A Rare Case of Bilateral Lateral Ventricular Subependymomas With Complete Resection of the Residual Tumor via Flexible Neuroendoscopy 20 Years After Initial Surgery.

Subependymoma is a benign, slow-growing tumor that arises from the ventricular wall. Although often asymptomatic, it can obstruct cerebrospinal fluid flow, leading to hydrocephalus. Most subependymomas are unilateral, typically located in the fourth ventricle, followed by the lateral ventricles.

Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on images.

Objective: Aimed to evaluate the potential of large language models (LLMs) in differentiating intra-axial primary brain tumors using structured magnetic resonance imaging (MRI) reports and compare their performance with radiologists.

Materials And Methods: Structured reports of preoperative MRI findings from 137 surgically confirmed intra-axial primary brain tumors, including Glioblastoma (n = 77), Central Nervous System (CNS) Lymphoma (n = 22), Astrocytoma (n = 9), Oligodendroglioma (n = 9), and others (n = 20), were analyzed by multiple LLMs, including GPT-4, Claude-3-Opus, Claude-3-Sonnet, GPT-3.5, Llama-2-70B, Qwen1.

Impact of super-resolution deep learning-based reconstruction for hippocampal MRI: A volunteer and phantom study.

Background And Purpose: To evaluate the effects of super-resolution deep learning-based reconstruction (SR-DLR) on thin-slice T2-weighted hippocampal MR image quality using 3 T MRI, in both human volunteers and phantoms.

Materials And Methods: Thirteen healthy volunteers underwent hippocampal MRI at standard and high resolutions. Original (standard-resolution; StR) images were reconstructed with and without deep learning-based reconstruction (DLR) (Matrix = 320 × 320), and with SR-DLR (Matrix = 960 × 960).

A Rare Case of Brain Metastasis of Gastric Neuroendocrine Carcinoma.

Gastric neuroendocrine carcinoma (small cell neuroendocrine carcinoma [small cell NEC]) is a rare type of gastric cancer that is rarely encountered in clinical practice. Although solitary brain metastasis from gastric cancer is exceptionally rare, we present a case of solitary brain metastasis of gastric NEC. The patient was a 71-year-old man who had undergone surgery and chemotherapy for gastric NEC two years prior.

Evaluating the Performance of Reasoning Large Language Models on Japanese Radiology Board Examination Questions.

Rationale And Objectives: This study evaluates the performance, cost, and processing time of OpenAI's reasoning large language models (LLMs) (o1-preview, o1-mini) and their base models (GPT-4o, GPT-4o-mini) on Japanese radiology board examination questions.

Materials And Methods: A total of 210 questions from the 2022-2023 official board examinations of the Japan Radiological Society were presented to each of the four LLMs. Performance was evaluated by calculating the percentage of correctly answered questions within six predefined radiology subspecialties.

Use of Electron Density Maps and Fused Images in Dual-Energy Cardiac Computed Tomography to Facilitate Detection of Late Iodine Enhancement.

Background: This study aimed to optimize the fusion of quantitative maps and morphological images to improve late iodine enhancement (LIE) imaging using cardiac dual-energy computed tomography (DECT).

Methods And Results: We retrospectively analyzed 15 patients with suspected old myocardial infarction who underwent cardiac DECT. Virtual monochromatic images (VMI) ranging from 40 to 200 keV and quantitative maps (e.

Usefulness of 3T split acquisition fast spin-echo diffusion-weighted imaging for differentiating pituitary abscess from other sellar cystic lesions: a preliminary study.

Purpose: Pituitary abscess is a rare condition that can be challenging to distinguish from other sellar cystic lesions (OSCLs) due to no specific symptoms and overlapping imaging features. Accurate differentiation is crucial for appropriate treatment planning. This study aimed to evaluate the usefulness of 3T split acquisition fast spin-echo diffusion-weighted imaging (SPLICE-DWI) in differentiating pituitary abscesses from OSCLs.

Duplicated Cervical Internal Carotid Artery with Ipsilateral Persistent Stapedial Artery and Contralateral Aberrant Internal Carotid Artery: A Case Report.

Objective: Duplication of extracranial cerebral arteries is a rare anatomical variant, most commonly observed in the vertebral artery. However, duplication of the cervical internal carotid artery (ICA) is extremely rare. We present a unique case of a patient diagnosed with a right facial artery aneurysm, in whom a right duplicated ICA, ipsilateral persistent stapedial artery (PSA), and contralateral aberrant ICA were incidentally identified.

Utilization of Heavily T2-Weighted Imaging and Dynamic Contrast-Enhanced 3T Magnetic Resonance Angiography for Diagnosing Spinal Extradural Arteriovenous Fistula: A Case Report.

Spinal arteriovenous fistula (SAVF), including spinal dural arteriovenous fistula and spinal extradural arteriovenous fistula (SEAVF), is a rare spinal vascular disorder characterized by abnormal intradural and extradural arteriovenous shunting, often resulting in progressive motor, sensory, and autonomic dysfunction. Due to its nonspecific presentation and overlapping imaging findings with other spinal diseases, SAVF is frequently misdiagnosed, delaying appropriate treatment and increasing the risk of neurological deterioration. Here, we present a case in which heavily T2-weighted imaging and dynamic contrast-enhanced magnetic resonance angiography at 3T were valuable for the diagnosis of SEAVF.

Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study.

Objective: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.

Methods: Our retrospective study incorporated 34 patients diagnosed with biliary and pancreatic disorders. We obtained MRCP images using a single breath-hold MRCP on a 3T MRI system.

