Purpose: To evaluate how the relationship between respiratory interval (RI) and temporal resolution (TR) impacts image quality in free-breathing abdominal MRI (FB-aMRI) using golden-angle radial sparse parallel (GRASP).

Methods: Ten healthy volunteers (25.9 ± 2.5 years, four women) underwent 2 mins free-breathing fat-suppression T1-weighted imaging using GRASP at RIs of 3 and 5s (RI₃ and RI₅, respectively) and retrospectively reconstructed at TR of 1.8, 2.9, 4.8, and 7.7s (TR_1.8, TR_2.9, TR_4.8, and TR_7.7, respectively) in each patient. The standard deviation (SD) under the diaphragm was measured using SD maps showing the discrepancy for each horizontal section at all TRs. Two radiologists evaluated image quality (visualization of the right hepatic vein at the confluence of the inferior vena cava, posterior segment branch of portal vein, pancreas, left kidney, and artifacts) at all TRs using a 5-point scale.

Results: The SD was significantly higher at TR_1.8 compared to TR_4.8 (P < 0.01) and TR_7.7 (P < 0.001), as well as at TR_2.9 compared to TR_7.7 (P < 0.01) for both RIs. The SD between TR_4.8 and TR_7.7 did not differ for both RIs. For all visual assessment metrics, the TR_1.8 scores were significantly lower than the TR_4.8 and TR_7.7 scores for both RIs. The pancreas and left kidney scores at TR_2.9 were significantly lower than those at TR_7.7 (P < 0.05) for RI₅. Additionally, the left kidney score at TR_1.8 was lower than that at TR_2.9 (P < 0.05) for RI₃. All scores at TR_2.9, TR_4.8, and TR_7.7 were similar for RI₃, while those at TR_4.8 and TR_7.7 were similar for RI₅.

Conclusion: Prolonging the TRs compared to RIs enhances image quality in FB-aMRI using GRASP.

Purpose: To investigate the predictive performance of radiomic features extracted from breast MRI for upgrade of ductal carcinoma in situ (DCIS) to invasive carcinoma.

Methods: This retrospective study included 71 women with DCIS lesions diagnosed preoperatively by biopsy. All women underwent breast dynamic contrast-enhanced (DCE) MRI of the breast, which included pre-contrast and five post-contrast phases continuously with a time resolution of 60s. Lesion segmentation was performed manually, and 144 radiomic features of the lesions were extracted from T2-weighted images (T2WI), pre-contrast T1-weighted images (T1WI), and post-contrast 1st, 2nd, and 5th phase subtraction images on DCE-MRI. Qualitative features of mammography, ultrasound, and MRI were also assessed. Clinicopathological features were evaluated using medical records. The least absolute shrinkage and selection operator (LASSO) algorithm was applied for features selection and model building. The predictive performance of postoperative upgrade to invasive carcinoma was assessed using the area under the receiver operating characteristic curve.

Results: Surgical specimens revealed 13 lesions (18.3%) that were upgraded to invasive carcinoma. Among clinicopathological and qualitative features, age was the only significant predictive variable. No significant radiomic features were observed on T2WI and post-contrast 2nd phase subtraction images on DCE-MRI. The area under the curves (AUCs) of the LASSO radiomics model integrated with age were 0.915 for pre-contrast T1WI, 0.862 for post-contrast 1st phase subtraction images, and 0.833 for post-contrast 5th phase subtraction images. The AUCs of the 200-times bootstrap internal validations were 0.885, 0.832, and 0.775.

Conclusion: A radiomics approach using breast MRI may be a promising method for predicting the postoperative upgrade of DCIS. The present study showed that the radiomic features extracted from pre-contrast T1WI and post-contrast subtraction images in the very early phase of DCE-MRI were more predictable.

Purpose: This study was conducted to evaluate whether thin-slice 2D fat-saturated proton density-weighted images of the shoulder joint in three imaging planes combined with parallel imaging, partial Fourier technique, and denoising approach with deep learning-based reconstruction (dDLR) are more useful than 3D fat-saturated proton density multi-planar voxel images.

