Hiroyuki Uetani

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. Methods We retrospectively analyzed magnetic resonance imaging (MRI) data from 32 patients with sellar cystic lesions, including 5 with pathologically confirmed pituitary abscesses and 27 with OSCLs. Conventional MRI sequences and SPLICE-DWI were performed, and apparent diffusion coefficient (ADC) values were calculated. Qualitative assessments of signal intensity on SPLICE-DWI and conventional MRI were conducted by two neuroradiologists. The diagnostic performance of these imaging parameters was evaluated using receiver operating characteristic (ROC) analysis. Results SPLICE-DWI successfully differentiated pituitary abscesses from OSCLs, showing significantly lower ADC values in the abscess group compared to OSCLs (0.62 ± 0.07 × 10^− 3 mm²/s vs. 1.83 ± 0.70 × 10^− 3 mm²/s, P = 0.002). ROC analysis revealed high diagnostic accuracy for DWI signal intensity (AUC = 0.89) and ADC values (AUC = 0.95). No significant differences were found in contrast-enhanced T1-weighted imaging (T1WI) features such as ring enhancement, pituitary stalk enlargement, or sphenoid sinus mucosal thickening between the two groups. Conclusion SPLICE-DWI is a valuable tool for the differentiation of pituitary abscesses from OSCLs, offering high diagnostic accuracy.

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. Methods This study included 36 immunocompetent patients with PCNSL, including 16 with double expressor and 20 without double expressor. The enhancement pattern and the values of apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV), leakage-corrected rCBV, and K2 at enhancing lesions were compared between the DE-PCNSL and non-DE-PCNSL groups. The mean and minimum values from the ROI on ADC maps were designated as ADC_mean and ADC_min, respectively. The data of rCBV, leakage-corrected rCBV and K2 were obtained from dynamic susceptibility contrast (DSC) perfusion MRI. The Kaplan-Meier method was used to estimate progression-free survival (PFS) differences. Results DE-PCNSL was significantly more common in women (12 of 16 patients, 75%) compared to non-DE-PCNSL (7 of 20 patients, 35%; P =.02). The rCBV ratio and leakage-corrected rCBV ratio were significantly lower in DE-PCNSL compared to non-DE-PCNSL (P =.02 and P =.03, respectively). There was no significant difference in the enhancement pattern and ADC_mean, ADC_min and K2 values between the two groups. DE-PCNSL tended to have a shorter PFS than non-DE-PCNSL, although the difference was not significant. Conclusion rCBV and leakage-corrected rCBV may help differentiate double-expressor from non-double-expressor subtypes in PCNSL.

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 0.23 × 0.23 × 0.5 mm. The contrast-to-noise ratios (CNRs) of the structures were compared between HR-3D T2-FASE images with and without DLR. The observers’ preferences based on four categories on the tumor side on HR-3D T2-FASE images were evaluated. The facial nerve in relation to the tumor on HR-3D T2-FASE images was assessed with reference to intraoperative findings. Results The mean CNR between the tumor and trigeminal nerve and between the cerebrospinal fluid and trigeminal nerve was significantly higher for DLR images than non-DLR-based images (14.3 ± 8.9 vs. 12.0 ± 7.6, and 66.4 ± 12.0 vs. 53.9 ± 8.5, P < 0.001, respectively). The observer’s preference for the depiction and delineation of the tumor, cranial nerves, vessels, and location relation on DLR HR-3D T2FASE images was superior to that on non-DLR HR-3D T2FASE images in 7 (54%), 6 (46%), 6 (46%), and 6 (46%) of 13 cases, respectively. The facial nerves around the tumor on HR-3D T2-FASE images were visualized accurately in five (38%) cases with DLR and in four (31%) without DLR. Conclusion DLR HR-3D T2-FASE imaging is useful for the preoperative assessment of CPA tumors.

Purpose The aim of this study is to assess the effect of super-resolution deep learning-based reconstruction (SR-DLR), which uses k-space properties, on image quality of intracranial time-of-flight (TOF) magnetic resonance angiography (MRA) at 3 T. Methods This retrospective study involved 35 patients who underwent intracranial TOF-MRA using a 3-T MRI system with SR-DLR based on k-space properties in October and November 2022. We reconstructed MRA with SR-DLR (matrix = 1008 × 1008) and MRA without SR-DLR (matrix = 336 × 336). We measured the signal-to-noise ratio (SNR), contrast, and contrast-to-noise ratio (CNR) in the basilar artery (BA) and the anterior cerebral artery (ACA) and the sharpness of the posterior cerebral artery (PCA) using the slope of the signal intensity profile curve at the half-peak points. Two radiologists evaluated image noise, artifacts, contrast, sharpness, and overall image quality of the two image types using a 4-point scale. We compared quantitative and qualitative scores between images with and without SR-DLR using the Wilcoxon signed-rank test. Results The SNRs, contrasts, and CNRs were all significantly higher in images with SR-DLR than those without SR-DLR (p < 0.001). The slope was significantly greater in images with SR-DLR than those without SR-DLR (p < 0.001). The qualitative scores in MRAs with SR-DLR were all significantly higher than MRAs without SR-DLR (p < 0.001). Conclusion SR-DLR with k-space properties can offer the benefits of increased spatial resolution without the associated drawbacks of longer scan times and reduced SNR and CNR in intracranial MRA.