Usefulness of Dual-Energy CT for Differentiating Hemorrhage From Iodine Extravasation in Meningiomas After Preoperative Embolization.

Objective: Discriminating between hemorrhage and iodine extravasation can pose challenges in conventional computed tomography (CCT) images following preoperative embolization for meningioma. This study aimed to assess the efficacy of dual-energy computed tomography (DECT) in differentiating hemorrhage from iodine extravasation after preoperative embolization for meningioma.

Methods: Twenty-one consecutive meningioma patients who underwent CCT before and DECT immediately after preoperative embolization were included in this study.

Dynamic susceptibility contrast perfusion MRI helps in differentiating double-expressor from non-double-expressor subtypes in primary central nervous system lymphoma.

Purpose: In the 2016 WHO Classification of Lymphoid Tissue Neoplasms, co-expression of MYC and BCL2 is newly designated as double expressor lymphoma. Patients with primary central nervous system lymphoma with double expressor (DE-PCNSL) have been reported to have a higher risk of recurrence and a worse prognosis than those with PCNSL without double expressor (non-DE-PCNSL). The aim of this study was to determine whether DE-PCNSL has characteristic clinical and MR imaging features compared to non-DE-PCNSL.

Enhancing thin slice 3D T2-weighted prostate MRI with super-resolution deep learning reconstruction: Impact on image quality and PI-RADS assessment.

Purposes: This study aimed to assess the effectiveness of Super-Resolution Deep Learning Reconstruction (SR-DLR) -a deep learning-based technique that enhances image resolution and quality during MRI reconstruction- in improving the image quality of thin-slice 3D T2-weighted imaging (T2WI) and Prostate Imaging-Reporting and Data System (PI-RADS) assessment in prostate Magnetic Resonance Imaging (MRI).

Methods: This retrospective study included 33 patients who underwent prostate MRI with SR-DLR between November 2022 and April 2023. Thin-slice 3D-T2WI of the prostate was obtained and reconstructed with and without SR-DLR (matrix: 720 × 720 and 240 × 240, respectively).

Machine Learning for Evaluating Vulnerable Plaque on Coronary Computed Tomography Using Spectral Imaging.

Background: This study aimed to determine whether spectral imaging with dual-energy computed tomography (CT) can improve diagnostic performance for coronary plaque characterization.

Methods And Results: We conducted a retrospective analysis of 30 patients with coronary plaques, using coronary CT angiography (dual-layer CT) and intravascular ultrasound (IVUS) studies. Based on IVUS findings, patients were diagnosed with either vulnerable or stable plaques.

Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.

Purpose: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.

Methods: We retrospectively analyzed scan data of adult patients who underwent body CT during two periods relative to DLR implementation at our facility: a 12-month pre-DLR phase (n = 5553) using hybrid iterative reconstruction and a 12-month post-DLR phase (n = 5494) with routine CT reconstruction transitioning to DLR. To ensure comparability between two groups, we employed propensity score matching 1:1 based on age, sex, and body mass index.

Performance of Multimodal Large Language Models in Japanese Diagnostic Radiology Board Examinations (2021-2023).

Rationale And Objectives: To evaluate the performance of various multimodal large language models (LLMs) in the Japanese Diagnostic Radiology Board Examinations (JDRBE) both with and without images.

Materials And Methods: Five multimodal LLMs-GPT-4o, Claude 3 Opus, GPT-4 Vision, Gemini Flash 1.5, and Gemini Pro 1.

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.

Objectives: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-phase sequence.

Materials And Methods: In this retrospective study, 29 patients who underwent lumbar spine MRI, including an MR bone imaging sequence between January and April 2023, were analyzed. Images were reconstructed with and without SR-DLR (Matrix sizes: 960 × 960 and 320 × 320, respectively).

A Novel Approach to Detecting Contrast Extravasation in Computed Tomography: Evaluating the Injection Pressure-to-Injection Rate Ratio.

Objective: The purpose of this study was to evaluate the usefulness of the injection pressure-to-injection rate (IPIR) ratio for the early detection of contrast extravasation at the venipuncture site during contrast-enhanced computed tomography.

Methods: We retrospectively enrolled 57,528 patients who underwent contrast-enhanced computed tomography examinations in a single hospital. The power injector recorded the contrast injection pressure at 0.

Effect of deep learning-based reconstruction on high-resolution three-dimensional T2-weighted fast asymmetric spin-echo imaging in the preoperative evaluation of cerebellopontine angle tumors.

Purpose: We aimed to evaluate the effect of deep learning-based reconstruction (DLR) on high-spatial-resolution three-dimensional T2-weighted fast asymmetric spin-echo (HR-3D T2-FASE) imaging in the preoperative evaluation of cerebellopontine angle (CPA) tumors.

Methods: This study included 13 consecutive patients who underwent preoperative HR-3D T2-FASE imaging using a 3 T MRI scanner. The reconstruction voxel size of HR-3D T2-FASE imaging was 0.

Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.

Objective: The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance angiography (MRA) at 3 T.

Methods: This prospective study enrolled 20 patients who underwent head MRI at 3 T, including TOF-MRA. We used 3D wheel sampling called "fast 3D" and DLR for HR-TOF-MRA (spatial resolution, 0.

A Rare Case of Adult Poorly Differentiated Chordoma of the Skull Base With Rapid Progression and Systemic Metastasis: A Review of the Literature.

Chordoma is a rare tumor that arises from chordal tissue during fetal life. Recently, the concept of poorly differentiated chordoma, a subtype of chordoma characterized by loss of / with a poorer prognosis than conventional chordomas, was established. It predominantly occurs in children and is rare in adults.