Japanese Journal of Radiology最新文献

Proper treatment of intra-articular tumor/tumor-like lesions (tenosynovial giant cell tumor, synovial chondromatosis, synovial hemangioma / intra-articular venous malformations, lipoma arborescens, etc.) depends on an accurate diagnosis. This review highlights the imaging findings of intra-articular tumor/tumor-like lesions and the other synovial diseases (gout, amyloid arthropathy, rheumatoid arthritis, ganglion, and postoperative intra-articular tumor) to determine whether they could help in establishing the correct diagnosis. Many synovial proliferative diseases have specific imaging characteristics and an awareness of these characteristics along with their pathological and anatomical features can allow for an accurate diagnosis. Even though a wide spectrum of diseases may involve the synovium, careful MRI assessment used in conjunction with clinical information can lead to a substantial narrowing of the differential diagnosis.

Background: Conventional ¹²³I-ioflupane dopamine-transporter SPECT requires 25-40 min of acquisition, causing patient discomfort and limiting throughput. This study assessed whether deep-learning (DL) reconstruction can yield diagnostic-quality images from a 5-min scan.

Methods: We retrospectively analysed 207 studies (1035 slices) obtained between April 2018 and June 2020. After cropping to 64 × 64 striatal regions, 600, 185 and 250 images from 120, 37 and 50 patients were used for training, validation and testing. Six convolutional architectures-U-Net (one-five depths), V-Net, U-Net +  + , R2U-Net, Attention U-Net and TransUNet-were trained to translate 5-min into virtual 25-min images. Image quality was assessed with peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), analysed by Friedman and Dunn-Holm tests. A blinded reader study involved three nuclear medicine physicians grading 50 cases (100 striata) on a four-point scale; agreement with the 25-min consensus was measured by weighted κ and intra-/inter-observer intraclass correlation coefficients (ICC).

Results: All DL reconstructions significantly outperformed raw 5-min images in PSNR and SSIM (p < 0.01). The four-layer U-Net achieved the highest quality (PSNR 32.7 ± 1.7 dB, SSIM 0.842 ± 0.069), ≈1.8 dB and 0.13 higher than baseline, and statistically indistinguishable from 25-min images (p > 0.05). Reader concordance improved from fair with baseline (κ = 0.29-0.41) to substantial with the four-layer U-Net (κ = 0.62-0.70); intra-reader ICC was 0.84-0.93 and inter-reader ICC 0.73-0.75.

Conclusions: A compact four-layer U-Net restores diagnostic fidelity to 5-min ¹²³I-ioflupane SPECT, enabling an 80% reduction in scan time without loss of quantitative metrics or interpretability. DL-accelerated protocols may enhance comfort, reduce motion artefacts and increase throughput, warranting prospective multicentre validation.

Purpose: An artificial intelligence (AI) system for detecting interstitial lung abnormalities (ILA) was previously developed but requires external validation. This study aimed to examine the robustness across different populations and investigate associations between the system outputs and traction bronchiectasis/bronchiolectasis severity patterns.

Materials and methods: CT scans from population-based samples of the Rotterdam Study (2018-2019) and the Age Gene/Environment Susceptibility Reykjavik (AGES-Reykjavik) Study (baseline CT: 2002-2006, follow-up CT: 2007-2011) were used in this secondary analysis of the two cohorts. The AI system calculated ILA probability score (AI score) in the range from 0 to 1. Three experienced readers evaluated independently all CT scans for ILA, and two chest radiologists assessed traction bronchiectasis/bronchiolectasis using the 4-scale traction bronchiectasis/bronchiolectasis index (TBI) for severity by consensus. Receiver operating characteristic (ROC) analysis and Kruskal-Wallis test were used for statistical analysis.

Results: The system analyzed 932 CT scans of the Rotterdam Study (mean participant age, 79.6 years ± 4.3 (SD), 482 women) and 5242 CT scans of the AGES-Reykjavik Study (mean participant age, 76.4 years ± 5.6, 3032 women), and achieved area under the ROC curve of 0.841 (95% CI 0.804, 0.879) and 0.823 (95% CI 0.798, 0.847), respectively. AI scores correlated with readers' certainty, decreasing from unanimous ILA cases to No-ILA cases. Higher baseline AI scores correlated with greater severity of traction bronchiectasis/bronchiolectasis (TBI-3: 0.931 [IQR, 0.911-0.932], TBI-2: 0.738 [IQR, 0.406-0.880], TBI-1: 0.537 [IQR, 0.317-0.761], TBI-0: 0.250 [IQR, 0.136-0.455]).

