Yoshiyuki Ozawa

Purpose: Metabolic syndrome (MetS) is screened for or assessed by manual waist circumference (WC) measurements or adipose tissue evaluation using supine multidetector CT (MDCT). Currently, upright MDCT was clinically established and tested for different clinical aims. The purpose of this study was to directly compare the utility of metabolic disorder assessments and the diagnosis of MetS among WC, upright MDCT, and supine MDCT in a Japanese health checkup test cohort. Materials and methods: This study cohort consisted of 47 consecutive subjects who underwent WC measurements, blood tests, upright MDCT, and supine MDCT on the same day. In each subject, the total fat area (TFA), subcutaneous fat area (SFA), visceral fat area (VFA), and visceral-to-subcutaneous fat ratio (VSR) were semi-automatically assessed using upright MDCT and supine MDCT data. To compare each index on both CTs, as well as manual WC measurements between the MetS and non-MetS groups, Student’s t -test was performed. Univariate regression analyses were performed to evaluate the relationship between each index and blood test results. Subsequently, receiver operating characteristic (ROC)-based positive tests were performed. Finally, the sensitivity, specificity, and accuracy were compared among all indexes from both CTs, and a manual WC measurement evaluation was conducted using McNemar’s test. Results: Some indices showed significant differences between two groups ( p < 0.05). All indices shows significant correlations with BMI, TG, HDL-cholesterol, uric acid, glucose, HbA1c, insulin, HOMA-IR, GOT (or AST), GPT (or ALT), or creatinine (manual WC measurement: − 0.58 ≤ r ≤ 0.87, p < 0.05; supine MDCT: − 0.61 ≤ r ≤ 0.84, p < 0.05; upright MDCT: − 0.64 ≤ r ≤ 0.91, p < 0.05). TFA and VFA on upright MDCT had significantly higher sensitivities than WCs determined from manual and supine MDCT as well as the VSR ( p < 0.05). Conclusion: Upright MDCT-derived adipose tissue indices showed preliminary potential for assessing metabolic syndrome, but larger prospective studies are needed to validate their clinical utility.

Background/Objectives: To directly compare the capabilities of hybrid-type iterative reconstruction (IR) with the newly developed deep learning reconstruction (DLR) for the inner ear on high-definition CT (HDCT) obtained using the super-high-resolution (SHR) mode for external, middle and inner ear evaluations and diagnosis in patients with and without otologic diseases. Methods: Included in this study were 140 patients who had undergone HDCT, consisting of 32 otologic disease patients and 108 non-otologic disease patients, and 280 inner and middle ears and temporal bones were evaluated on a per ear analysis. Signal-to-noise ratios (SNRs) of the temporal bone surrounding the aural vestibule of the ear and in the vestibule as well as the cerebellar hemisphere, overall image and detailed evaluation of the visibility of anatomical landmarks in the middle and inner ear and temporal bone obtained with the two methods were assessed and statistically compared using the paired t-test or Wilcoxon’s signed-rank test. Then, receiver operating characteristic (ROC) analysis was performed to compare diagnostic performance between two reconstruction methods. Results: Each SNR of DLR was significantly higher than that of hybrid-type IR (p < 0.05). Overall image quality and detailed visualization of each anatomical structure obtained with DLR were significantly better than those obtained with hybrid-type IR (p < 0.05). The area under the curve of DLR had no significant difference with hybrid-type IR (p = 0.18). Conclusions: DLR has superior potential to hybrid-type IR for better image quality and visualization of anatomical landmarks in middle and inner ears and temporal bones on HDCT, although diagnostic performance was not affected in clinical practice.

