Kazuhiro Saito

Background: Seromucinous borderline tumor (SMBT) and endometriosis-associated ovarian cancer (EAOC) may show overlapping magnetic resonance imaging (MRI) features. Quantitative diffusion-weighted imaging may improve their preoperative differentiation. Purpose: To evaluate the diagnostic performance of the cystic–solid apparent diffusion coefficient difference (ΔADC) for differentiating SMBT from EAOC. Material and Methods: This retrospective single-center study included 49 patients with pathologically confirmed SMBT (n = 14) or EAOC (n = 35) who underwent preoperative pelvic MRI. Apparent diffusion coefficient (ADC) values were measured in the cystic and solid components, and ΔADC was calculated as cystic ADC minus solid ADC. Receiver operating characteristic (ROC) analysis was performed with EAOC as the positive outcome. Results: SMBT showed lower cystic ADC values and higher solid ADC values than EAOC, resulting in a smaller ΔADC. ΔADC and solid ADC yielded areas under the ROC curve of 0.924 (95% confidence interval (CI) 0.817–1.000) and 0.918 (95% CI 0.837–1.000), respectively. The difference was not statistically significant ( P = 0.862). At the internally derived ΔADC cutoff of 0.529 ×10 ⁻³ mm ² /s, sensitivity was 94.3% (95% CI 80.8–99.3) and specificity was 92.9% (95% CI 66.1–99.8); because the cutoff was derived and evaluated in the same cohort, these performance estimates may be optimistic. Conclusion: ΔADC showed high diagnostic performance for differentiating SMBT from EAOC, but incremental diagnostic performance over solid ADC was not demonstrated. The internally derived cutoff and associated performance estimates require independent multicenter validation before clinical application.

We report a case of Epstein–Barr virus–positive inflammatory follicular dendritic cell sarcoma (EBV+ IFDCS) of the spleen demonstrating myofibroblastic differentiation with α-smooth muscle actin (α-SMA) expression. A 67-year-old woman was incidentally found to have a 45-mm splenic mass during postoperative surveillance for lung cancer. CT and MRI revealed a well-circumscribed lesion with a fibrous capsule and heterogeneous necrotic components, showing gradual enhancement. FDG-PET/CT demonstrated intense focal uptake (SUVmax=8.40) without additional hypermetabolic lesions. Histopathologic examination showed EBV positivity and CD23 expression with prominent inflammatory infiltrates. Notably, α-SMA expression suggested myofibroblastic differentiation. This case highlights the imaging features of EBV+ IFDCS and suggests a possible association between myofibroblastic differentiation and radiologic characteristics.

Background: Minimum apparent diffusion coefficient (ADC) values are independent predictors of clinically significant prostate cancer (csPC). We developed a novel ADC-based bi-color map and evaluated its utility for identifying lesions suspicious for csPC. Methods: We retrospectively analyzed 108 targeted prostate biopsy cases and 93 radical prostatectomy cases. In the biopsy cohort, we assessed the association between ADC-based bi-color map positivity and csPC in lesions with a Prostate Imaging–Reporting and Data System (PI-RADS) score ≥ 3. In the prostatectomy cohort, we evaluated additional color map-positive lesions not categorized as PI-RADS ≥ 3 on preoperative MRI. Results: In the biopsy cohort, 118 lesions were positive on the ADC-based bi-color map, including lesions outside PI-RADS ≥ 3 categories. Among 157 lesions with a PI-RADS score ≥ 3, csPC was detected in 65 lesions (41.4%). Of these lesions, 70 (44.6%) were positive on the bi-color map, and csPC was identified in 49 (70.0%). The added value of the bi-color map was most evident in PI-RADS 4 lesions, where csPC detection rates were significantly higher in color map-positive than in color map-negative lesions (74.4% vs. 23.3%). In the prostatectomy cohort, 215 lesions were positive on the bi-color map, and csPC was confirmed pathologically in 126 lesions (58.6%). Among 82 color map-positive lesions not classified as PI-RADS ≥3, 55 (67.1%) corresponded to csPC. Conclusions: The ADC-based bi-color map may improve lesion highlighting and risk stratification for csPC and help identify suspicious lesions overlooked on conventional MRI assessment.

Visualization of cranial nerves III-VI (CN III-VI) within the orbit has traditionally been challenging on conventional MRI, even with advanced imaging techniques. Detailed nerve anatomy has largely been inferred from anatomical studies, while most previous MR imaging focused on proximal segments such as the cisternal or cavernous portions of CN III-VI. This study evaluated whether fat-suppressed three-dimensional (3D) FLAIR imaging obtained as part of brain MRI can depict these nerves. This retrospective, IRB-approved study included 46 subjects (92 orbits) without orbital disease who underwent brain MRI, including fat-suppressed 3D FLAIR imaging. Thirteen orbital structures were evaluated: the superior and inferior divisions and 5 orbital branches of the oculomotor nerve (CN III); trochlear nerve (CN IV); abducens nerve (CN VI); 3 branches of the ophthalmic nerve (CN V1) - frontal, lacrimal, nasociliary nerves; and the ciliary ganglion. Three independent readers scored each structure as 1 if identifiable or 0 if not, and detection rates and interobserver agreement were quantified using observed agreement and Gwet's AC1. The inferior and superior divisions of the oculomotor nerve and their branches (medial, inferior, and superior rectus branches), the abducens nerve, and the frontal nerve of V1 were identified in 100% of orbits, with observed agreement ranging from 83.7-98.9% and AC1 ranging from .87-.99. The trochlear nerve, ciliary ganglion, and lacrimal nerve were detected in 96.7-98.9% of orbits, with observed agreement of 78.3-81.5% and AC1 of .82-.84. Smaller or variable branches, including the inferior oblique and levator palpebrae superioris branches of CN III and the nasociliary nerve, showed detectability of 87.0-95.7%, with observed agreement of 17.4-38.0% and AC1 of -.08-.13. Fat-suppressed 3D FLAIR imaging acquired as part of brain MRI enables visualization of orbital nerves of CN III-VI and the ciliary ganglion without specialized sequences. This practical MR neurography approach may support future studies of orbital nerve anatomy and subtle abnormalities.

