical giftedness with memory decline underscores the value of 3D MR imaging in revealing memory decline masked by cognitive reserve.

Objectives: This study presents a comprehensive bibliometric analysis of Indian research on the application of generative artificial intelligence (GAI) in healthcare imaging from 2017 to 2025. It aims to evaluate the research output, citation impact, collaborative patterns, and key thematic areas to understand India’s position in this rapidly evolving global landscape. Material and Methods: We used a comprehensive search strategy on the Scopus database, limited to publications with an Indian affiliation from 2017 to 2025. Data on author names, affiliations, publication years, keywords, and citations were extracted from 383 records. The analysis employed citation analysis, co-authorship networks, and keyword co-occurrence analysis, with VOSviewer software used for data visualization. Results: Globally, 2,761 papers were published in this field, with an average growth rate of 133.2%. India ranked third globally in publication volume with 383 papers, but its average citations per paper (CPP) were 6.55, much below the global average of 21.71. Conference papers dominated India’s output (58.49%) but had a low CPP of 2.92, in contrast to higher-impact journal articles (11.29 CPP). Key institutions such as SRM Institute of Science and Technology were highly productive, while others, such as the GLA University, demonstrated high citation impact. The most prevalent keywords were “generative adversarial networks” and “medical imaging,” highlighting a strong focus on technical applications. Conclusion: Indian research in GAI in healthcare imaging is marked by a significant increase in output, establishing the country as a major contributor. Although India ranks third globally in research output, its citation impact remains below the global average, reflecting the need to improve research quality, visibility, and international collaboration.

Adamantinoma-like Ewing sarcoma (ALES) of the parotid gland is an exceptionally rare neoplasm. We report the case of a 57-year-old male with a history of p16-positive tonsillar squamous cell carcinoma who presented 2 years after remission with excessive mucus production and neck stiffness. Imaging identified a left parotid mass, and diagnosis was confirmed through surgical pathology, with molecular testing revealing a Fused in Sarcoma-Fifth Ewing Variant ( FUS-FEV) fusion gene. Treatment included radical parotidectomy, adjuvant external beam radiation, and systemic chemotherapy following the Ewing sarcoma paradigm. Despite initial response, the patient experienced significant toxicities and eventually succumbed to disease-related complications. This case illustrates the challenges in diagnosing and managing rare parotid malignancies and highlights the importance of multidisciplinary care.

Inflammatory myofibroblastic tumor (IMT) is a rare mesenchymal-derived neoplasm that most commonly arises in the lung. It can also occur in other parts of the body. Primary IMT of the gallbladder is exceptionally uncommon. Due to the absence of large-sample studies, the current understanding of gallbladder IMT remains largely limited to case reports. This article reports the diagnosis and treatment course of a 13-year-old male with inflammatory myofibroblastoma of the gallbladder. It specifically focuses on delineating its distinct imaging characteristics across ultrasonography, computed tomography, and magnetic resonance imaging, aiming to enhance the accuracy of pre-operative diagnosis and provide valuable insights into the literature for this rare condition.

Transcription Factor E3 (TFE3)-rearranged renal cell carcinoma (RCC) is rare. Radiologically, TFE3-rearranged RCC typically appears as a hyperattenuating mass with calcifications. Calcifications typically appear as small punctate or irregular coarse deposits, which are pathologically associated with granular and collagenous stromal degeneration. Here, we report a case of TFE3-rearranged RCC with extensive calcification in a young female, emphasizing imaging-pathologic correlation to enhance diagnostic accuracy. This case underscores the importance of recognizing atypical radiological features in rare RCC subtypes.

We report a rare case of a 28-year-old African–American woman with chronic hidradenitis suppurativa (HS), in whom breast masses were initially misattributed to HS-related inflammation, delaying diagnosis of breast cancer. She presented with back pain and diagnostic work-up revealed thoracic vertebral metastasis. Dedicated breast imaging showed suspicious breast masses and biopsy confirmed invasive ductal carcinoma. This case highlights the importance of breast imaging when inflammatory skin conditions of the breast fail to respond to standard treatment.