Methods: Eighteen patients who underwent MRI of the shoulder joint at 3T were enrolled. The denoising effect of dDLR in 2D was evaluated using coefficient of variation (CV). Qualitative evaluation of anatomical structures, noise, and artifacts in 2D after dDLR and 3D was performed by two radiologists using a five-point Likert scale. All were analyzed statistically. Gwet’s agreement coefficients were also calculated.

Results: The CV of 2D after dDLR was significantly lower than that before dDLR (P < 0.05). Both radiologists rated 2D higher than 3D for all anatomical structures and noise (P < 0.05), except for artifacts. Both Gwet’s agreement coefficients of anatomical structures, noise, and artifacts in 2D and 3D produced nearly perfect agreement between the two radiologists. The evaluation of 2D tended to be more reproducible than 3D.

Conclusion: 2D with parallel imaging, partial Fourier technique, and dDLR was proved to be superior to 3D for depicting shoulder joint structures with lower noise.

Purpose: We aimed to investigate the changes in intravoxel incoherent motion (IVIM) and diffusion parameters between in vivo and post-mortem conditions and the time dependency of these parameters using two different mouse tumor models with different vessel lumen sizes.

Methods: Six B16 and six MDA-MB-231 xenograft mice were scanned using 7 Tesla MRI under both in vivo/post-mortem conditions. Diffusion weighted imaging with 17 b-values (0–3000 s/mm²) were obtained at two diffusion times (9 and 27.6 ms). The shifted apparent diffusion coefficient (sADC) using 2 b-values (200 and 1500 s/mm²), non-Gaussian diffusion and IVIM parameters (ADC₀, K, f_IVIM) were estimated at each of the diffusion times. The results were evaluated by repeated measures two-way analysis of variance and post hoc Bonferroni test.

Results: In B16 tumors, f_IVIM significantly decreased with post-mortem conditions (from 12.6 ± 6.5% to 5.2 ± 1.9%, P < 0.05 at long diffusion time; from 11.0 ± 2.4% to 4.6 ± 2.7%, P < 0.05 at short diffusion time). In MDA-MB-231 tumors, f_IVIM also significantly decreased (from 8.8 ± 3.8% to 2.6 ± 1.1%, P < 0.05 at long; from 7.9 ± 5.4% to 2.9 ± 1.1%, P < 0.05 at short). No diffusion time dependency was observed (P = 0.59 in B16 and P = 0.77 in MDA-MB-231). The sADC and ADC₀ values tended to decrease and the K value tended to increase after sacrificing and when increasing the diffusion time.

Conclusion: The f_IVIM values dropped after sacrificing, confirming that IVIM MRI is a promising quantitative parameter to evaluate blood microcirculation. The presence of residual post-mortem f_IVIM values suggested that the influence of water molecule diffusion in the blood lumen may contribute to the IVIM effect. Diffusion MRI parameter’s time dependency and those changes after sacrificing could possibly provide additional insights into diffusion hindrance mechanisms.

Purpose: Chronic obstructive pulmonary disease (COPD) is a complex multisystem disease associated with comorbidities outside the lungs. The aim of this study was to measure changes in metrics of pulmonary gas exchange function and brain tissue metabolism in a mouse model of COPD using hyperpolarized ¹²⁹Xe (HP ¹²⁹Xe) MRI/MR spectroscopy (MRS) and investigate the relationship between the metrics of lung and brain.

Methods: COPD phenotypes were induced in 15 mice by 6-week administration of cigarette smoke extract (CSE) and lipopolysaccharide (LPS). A separate negative control (NC) group was formed of 6 mice administered with saline for 6 weeks. After these 6-week administrations, the pulmonary gas exchange function parameter f_D (%) and the rate constant, α (s⁻¹), which are composed of the cerebral blood flow F_i and the longitudinal relaxation rate 1/T_1i in brain tissue, were evaluated by HP ¹²⁹Xe MRI/MRS.

Results: The f_D of CSE-LPS mice was significantly lower than that of NC mice, which was in parallel with an increase in bronchial wall thickness. The α in the CSE-LPS mice decreased with the decrease of f_D in contrast to the trend in the NC mice. To further elucidate the opposed trend, the contribution of T_1i was separately determined by measuring F_i. The T_1i in the CSE-LPS mice was found to correlate negatively with f_D as opposed to the positive trend in the NC mice. The opposite trend in T_1i between CSE-LPS and NC mice suggests hypoxia in the brain, which is induced by the impaired oxygen uptake as indicated by the reduced f_D.