Conclusion: The system demonstrated robust ILA detection performance across different populations, with AI scores showing associations with traction bronchiectasis/bronchiolectasis severity.

Purpose: Accurate identification of brain metastases is critical for determining prognosis and guiding treatment. Deep learning reconstruction (DLR) enhances MRI quality by reducing noise, while super-resolution DLR (SR-DLR) may further improve spatial resolution and lesion detectability. To evaluate SR-DLR versus conventional DLR in detecting and visualizing brain metastases on postcontrast T1-weighted brain MRI.

Materials and methods: This retrospective study included 47 consecutive patients who underwent postcontrast 3D whole-brain T1-weighted MRI between July and December 2024. Images were reconstructed using both SR-DLR and DLR. Three independent readers evaluated metastatic lesion detection and rated image quality. Subjective assessments included lesion visibility, visibility of normal structures, sharpness, noise, and overall image quality. Objective metrics-full width at half maximum (FWHM), edge rise distance (ERD), edge rise slope (ERS), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)-were also measured. Statistical tests included jackknife alternative free-response receiver operating characteristic (JAFROC) analysis, Wilcoxon signed-rank test, McNemar's test, and paired t-tests, with significance threshold of p < 0.050.

Results: A total of 117 brain metastases were detected in 47 patients (mean age, 59 years ± 18; 27 men). SR-DLR demonstrated significantly better lesion detection performance than DLR (mean figure of merit = 0.842 vs. 0.797; p = 0.042). Subjective image quality ratings favored SR-DLR for lesion and structure visibility, sharpness, noise, and overall quality in most cases. Objectively, SR-DLR yielded lower FWHM (1.2 mm vs. 1.9 mm; p < 0.001), higher ERS (791.3 mm^- 1 vs. 645.3 mm^- 1; p = 0.013) indicating enhanced sharpness as well as improved CNR (27.5 vs. 24.9; p < 0.001) compared to DLR.

Conclusion: Compared to DLR, SR-DLR significantly enhances brain MRI quality and improves detection of metastatic lesions.

Purpose: We aimed to compare visual and quantitative assessments between PET/CT at 90 min and sequential PET/MRI at approximately 120 min after injection of ¹⁸F-flutemetamol, and to investigate factors affecting differences in standardized uptake value ratio (SUVr) and Centiloid scale.

Materials and methods: Eighty-three participants underwent both PET/CT and sequential PET/MRI. Two nuclear medicine physicians performed visual interpretations. SUVr was calculated using four reference regions-pons, whole cerebellum, cerebellar gray matter (CGM), and whole cerebellum and brainstem-and compared between PET/CT and PET/MRI. Centiloid Scale was also compared between PET/CT and PET/MRI. Subgroup analyses were conducted based on Centiloid scale. Associations between scan interval, age, and amyloid burden were evaluated using stepwise regression. Cerebrospinal fluid (CSF) biomarkers were compared with imaging findings in 52 participants. Additionally, six participants underwent dynamic PET/MRI at 0, 60, 90, and 120 min post-injection.

Results: Visual interpretation showed high agreement between PET/CT and PET/MRI (κ = 0.97), and 98% concordance with CSF findings. SUVr and Centiloid scale demonstrated a strong intraclass correlation coefficient of 0.96-0.98. However, SUVr and Centiloid scale were significantly higher from PET/CT than from PET/MRI, except for SUVr using CGM. Age and Centiloid scale were significant predictors of modality differences. Scan interval was also significant when CGM was used as the reference region. Dynamic PET/MRI revealed time-dependent increases in Centiloid scale among amyloid-positive participants. High concordance in visual and quantitative assessments was seen for ¹⁸F-flutemetamol PET/CT (90 min) and subsequent PET/MRI (120 min). While diagnostic agreement was preserved, quantitative values were influenced by amyloid burden, age, and scan timing. These findings suggest a need for careful consideration when interpreting quantitative metrics across different imaging modalities and time points.

