Japanese Journal of Radiology最新文献

Purpose: To evaluate the cancer detection rates for each category of Prostate Imaging-Reporting and Data System version 2.1 (PI-RADSv2.1) using multiparametric magnetic resonance imaging (mpMRI) and biparametric MRI (bpMRI) based on MRI/ultrasound (US)-fusion biopsy.

Materials and methods: This prospective study included participants who underwent mpMRI or bpMRI with a PI-RADSv2.1 interpretation and subsequently received MRI/US-fusion biopsy between August 2022 and December 2023. The lesion-based detection rates of clinically significant prostate cancer (csPCa) in each PI-RADSv2.1 category and the correlation between PI-RADSv2.1 categories and International Society of Urological Pathology (ISUP) grade groups were analyzed. The diagnostic performance of PI-RADSv2.1 in predicting csPCa was evaluated, and diagnostic performance of mpMRI and bpMRI was compared using cut-offs, with PI-RADSv2.1 categories ≥ 3 or ≥ 4 defined as positive.

Results: A total of 247 lesions from 216 participants were included in this study. A total of 157 patients underwent mpMRI and the remaining 59 underwent bpMRI. The csPCa detection rates for each PI-RADSv2.1 category of mpMRI and bpMRI were as follows: category 1, 0% (0/11); 2, 13% (3/23); 3, 16% (5/31); 4, 60% (43/72); 5, 65% (26/40), in mpMRI; category 1, 0% (0/4); 2, 33% (1/3); 3, 25% (3/12); 4, 61% (19/31); 5, 75% (15/20) in bpMRI. PI-RADSv2.1 categories were significantly positively associated with csPCa detection rates in both mpMRI and bpMRI (p < 0.0001 and p = 0.00048, respectively). PI-RADSv2.1 categories correlated with ISUP grade groups for mpMRI and bpMRI (p < 0.0001 for both). There were no significant differences in the detection rates between mpMRI and bpMRI for PI-RADS v2.1 positive and negative lesions.

Conclusion: PI-RADSv2.1 using mpMRI and bpMRI could stratify the risk of csPCa, and the csPCa detection rate of bpMRI was compatible with that of mpMRI using cut-offs of PI-RADSv2.1 categories ≥ 3 or ≥ 4.

Purpose: We compared quantitative susceptibility mapping (QSM) with wave-CAIPI 9 × (QSM_WC9 ×) with reference standard QSM with GRAPPA 2 × (QSM_G2 ×) in two MR scanners. We also compared detectability of microbleeds in both QSMs to demonstrate clinical feasibility of both QSMs.

Materials and methods: This prospective study was approved by the institutional review board and written informed consent was obtained from each subject. Healthy subjects were recruited to evaluate intra-scanner reproducibility, inter-scanner consistency, and inter-sequence consistency of QSM_G2 × and QSM_WC9 × at 2 MR scanners. Susceptibility values measured with volume of interests (VOIs) were evaluated. Patients who were requested for susceptibility weighted imaging were also recruited in this study to measure microbleeds on QSM_G2 × and QSM_WC9 × . The number of microbleeds was compared between two QSMs.

Results: Total 55 healthy subjects (male 34, female 21, 38.3 years [23-79]) were included in this study. We investigated reproducibility and consistency of QSM_WC9 × by comparing reference standard QSM_G2 × in two MR scanners in this study, and high correlation (ρ, 0.93-0.97) and high intraclass correlation coefficient (ICC) (0.97-0.99) were obtained. Sixty patients (male 30, female 30; age, 55.4 years [21-85]) were finally enrolled in this prospective study. The ICC of the detected number of microbleeds between QSM_G2 × and QSM_WC9 × was 0.99 (0.98-0.99).

Conclusion: QSM_WC9 × and reference standard QSM_G2 × in two MR scanners showed good reproducibility and consistency in estimating magnetic susceptibilities. QSM_WC9 × and QSM_G2 × were also comparable in terms of microbleeds detection with good agreement of raters and high ICC.