Parathyroid four-dimensional CT (4DCT) involves repeated non-contrast and multiphase contrast-enhanced acquisitions, leading to increased radiation exposure. As the examination targets the anatomically complex structures of the neck, maintaining high image quality is particularly important. Photon-counting CT (PCCT) is a novel technology reported to improve dose efficiency and image quality compared to conventional energy-integrating detector CT (EIDCT). This study provides a systematic, quantitative comparison of CT scanner radiation output (CTDI_vol and DLP) and image quality, assessed by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), between PCCT and EIDCT for multiphase parathyroid 4DCT exams. In this IRB-approved retrospective study, 96 patients who underwent a 4DCT for the workup of hyperparathyroidism (PCCT, n = 32; EIDCT, n = 64) were reviewed. Regions of interest (ROIs) were placed on the non-contrast, arterial, and venous phase images in the sternocleidomastoid muscles at the upper thyroid level, the anterior scalene muscles at the lower thyroid level, and in the extracorporeal air. Mean attenuation, SNR, and CNR were measured. Statistical analyses included unpaired t-tests and two-way ANOVA. PCCT had significantly lower radiation output across all 4DCT phases (total CTDI_vol 30.6 ± 3.3 vs. 60.8 ± 15.7 mGy; DLP 859 ± 178 vs. 1523 ± 519 mGy·cm; P < .001). SNR and CNR were significantly higher on PCCT across all evaluated ROIs, with lower background noise (all P < .05). Two-way ANOVA confirmed the advantages of PCCT regardless of contrast injection side, with no significant interactions. PCCT substantially reduces CT scanner radiation output while improving quantitative image quality in multiphase parathyroid 4DCT, including technically challenging arterial-phase acquisitions at the lower thyroid level, supporting its technical advantage over conventional EIDCT.

Background: Primary progressive aphasia (PPA) is a clinical syndrome characterized by progressive language impairment. The logopenic variant (lvPPA) is frequently associated with Alzheimer's disease (AD) pathology. With the approval of anti‐amyloid‐β monoclonal antibodies, such as lecanemab and donanemab, for the treatment of AD, accurately differentiating lvPPA due to AD (lvAD) from the other PPA variants has become highly important. Methods: Thirteen patients with PPA who underwent cognitive testing, including the Standard Language Test of Aphasia (SLTA), brain magnetic resonance imaging, single‐photon emission computed tomography (SPECT), cerebrospinal fluid (CSF) biomarker analysis, and amyloid positron emission tomography (PET) imaging were enrolled in this study. Patients were classified into the lvPPA, semantic variant PPA (svPPA), and nonfluent/agrammatic variant PPA (nfaPPA) groups based on the results of clinical and neuropsychological assessments. We determined the proportion of PPA patients in each group who met the optimal use guidelines for anti‐amyloid monoclonal antibody therapy. Results: Six (86%) of the 7 lvPPA patients were amyloid positive (A+), and 5 (71%) were eligible for lecanemab or donanemab. In most lvPPA patients, SPECT displayed an AD‐typical pattern of hypoperfusion in the bilateral temporoparietal regions, posterior cingulate gyrus, and precuneus. One lvPPA patient was negative for AD biomarkers and demonstrated an atypical perfusion pattern for AD, and was subsequently rediagnosed as having frontotemporal lobar degeneration. Conclusions: These results suggest that SPECT may play a supportive role in differentiating lvAD from PPA. In the current clinical era of anti–amyloid‐β monoclonal antibody therapy, accurate identification of lvAD among patients with language‐predominant symptoms is increasingly important. Larger studies should be performed in the near future to validate these findings.

Background: Lecanemab, a monoclonal antibody targeting amyloid-β (Aβ), has been shown to reduce Aβ plaques and slow cognitive decline in patients with Alzheimer's disease (AD). However, its effect on brain structure in real-world clinical settings remains unclear. The voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) enables quantitative assessment of brain atrophy, particularly in the medial temporal lobe, using MRI. Objective: To evaluate the effects of lecanemab on brain structure by analyzing changes in Z-scores derived from VSRAD in AD patients treated with lecanemab in actual clinical practice. Methods: This retrospective study included 16 patients with AD who received four biweekly administrations of lecanemab (10 mg/kg) between February 2023 and August 2024. Amyloid pathology was confirmed via ¹⁸ F-flutemetamol PET and cerebrospinal fluid Aβ _42/40 ratio. VSRAD analysis was performed using three-dimensional sagittal T1-weighted MRI scans obtained before the first and after the fourth lecanemab administration. Changes in the Z-score of medial temporal lobe (MTL) and MTL/whole brain ratios were assessed. Results: After four doses of lecanemab, the Z-score of MTL in AD patients significantly decreased from 1.61 ± 0.76 to 1.38 ± 0.67 ( p < 0.01), and the MTL/whole brain ratio significantly decreased from 6.47 ± 6.48 to 4.59 ± 4.80 ( p < 0.02). Conclusions: Lecanemab treatment was associated with a significant reduction in the Z-score of MTL, indicating a decrease in brain volume. The clinical significance of this brain volumetric change remains uncertain, and hence longitudinal studies linking brain volume reduction with clinical outcomes, including cognition, are warranted.