The purpose of this study is to report profile data on the technical elements of Japanese particle therapy facilities. We requested a survey on the following four technical elements; (1) facilities and systems, (2) immobilization device and treatment planning CT, (3) patient specific QA, and (4) patient positioning. Responses were received from 21 facilities. The most commonly used accelerators were synchrotrons, which were used in 17 facilities (81.0%). The lowest available energy was widely distributed between 55.6 MeV/u and 290 MeV/u, but the maximum energy was often around 240 MeV/u for proton beams and 430 MeV for carbon ion beams. Of all treatment rooms, passive irradiation accounted for 57.7% (30 rooms), layer stacking irradiation for 7.7% (4 rooms), and scanning irradiation for 32.7% (17 rooms). Shell-type immobilization devices were most commonly used in the head and neck region, and vacuum bags were most commonly used in the thoracic to caudal regions. Lateral dose profile measurement was the most commonly used patient specific QA method. The most commonly used detector was the ionization chamber or ionization chamber-type planar detector. 2D X-ray radiography was the most commonly used in patient positioning. Marker matching was commonly used for the prostate and liver, bone matching for the head and neck and lungs, and tumor matching was used only sparingly. The results of this study may clarify current issues in particle therapy technology and provide data to guide further technology development.

Purpose: The aim of this study was to evaluate the pharmacokinetics and safety of gadopiclenol in Japanese healthy volunteers. A population-based pharmacokinetic approach was used to compare pharmacokinetic parameters with a non-Japanese adult population.

Materials and methods: In this double-blind, placebo-controlled phase I study, Japanese healthy volunteers were randomized to receive gadopiclenol (at 0.025, 0.05, or 0.1 mmol/kg) or a placebo. Blood and urine samples were collected up to 24- and 48-h post-administration, respectively. The pharmacokinetic profile of gadopiclenol was evaluated using standard non-compartmental analysis. Adverse events (AEs) were collected during the whole study period.

Results: Overall, 27 participants were randomized (median [range] age: 22 [20-43] years; 52% male): 18 received gadopiclenol (6 in each dose group), and 9 received the placebo. The mean systemic exposure of gadopiclenol increased proportionally with the injected dose (area under the curve [AUC]: 215-1034 μg/mL.h) and was comparable between the three dose groups when normalized to dose (AUC/dose: 182-189 μg/mL/g.h) and to non-Japanese (168-183 μg/mL.h). The mean terminal half-life (1.43-1.86 h), and the distribution volume (11.3-15.2 L) were also similar to those of non-Japanese healthy volunteers (1.50-1.73 h and 13.0-15.5 L, respectively). The mean fraction of gadopiclenol excreted in urine was between 87 and 95%, depending on the administered dose. Most of gadopiclenol (median of 95.7%) was excreted within 24 h after administration. The mean total clearance was comparable between the different administered doses (5.3-5.6 L/h) and similar to the mean renal clearance. No gadopiclenol-related AEs were reported.

Conclusions: The pharmacokinetic profile of gadopiclenol is similar in Japanese and non-Japanese healthy volunteers. The population pharmacokinetic analysis showed no significant ethnic disparities between these two populations and suggested that no dose adjustment was required for Japanese patients. Gadopiclenol had a very good tolerability in Japanese healthy volunteers with no adverse reactions reported.

Purpose: We aimed to evaluate whether the ALPS index derived from diffusion tensor image analysis along the perivascular space (DTI-ALPS) is influenced by white matter fibres within the analysis region, particularly commissural fibres from the corpus callosum that traverse this area in psychiatric patients with suspected obstructive sleep apnea (OSA). We also investigated associations between diffusion-based parameters, sleep-related data, and neurofluid-related imaging metrics.

Methods: Fifty participants with OSA underwent brain magnetic resonance imaging and polysomnography, including diffusion tensor and structural sequences. Among them, 8 participants had no psychiatric comorbidities, while the remaining 42 had various psychiatric disorders in addition to OSA. Diffusion-based parameters were obtained, and both the original and variant ALPS index were calculated. Correlation analyses were conducted with sleep-related data and neurofluid-related imaging parameters, including choroid plexus volume (CPV) and volume of white matter lesion burden (WMHV). Mediation analyses were also performed to explore the influence of white matter diffusivity on the perivascular diffusivity index.

Results: The ALPS index showed weak to moderate correlations with multiple sleep-related variables. It also correlated with CPV and WMHV. Mediation analyses demonstrated that diffusivity within white matter fibres was associated with the ALPS index. Moreover, variant ALPS indices measured in the corpus callosum may reflect fluid motion in the direction of perivascular spaces.

Conclusion: These findings suggest that the ALPS index is influenced by both diffusivity along perivascular spaces and white matter microstructure, particularly commissural fibres. Although it should not be regarded as a highly specific marker of perivascular space function, variant indices support partial perivascular contribution. Furthermore, associations with sleep and neurofluid-related metrics imply that white matter architecture and inter-fibre spaces may serve as plausible routes for interstitial fluid flow.