Purpose: To optimize NTO parameters in non-coplanar RapidArc (RA) stereotactic radiosurgery (SRS) for multiple brain metastases and compare them with HyperArc (HA) plans.

Materials and methods: Thirty patients with multiple brain metastases, receiving 21 Gy prescriptions, were retrospectively enrolled, with lesions ranging from two to eight and volumes between 0.27 and 10.56 cm³. Non-coplanar RapidArc plans utilized manual NTO (RA-mNTO) with varying dose fall-off values (0.1 mm^-1, 0.5 mm^-1, 1.0 mm^-1, 2.0 mm^-1, 3.0 mm^-1) and end doses (50%, 25% & 10%). Additionally, two HyperArc plans were generated: HA-ALDO used Automatic Lower Dose Objectives with SRS NTO, while HA-mNTO used the same beam geometry with manual NTO parameters optimized from RA-mNTO plans. TrueBeam with High-Definition Multi-leaf Collimators (HDMLC), 6 MV Flattening Filter Free (FFF) Beam at a maximum dose rate of 1400 MU/min, and Eclipse version 16.1 TPS were used. Plans were assessed for Paddick Conformity Index (CI), Gradient Index (GI), Homogeneity Index (HI), normal brain doses (V_18Gy, V_15Gy, and V_12Gy), Monitor Units (MUs), and delivery accuracy using aS1200 Digital Megavolt Imager (DMI) with 2%/2 mm gamma criteria. Statistical analysis utilized integrated scoring and the Wilcoxon signed-rank test.

Results: RA-mNTO plans with 0.5 mm⁻¹ dose fall-off and 10% end-dose showed superior dosimetric outcomes: CI (0.85 ± 0.08), GI (3.63 ± 0.87), and HI (0.36 ± 0.06) compared to HA-ALDO (CI 0.84 ± 0.09, GI: 3.97 ± 0.85, HI: 0.39 ± 0.07) and HA-mNTO (CI 0.83 ± 0.08, GI: 3.60 ± 0.93, HI: 0.40 ± 0.06). MUs were comparable: RA-mNTO (9679 ± 1882), HA-ALDO (9509 ± 1315), and higher for HA-mNTO (10,457 ± 1980). RA-mNTO plans exhibited significantly lower normal brain doses (V_18Gy: 1.78 ± 1.23, V_15Gy: 3.54 ± 2.37, V_12Gy: 6.21 ± 4.09) compared to HA-ALDO (V_18Gy: 2.02 ± 1.34, V_15Gy: 4.09 ± 2.66, V_12Gy: 7.15 ± 4.56) and HA-mNTO (V_18Gy: 1.85 ± 1.20, V_15Gy: 3.68 ± 2.33, V_12Gy: 6.36 ± 3.97). All techniques achieved > 98% gamma pass rate.

Conclusion: Non-coplanar RA plans with optimized mNTO settings outperformed HyperArc plans in all studied dosimetric parameters for SRS treatment of multiple brain metastases.

Purpose: To assess the image quality of a modified Fast three-dimensional (Fast 3D) mode wheel with sequential data filling (mFast 3D wheel) combined with a deep learning denoising technique (Advanced Intelligent Clear-IQ Engine [AiCE]) in contrast-enhanced (CE) 3D dynamic magnetic resonance (MR) imaging of the abdomen during a single breath hold (BH) by intra-individual comparison with compressed sensing (CS) with AiCE.

Methods: Forty-two patients who underwent multiphasic CE dynamic MRI obtained with both mFast 3D wheel using AiCE and CS using AiCE in the same patient were retrospectively included. The conspicuity, artifacts, image quality, signal intensity ratio (SIR), signal-to-noise ratio (SNR), contrast ratio (CR), and contrast enhancement ratio (CER) of the organs were compared between these 2 sequences.

Results: Conspicuity, artifacts, and overall image quality were significantly better in the mFast 3D wheel using AiCE than in the CS with AiCE (all p < 0.001). The SNR of the liver in CS with AiCE was significantly better than that in the mFast 3D wheel using AiCE (p < 0.01). There were no significant differences in the SIR, CR, and CER between the two sequences.