Purpose: Since the clinical application of computed tomography (CT), cardiac and respiratory motion artifacts have caused decreased image quality and reduced detection or quantitative or qualitative evaluation of lung parenchymal or vascular abnormalities on chest CT with lung window settings in patients with pulmonary diseases. Recently, a deep learning (DL)-based motion correction algorithm (CLEAR Motion) has been developed and clinically used for chest CT. We hypothesized that CLEAR Motion can significantly reduce motion artifacts on chest CT examinations relative to conventional chest CT images reconstructed without CLEAR Motion. The purpose of this study was to determine the utility of CLEAR Motion for image quality improvement in chest CT with lung window settings in patients with various pulmonary diseases. Materials and methods: Fifty-six consecutive patients with various thoracic diseases underwent non-electrocardiogram-gated chest helical CT examination using a 320-detector row CT and underwent reconstruction using the conventional reconstruction method and CLEAR Motion. To compare the quantitative image quality, the cardio-pulmonary edge distance (CPED) and slope (CPES) were measured on each CT scan in the axial plane. Comparing cardiac motion reduction capability, overall image quality, cardiac motion artifact, and region conspicuity were visually assessed in the lung window setting on the axial, coronal, and sagittal planes. The paired t-test and Wilcoxon signed-rank test were then performed. Results: The CPEDs and CPESs of the entire lung and left lung on CT with CLEAR Motion were significantly superior to those of CT without CLEAR Motion ( p < 0.001). The overall image quality, cardiac motion artifact, and region conspicuity on CT with CLEAR Motion were significantly higher than those without CLEAR Motion on each plane ( p < 0.001). Conclusion: The DL-based motion correction algorithm named as ‘CLEAR Motion’ has a potential to improve image quality on chest CT with lung window setting in patients with pulmonary diseases.

Background: Prognostic markers reflecting nutritional vulnerability in idiopathic pulmonary fibrosis (IPF) remain poorly defined. Methods: In this prospective cohort study, 63 stable outpatients with IPF were followed for 3 years. Sarcopenia was defined according to the 2019 Asian Working Group for Sarcopenia criteria. Serum transthyretin levels were measured concurrently. Cox proportional hazards regression, binary logistic regression, and Kaplan–Meier survival analyses were performed. Results: During follow-up, 18 patients (29%) died and 21 (33%) experienced respiratory-related hospitalization. Serum transthyretin was an independent predictor of both 3-year mortality and respiratory-related hospitalization, even after adjusting for the Gender–Age–Physiology index. Conversely, sarcopenia and low appendicular skeletal muscle mass index (ASMI) were not independently associated with either outcome. Kaplan–Meier analysis demonstrated significant differences in both mortality and hospitalization according to serum transthyretin levels. Low ASMI evaluated using sex-specific cutoffs was associated with higher mortality in the unadjusted analysis, but not with hospitalization; sarcopenia was not significantly associated with either endpoint. Conclusions: Serum transthyretin may serve as a practical biomarker of nutritional vulnerability, providing complementary prognostic information beyond muscle mass-based assessment in IPF.

To evaluate the image quality and clinical utility of high-resolution computed tomography (CT) images reconstructed using post-processing with a 1024 × 1024 matrix. Four CT image types were reconstructed: type A (512 × 512 matrix, 1-mm slice thickness), type B (1024 × 1024 matrix, 1-mm slice thickness), type C (1024 × 1024 matrix, 0.5-mm slice thickness), and type D (retargeted zoomed images; 512 × 512 matrix, 1-mm slice thickness). Type D images served as the reference standard with a field of view (FOV) half that of the other image types. Phantom image quality was objectively assessed using the task transfer function (TTF), noise power spectrum (NPS), and attenuation profile analysis. In the clinical study, two radiologists independently evaluated image quality in 93 patients, including abnormal lung findings, normal structures, and subjective image noise. In the phantom study, post-processing 1024 × 1024 matrix reconstruction derived from the same sinogram as conventional 512 × 512 reconstruction improved spatial resolution while maintaining comparable noise characteristics at the same slice thickness. Clinically, image quality of normal structures and abnormal lesions was significantly higher in the order of type C > type B > type A (p < 0.0001). Subjective image noise followed the same order. Image quality and noise levels of type B images were comparable to those of type D images. Post-processing 1024 × 1024 matrix reconstruction improves spatial resolution and provides clinically useful high-resolution CT images comparable to retargeted zoomed reconstruction without the limitation of a reduced FOV. The online version contains supplementary material available at 10.1007/s11604-026-01964-0.