Conclusion: This study demonstrates the feasibility of using HP ¹²⁹Xe MRI/MRS to study pathological mechanisms of brain dysfunction in comorbidities with COPD.

Purpose: Gadolinium-based contrast media (GBCM) may affect apparent diffusion coefficient measurements on diffusion-weighted imaging. We aimed at investigating the effect of GBCM and inter-reader variation on intravoxel incoherent motion (IVIM) parameters in breast lesions.

Methods: A total of 89 patients referred to 3T breast MRI with at least one histologically verified lesion were included. IVIM data were acquired using a single-shot echo planar imaging sequence before and after GBCM administration. D (true diffusion coefficient), D* (pseudo-diffusion coefficient) and f (perfusion fraction) were calculated and measured by two readers (R1, R2). Inter-reader and intra-reader agreements were assessed by intraclass correlation coefficients (ICCs) and Bland–Altman plots.

Results: D was comparable before and after GBCM administration and between readers. D* and f decreased after GBCM administration and showed a lower agreement between readers. Intra-reader agreement before and after GBCM administration was almost perfect for D for both R1 and R2 (ICC 0.955 and 0.887). The intra-reader agreement was substantial to moderate for D* (ICC R1 0.708, R2 0.583) and moderate for f (ICC R1 0.529 and R2 0.425). Inter-reader agreement before GBCM administration was almost perfect for D (ICC 0.905), substantial for D* (ICC 0.733), and moderate for f (ICC 0.404); after contrast media administration, it was almost perfect for D (ICC 0.876) and substantial for D* (ICC 0.654) and f (ICC 0.606). Bland–Altman plots revealed no significant bias.

Conclusion: Administration of GBCM seems to have a stronger effect on D* and f values than on D values. This should be considered when applying IVIM in clinical practice.

Purpose: To compare the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo T2WI with DLIR for evaluating pancreatic protocol.

Methods: This retrospective study included 42 patients (mean age, 70.2 years) with pancreatic cancer who underwent gadoxetic acid-enhanced MRI. Three fat-suppressed T2WI, including conventional fast-spin echo with 6 mm thickness (FSE 6 mm), single-shot fast-spin echo with 6 mm and 3 mm thickness (SSFSE 6 mm and SSFSE 3 mm), were acquired for each patient. For quantitative analysis, the SNRs of the upper abdominal organs were calculated between images with and without DLIR. The pancreas-to-lesion contrast on DLIR images was also calculated. For qualitative analysis, two abdominal radiologists independently scored the image quality on a 5-point scale in the FSE 6 mm, SSFSE 6 mm, and SSFSE 3 mm with DLIR.

Results: The SNRs significantly improved among the three T2-weighted images with DLIR compared to those without DLIR in all patients (P < 0.001). The pancreas-to-lesion contrast of SSFSE 3 mm was higher than those of the FSE 6 mm (P < 0.001) and tended to be higher than SSFSE 6 mm (P = 0.07). SSFSE 3 mm had the highest image qualities regarding pancreas edge sharpness, pancreatic duct clarity, and overall image quality, followed by SSFSE 6 mm and FSE 6 mm (P < 0.0001).

Conclusion: SSFSE 3 mm with DLIR demonstrated significant improvements in SNRs of the pancreas, pancreas-to-lesion contrast, and image quality more efficiently than did SSFSE 6 mm and FSE 6 mm. Thin-slice fat-suppressed single-shot T2WI with DLIR can be easily implemented for pancreatic MR protocol.

Purpose: Voxel-based morphometry (VBM) is widely used to investigate white matter (WM) atrophy in patients with progressive supranuclear palsy (PSP). In contrast to high-resolution 3D T1-weighted imaging such as magnetization-prepared rapid acquisition with gradient echo (MPRAGE) sequences, the utility of other 3D sequences has not been sufficiently evaluated. This study aimed to assess the feasibility of using a 3D fast low-angle shot sequence captured as a localizer image (L3DFLASH) for VBM analysis of WM atrophy patterns in patients with PSP.