Objectives:The objectives of the study are to compare the effect on image quality of a motion artifact correction algorithm (CAVAREC) alone versus in combination with an automated bone removal algorithm (ZIBOS) for motion-degraded intraprocedural liver cone-beam computed tomography (CBCT) images.Material and Methods:In this retrospective, two-center, Institutional Review Board (IRB)-approved study, 48 CBCTs from 41 patients were included. Inclusion criteria were (a) age ≥18; (b) liver CBCT with contrast injected at the main, right, or left hepatic artery; and (c) CBCT motion-degraded. Exclusion criteria were (a) no visible tumor and (b) CBCT not capturing the entire liver. The mean (standard deviation [SD]) age was 64 (7) years, 81% male. 65% had hepatocellular carcinoma and 35% metastatic cancer. 69% CBCTs were from transarterial radioembolization (TARE) mapping, 25% transarterial chemoembolization, and 6% TARE treatment. Mean (SD) maximum tumor diameter was 4.6 (2.7) cm. CBCT images were processed with CAVAREC (prototype, Siemens Healthineers AG, Forchheim, Germany) and CAVAREC + ZIBOS (work in progress, Comprehenso, Hannover, Germany). Using CoroEval, sharpness for two segmental arteries per case was obtained quantitatively. Three blinded interventional radiologists independently evaluated overall image quality on a 0–100 scale and large vessels, small vessels, vessel sharpness, tumor feeders, tumor blush, and streak artifacts on a −50 to +50 scale relative to uncorrected images. Results were analyzed with paired t-tests and Wilcoxon signed-rank tests, adjusting P-values with the Benjamini–Hochberg procedure.Results:On quantitative assessment, mean (SD) sharpness for uncorrected, CAVAREC, and CAVAREC + ZIBOS (C+Z) images was 0.281 (0.04), 0.287 (0.04), and 0.284 (0.04), respectively, P = 0.02 for uncorrected versus CAVAREC and P > 0.05 for other comparisons. On qualitative assessment, mean (SD) overall quality for uncorrected, CAVAREC, and C+Z images was 45 (14), 53 (16), and 53 (17), respectively, P < 0.001 for both uncorrected versus CAVAREC and uncorrected versus C+Z and P = 0.06 for CAVAREC versus C+Z. The mean preference for both CAVAREC and C+Z compared to uncorrected images for all parameters ranged from +4.3 to +9.5, P < 0.001, except tumor blush which was +1.6 for CAVAREC and +0.9 for C+Z, P > 0.05. CAVAREC versus C+Z was not significant for any parameter.Conclusion:Motion artifact correction of liver CBCT images using CAVAREC improves image quality significantly. According to observer studies, integrating the automated bone segmentation algorithm ZIBOS with CAVAREC does not degrade image quality.

Objectives:This study aims to evaluate the image quality of 55 keV virtual monoenergetic imaging (VMI) in carotid dual-energy computed tomography (CT) angiography (DE-CTA) reconstructed using deep learning image reconstruction (DLIR) algorithms and traditional iterative reconstruction algorithms.Material and Methods:This prospective study included 48 patients who underwent DE-CTA examinations at our institution between December 2024 and January 2025. Image reconstructions were performed using 50% strength adaptive statistical iterative reconstruction-Veo (ASIR-V 50%), low and high strengths DLIR (DLIR-L and DLIR-H) algorithms. Objective image quality was evaluated by measuring background noise (standard deviation), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) at key anatomical locations, including the aortic arch, common carotid artery, carotid bifurcation, and internal carotid artery. Two senior radiologists conducted subjective assessments of image quality, focusing on image noise, artifacts, and vessel continuity, and the clarity of vascular wall margin.Results:Compared with ASIR-V 50% and DLIR-L, DLIR-H significantly improved image quality by reducing background noise and increasing SNR and CNR (P < 0.05). Subjectively, DLIR-H images demonstrated better suppression of noise and clearer vascular wall margin (P < 0.05). Subgroup analysis revealed that these improvements were more pronounced in patients with a body mass index (BMI) ≥24 kg/m2. No significant differences were observed in CT attenuations among the three reconstruction methods (P > 0.05).Conclusion:At 55 keV VMI in carotid DE-CTA, DLIR-H significantly enhanced image quality, particularly by reducing noise and preserving fine anatomical structures. Its efficacy was especially notable in patients with BMI ≥24 kg/m2.

Neuronal migrational anomalies, cortical dysplasias, hemimegalencephaly, and microcephalies are collectively termed malformations of cortical development (MCD). MCDs have multifactorial etiologies including genetic, environmental, vascular, and infectious insults between the late 1st trimester and late 2nd trimester. Neonatal correlates of various neuronal migration anomalies detected on fetal magnetic resonance imaging are illustrated. Physiologic immaturity of sulci and certain mimics of migration anomalies can pose a challenge, and these are also outlined.