Background/Objectives: The rates and predictors of clinical remission, a novel and practical therapeutic goal in severe asthma, have been inconsistently reported across studies. Data on clinical remission in Japanese patients remain limited. The aim of this study was to assess the rate of four-component clinical remission and its predictors in Japanese adult patients with severe asthma. Methods: This retrospective study enrolled adult patients with severe asthma who had initiated biologic therapy at least 12 months prior to inclusion at Nagoya City University Hospital. The primary endpoint was the achievement rate of four-component clinical remission, defined as (1) no maintenance oral corticosteroids (OCS); (2) no exacerbations for 12 months; (3) Asthma Control Test (ACT) score ≥ 20; and (4) forced expiratory volume in one second (FEV₁) ≥ 80% of predicted. The secondary endpoint was to identify factors, including airway structural indices measured using chest computed tomography (CT), associated with clinical remission at 12 months. Results: Among 87 patients with severe asthma, 26 (30%) achieved four-component clinical remission after 12 months of biologic therapy. In univariate analysis, clinical remission was more frequently achieved in patients with chronic rhinosinusitis, higher FEV₁ (% predicted), higher blood eosinophil counts, higher ACT scores, fewer exacerbations in the previous year, higher Lund–Mackay scores, and smaller airway wall thickness and luminal areas on CT (all p < 0.05). Multivariate analysis revealed that higher blood eosinophil counts and fewer exacerbations in the previous year were independently associated with clinical remission (both p < 0.05). Conclusions: After 12 months of biologic therapy, 30% of patients with severe asthma achieved four-component clinical remission. Higher blood eosinophil counts and fewer prior exacerbations were associated with higher remission rates.

Purpose: To evaluate whether reverse encoding distortion correction (RDC) improves image quality and maintains apparent diffusion coefficient (ADC) measurements in diffusion-weighted imaging (DWI) on female pelvic MRI using a 1.5-T in in vitro and in vivo studies.Methods: This retrospective, institutional review board-approved study included both in vitro and in vivo analyses of 31 women (mean age, 41 ± 15 years; range, 24–80 years) who underwent pelvic MRI between January and March 2022. T2-weighted image (T2WI) and DWI with and without RDC were acquired, and ADC maps were generated. Quantitative metrics included SNR, contrast-to-noise ratio (CNR), ADC values, and deformation ratio (DR), defined as the proportional area discrepancy between DWI and T2WI for the uterine corpus, cervix, ovary, and lesions. Qualitative assessments—overall image quality (OIQ), deformation severity (DS), and diagnostic confidence level (DCL)—were independently scored by 2 blinded radiologists using 5-point scales.Results: In vitro SNR and ADC values showed no significant differences between DWI with and without RDC, with strong correlations to reference measurements (ρ = 0.99, P < 0.001). In vivo, SNR, CNR, and ADC values of the myometrium, cervix, and ovary did not differ significantly between 2 methods (P > 0.05). DRs were significantly lower in DWI with RDC than in DWI without RDC (P ≤ 0.0003). ADC values showed strong correlations between DWI with and without RDC on uterine corpus, cervix, ovary and lesions (ρ = 0.82–0.90, P < 0.001). Qualitative scores improved with RDC: higher OIQ (P = 0.0004), lower DS (P = 0.0004), and higher DCL (P = 0.03). Interobserver agreement ranged from substantial to almost perfect (κ = 0.78–0.97).Conclusion: RDC improves image quality and reduces image distortion in DWI on female pelvic MRI at a 1.5-T, while maintaining ADC measurements in in vitro and in vivo settings.