Methods: This retrospective study included 12 patients with pathologically or clinically confirmed PSP, and 18 age- and sex-matched healthy controls scanned with both L3DFLASH and MPRAGE sequences. Image processing was conducted with the Computational Anatomy Toolbox 12 in statistical parametric mapping 12. In addition to the atrophic WM pattern of PSP on VBM, we assessed the WM volume agreement between the two sequences using simple linear regression and Bland–Altman plots.

Results: Despite the slightly larger clusters on MPRAGE, VBM using both sequences showed similar characteristics of PSP-related WM atrophy, including in the midbrain, pons, thalamus, and precentral gyrus. In contrast, VBM showed gray matter (GM) atrophy of the precuneus and right superior parietal lobule exclusively on L3DFLASH. Unlike the measured values of total intracranial volume, GM, and cerebrospinal fluid on MPRAGE, the value of WM was larger on L3DFLASH. In contrast to the total intracranial volume, brainstem, and frontal and occipital lobes, the correlation with WM volume in other regions was relatively low. However, the Bland–Altman plots demonstrated strong agreement, with over 90% of the values falling within the agreement limits.

Conclusion: Both MPRAGE and L3DFLASH are useful for detecting PSP-related WM atrophy using VBM.

Purpose: We developed new deep learning-based hierarchical brain segmentation (DLHBS) method that can segment T1-weighted MR images (T1WI) into 107 brain subregions and calculate the volume of each subregion. This study aimed to evaluate the repeatability and reproducibility of volume estimation using DLHBS and compare them with those of representative brain segmentation tools such as statistical parametric mapping (SPM) and FreeSurfer (FS).

Methods: Hierarchical segmentation using multiple deep learning models was employed to segment brain subregions within a clinically feasible processing time. The T1WI and brain mask pairs in 486 subjects were used as training data for training of the deep learning segmentation models. Training data were generated using a multi-atlas registration-based method. The high quality of training data was confirmed through visual evaluation and manual correction by neuroradiologists. The brain 3D-T1WI scan–rescan data of the 11 healthy subjects were obtained using three MRI scanners for evaluating the repeatability and reproducibility. The volumes of the eight ROIs—including gray matter, white matter, cerebrospinal fluid, hippocampus, orbital gyrus, cerebellum posterior lobe, putamen, and thalamus—obtained using DLHBS, SPM 12 with default settings, and FS with the “recon-all” pipeline. These volumes were then used for evaluation of repeatability and reproducibility.

Results: In the volume measurements, the bilateral thalamus showed higher repeatability with DLHBS compared with SPM. Furthermore, DLHBS demonstrated higher repeatability than FS in across all eight ROIs. Additionally, higher reproducibility was observed with DLHBS in both hemispheres of six ROIs when compared with SPM and in five ROIs compared with FS. The lower repeatability and reproducibility in DLHBS were not observed in any comparisons.

Conclusion: Our results showed that the best performance in both repeatability and reproducibility was found in DLHBS compared with SPM and FS.

Purpose: We aimed to evaluate the quality of various 3D T₁-weighted images (T₁WIs) of the stent lumen using a carotid stent phantom and determine the suitable T₁WI sequence for visualization of the stent lumen after carotid artery stenting.

Methods: The carotid stent phantom consisted of polypropylene tubes that mimicked common carotid arteries with and without stenting. On 1.5T and 3.0T MRI scanners, transverse T₁WIs of the carotid stent phantom were obtained using 3D turbo spin-echo (TSE), 3D fast field-echo (3D-FFE), and 3D turbo field echo volumetric interpolated breath-hold examination (VIBE) under clinical conditions. The signal intensity ratio (SIR) was determined using the mean signal intensity of the stent lumen (SI_stent) divided by the lumen without a stent in each T₁WI. The SNR of the stent lumen (SNR_stent) was calculated from SI_stent divided by the standard deviation of the uniform region near the stent lumen.

Results: The 3D-FFE and VIBE had higher SNR_stent than other T₁WIs and clearly visualized the stent lumen. The 3D-TSE had the lowest SIR and SNR_stent, preventing stent lumen visualization.

Conclusion: T₁WIs obtained using 3D-FFE and VIBE allows stent lumen visualization.