Conclusion: A mFast 3D wheel using AiCE as a deep learning denoising technique improved the conspicuity of abdominal organs and intrahepatic structures and the overall image quality with sufficient contrast enhancement effects, making it feasible for BH 3D CE dynamic MR imaging of the abdomen.

Purpose: Risk stratification for incidence of major adverse cardiovascular events (MACE) in patients with dialysis-dependent end-stage renal disease (dd-ESRD) is challenging. Moreover, the usefulness of coronary CT angiography (CCTA) is often limited because of high calcification. This study aimed to investigate the prognostic value of comprehensive cardiac CT in patients with dd-ESRD for predicting MACE.

Materials and methods: This retrospective analysis included 92 patients with dd-ESRD who underwent comprehensive cardiac CT. Obstructive coronary artery disease (CAD) was defined by CCTA with > 50% stenosis. Global myocardial blood flow (MBF) and summed stress score (SSS) were obtained through dynamic CTP. Cox regression analysis was used to assess correlation with MACE. Kaplan-Meier curves were used to estimate cumulative event rates, and the global Chi-square test was used to assess the incremental value of dynamic CTP over CCTA.

Results: During a median follow-up of 2.3 years, 43 patients experienced MACE. Univariate analysis revealed that presence of obstructive CAD, higher SSS, and lower global MBF were significantly associated with increased risk of MACE. In multivariable analysis, lower global MBF and presence of obstructive CAD were independently associated with MACE (p = 0.02, and p = 0.04, respectively). CCTA and dynamic CTP combination had incremental value over CCTA alone for predicting MACE, respectively (global Chi-square score, 19.3 and 11.7, respectively).

Conclusion: Presence of obstructive CAD on CCTA and lower global MBF on dynamic CTP are independently associated with increased risk of MACE in patients with dd-ESRD. The addition of dynamic CTP to CCTA may improve risk stratification in this population.

Purpose: Under-sampled scans with iterative reconstruction and high-frequency preserving transform (Us-IRHF) can increase the acquisition speed without degrading the image quality by recovering image information from under-sampled data. We investigate the clinical applicability of high spatial resolution magnetic resonance cholangiopancreatography (MRCP) images without extending the scanning time using Us-IRHF.

Methods: A slit phantom was scanned with conventional- (without Us-IRHF), Us-IR- (without HF), and Us-IRHF scanning. The matrix size was 320 × 320 for Us-IR- and Us-IRHF- and 288 × 208 for conventional scanning. Modulation transfer function (MTF) focused on the 1.0 lp/cm gauge for each scanning was calculated. For clinical study we acquired respiratory-triggered 3D MRCP scans with and without Us-IRHF (U⁺-, U^-MRCP) in 41 patients. The matrix size was 320 × 320 for U⁺- and 288 × 208 for U^-MRCP. The acquisition time and the relative duct-to-periductal contrast ratios (RCs) for the right- and left intrahepatic bile-, the common bile-, and the main pancreatic duct were recorded. Visualization of each duct and overall image quality was scored on 5-point confidence scales. For visualization of each duct the score ranged from 1 (not visible) to 5 (visible with excellent details), for the image quality, it ranged from 1 (undiagnostic) to 5 (excellent). Superiority for the qualitative visualization score and non-inferiority for the RC values with prespecified margins were assessed.

Results: Phantom study showed that compared to the conventional- and Us-IR (without HF) images, the MTF for the Us-IRHF image revealed the highest response. For clinical study, the mean acquisition time was 161 s for U⁺- and 165 s for U^-MRCP. For all ducts, the RC value of U⁺MRCP was non-inferior to U^-MRCP and the qualitative visualization score assigned to U⁺MRCP was superior to U^-MRCP.

Conclusion: Us-IRHF improved the image quality of high spatial resolution MRCP without extending the scanning time.