Purpose: In this preliminary study, we aimed to evaluate the potential of the generative pre-trained transformer (GPT) series for generating radiology reports from concise imaging findings and compare its performance with radiologist-generated reports. Methods: This retrospective study involved 28 patients who underwent computed tomography (CT) scans and had a diagnosed disease with typical imaging findings. Radiology reports were generated using GPT-2, GPT-3.5, and GPT-4 based on the patient’s age, gender, disease site, and imaging findings. We calculated the top-1, top-5 accuracy, and mean average precision (MAP) of differential diagnoses for GPT-2, GPT-3.5, GPT-4, and radiologists. Two board-certified radiologists evaluated the grammar and readability, image findings, impression, differential diagnosis, and overall quality of all reports using a 4-point scale. Results: Top-1 and Top-5 accuracies for the different diagnoses were highest for radiologists, followed by GPT-4, GPT-3.5, and GPT-2, in that order (Top-1: 1.00, 0.54, 0.54, and 0.21, respectively; Top-5: 1.00, 0.96, 0.89, and 0.54, respectively). There were no significant differences in qualitative scores about grammar and readability, image findings, and overall quality between radiologists and GPT-3.5 or GPT-4 (p > 0.05). However, qualitative scores of the GPT series in impression and differential diagnosis scores were significantly lower than those of radiologists (p < 0.05). Conclusions: Our preliminary study suggests that GPT-3.5 and GPT-4 have the possibility to generate radiology reports with high readability and reasonable image findings from very short keywords; however, concerns persist regarding the accuracy of impressions and differential diagnoses, thereby requiring verification by radiologists.

Purpose The purpose of this study is to evaluate the influence of super-resolution deep learning-based reconstruction (SR-DLR), which utilizes k-space data, on the quality of images and the quantitation of the apparent diffusion coefficient (ADC) for diffusion-weighted images (DWI) in brain magnetic resonance imaging (MRI). Methods A retrospective analysis was performed on 34 patients who had undergone DWI using a 3 T MRI system with SR-DLR reconstruction based on k-space data in August 2022. DWI was reconstructed with SR-DLR (Matrix = 684 × 684) and without SR-DLR (Matrix = 228 × 228). Measurements were made of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) in white matter (WM) and grey matter (GM), and the full width at half maximum (FWHM) of the septum pellucidum. Two radiologists assessed image noise, contrast, artifacts, blur, and the overall quality of three image types using a four-point scale. Quantitative and qualitative scores between images with and without SR-DLR were compared using the Wilcoxon signed-rank test. Results Images with SR-DLR showed significantly higher SNRs and CNRs than those without SR-DLR (p < 0.001). No statistically significant variances were found in the apparent diffusion coefficients (ADCs) in WM and GM between images with and without SR-DLR (ADC in WM, p = 0.945; ADC in GM, p = 0.235). Moreover, the FWHM without SR-DLR was notably lower compared to that with SR-DLR (p < 0.001). Conclusion SR-DLR has the potential to augment the quality of DWI in DL MRI scans without significantly impacting ADC quantitation.

Objectives As a novel follow-up method for intracranial aneurysms treated with stent-assisted coil embolization (SACE), we developed four-dimensional magnetic resonance angiography (MRA) with minimized acoustic noise utilizing ultrashort-echo time (4D mUTE-MRA). We aimed to assess whether 4D mUTE-MRA is useful for the evaluation of intracranial aneurysms treated with SACE. Methods This study included 31 consecutive patients with intracranial aneurysm treated with SACE who underwent 4D mUTE-MRA at 3 T and digital subtraction angiography (DSA). For 4D mUTE-MRA, five dynamic MRA images with a spatial resolution of 0.5 × 0.5 × 0.5 mm³ were obtained every 200 ms. Two readers independently reviewed the 4D mUTE-MRA images to evaluate the aneurysm occlusion status (total occlusion, residual neck, and residual aneurysm) and the flow in the stent using a 4-point scale (from 1 [not visible] to 4 [excellent]). The interobserver and intermodality agreement was assessed using κ statistics. Results On DSA images, 10 aneurysms were classified as total occlusion, 14 as residual neck, and 7 as residual aneurysm. In terms of aneurysm occlusion status, the intermodality and interobserver agreement was excellent (κ = 0.92 and κ = 0.96, respectively). For the flow in the stents on 4D mUTE-MRA, the mean score was significantly higher for single stents than multiple stents (p < .001) and for open-cell type stents than closed-cell type (p < .01). Conclusions 4D mUTE-MRA is a useful tool with a high spatial and temporal resolution for the evaluation of intracranial aneurysms treated with SACE. Key Points • In the evaluation of intracranial aneurysms treated with SACE on 4D mUTE-MRA and DSA, the intermodality and interobserver agreement in aneurysm occlusion status was excellent. • 4D mUTE-MRA shows good to excellent visualization of flow in the stents, especially for cases treated with a single or open-cell stent. • 4D mUTE-MRA can provide hemodynamic information related to embolized aneurysms and the distal arteries to stented parent arteries.