In this narrative review, we review the applications of artificial intelligence (AI) into clinical magnetic resonance imaging (MRI) exams, with a particular focus on Japan's contributions to this field. In the first part of the review, we introduce the various applications of AI in optimizing different aspects of the MRI process, including scan protocols, patient preparation, image acquisition, image reconstruction, and postprocessing techniques. Additionally, we examine AI's growing influence in clinical decision-making, particularly in areas such as segmentation, radiation therapy planning, and reporting assistance. By emphasizing studies conducted in Japan, we highlight the nation's contributions to the advancement of AI in MRI. In the latter part of the review, we highlight the characteristics that make Japan a unique environment for the development and implementation of AI in MRI examinations. Japan's healthcare landscape is distinguished by several key factors that collectively create a fertile ground for AI research and development. Notably, Japan boasts one of the highest densities of MRI scanners per capita globally, ensuring widespread access to the exam. Japan's national health insurance system plays a pivotal role by providing MRI scans to all citizens irrespective of socioeconomic status, which facilitates the collection of inclusive and unbiased imaging data across a diverse population. Japan's extensive health screening programs, coupled with collaborative research initiatives like the Japan Medical Imaging Database (J-MID), enable the aggregation and sharing of large, high-quality datasets. With its technological expertise and healthcare infrastructure, Japan is well-positioned to make meaningful contributions to the MRI-AI domain. The collaborative efforts of researchers, clinicians, and technology experts, including those in Japan, will continue to advance the future of AI in clinical MRI, potentially leading to improvements in patient care and healthcare efficiency.

Purpose: To investigate the value of preoperative apparent diffusion coefficient (ADC) histogram analysis in predicting the prognosis of patients with sinonasal adenoid cystic carcinoma (ACC) and the correlation between ADC histogram parameters and Ki-67 labeling index (LI).

Materials and methods: The study enrolled 66 patients with sinonasal ACC who were surgically resected and confirmed by histopathology. The disease-free survival (DFS) was evaluated with clinical-pathologic and radiologic characteristics using the Cox proportion hazard model. Spearman correlation analysis was used to evaluate the correlation between ADC histogram parameters and Ki-67 LI. The predictive performance of ADC histogram parameters for Ki-67 LI was assessed using the receiver operating characteristic (ROC) curve.

Results: Multivariable analysis showed Ki-67 LI (hazard ratio: 9.279; 95% confidence interval 1.099-78.338; P = 0.041) and ADCskewness (hazard ratio: 5.942; 95% confidence interval 1.832-19.268; P = 0.003) were significant independent predictors of DFS. The combination of these two variables achieved the predictive ability with a C-index of 0.717 (95% confidence interval 0.607-0.826). ADCmean and all ADC percentiles (10th, 50th, and 90th) significantly and inversely correlated with Ki-67 LI of ACC (Correlation coefficients = - 0.574 to - 0.591, Ps < 0.001). Among the ADC histogram parameters, the ADC50th showed superior performance for the differentiation of the high from low Ki-67 LI groups with an area under the curve (AUC) of 0.834 and an accuracy of 80.30%.

Conclusion: ADC histogram analysis had predictive value for DFS and Ki-67 LI, which may be a valuable biomarker for prognosis and proliferation status for ACC in clinical practice.

Objective: The aim of this special report is to describe the 6th edition of "The Guidelines for the Management of Pulmonary Nodules Detected by Low-Dose CT Lung Cancer Screening ".

Methods: Since the 5th edition six years ago, a review of the literature and consideration of consistency with new evidence led to the revision of the 6th edition.

Results: The main revisions in the 6th edition can be summarized as follows: 1) addition of the section "Recommendations for Low-Dose CT Lung Cancer Screening in Japan"; 2) change in the recommended solid component diameter, and follow-up interval for nodules with a total mean diameter of less than 15 mm and a solid component diameter of less than 8 mm; 3) replacement of the recommended case images; and 4) introduction of the criteria of the Accreditation Council for Lung Cancer CT Screening.

Conclusion: This guideline is gradually gaining acceptance in Japan. This guideline should be applied carefully in clinical practice, considering various factors such as the patient's condition.