Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS.

PURPOSE: To develop and evaluate methods for (1) reconstructing 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) time-series images using a low-rank subspace method, which enables accurate and rapid T1 and T2 mapping, and (2) improving the fidelity of subspace QALAS by combining scan-specific deep-learning-based reconstruction and subspace modeling. THEORY AND METHODS: A low-rank subspace method for 3D-QALAS (i.e., subspace QALAS) and zero-shot deep-learning subspace method (i.e., Zero-DeepSub) were proposed for rapid and high fidelity T1 and T2 mapping and time-resolved imaging using 3D-QALAS. Using an ISMRM/NIST system phantom, the accuracy and reproducibility of the T1 and T2 maps estimated using the proposed methods were evaluated by comparing them with reference techniques. The reconstruction performance of the proposed subspace QALAS using Zero-DeepSub was evaluated in vivo and compared with conventional QALAS at high reduction factors of up to nine-fold. RESULTS: Phantom experiments showed that subspace QALAS had good linearity with respect to the reference methods while reducing biases and improving precision compared to conventional QALAS, especially for T2 maps. Moreover, in vivo results demonstrated that subspace QALAS had better g-factor maps and could reduce voxel blurring, noise, and artifacts compared to conventional QALAS and showed robust performance at up to nine-fold acceleration with Zero-DeepSub, which enabled whole-brain T1, T2, and PD mapping at 1 mm isotropic resolution within 2 min of scan time. CONCLUSION: The proposed subspace QALAS along with Zero-DeepSub enabled high fidelity and rapid whole-brain multiparametric quantification and time-resolved imaging.

Cross-vendor multiparametric mapping of the human brain using 3D-QALAS: A multicenter and multivendor study.

PURPOSE: To evaluate a vendor-agnostic multiparametric mapping scheme based on 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) for whole-brain T1, T2, and proton density (PD) mapping. METHODS: This prospective, multi-institutional study was conducted between September 2021 and February 2022 using five different 3T systems from four prominent MRI vendors. The accuracy of this technique was evaluated using a standardized MRI system phantom. Intra-scanner repeatability and inter-vendor reproducibility of T1, T2, and PD values were evaluated in 10 healthy volunteers (6 men; mean age ± SD, 28.0 ± 5.6 y) who underwent scan-rescan sessions on each scanner (total scans = 100). To evaluate the feasibility of 3D-QALAS, nine patients with multiple sclerosis (nine women; mean age ± SD, 48.2 ± 11.5 y) underwent imaging examination on two 3T MRI systems from different manufacturers. RESULTS: Quantitative maps obtained with 3D-QALAS showed high linearity (R2 = 0.998 and 0.998 for T1 and T2, respectively) with respect to reference measurements. The mean intra-scanner coefficients of variation for each scanner and structure ranged from 0.4% to 2.6%. The mean structure-wise test-retest repeatabilities were 1.6%, 1.1%, and 0.7% for T1, T2, and PD, respectively. Overall, high inter-vendor reproducibility was observed for all parameter maps and all structure measurements, including white matter lesions in patients with multiple sclerosis. CONCLUSION: The vendor-agnostic multiparametric mapping technique 3D-QALAS provided reproducible measurements of T1, T2, and PD for human tissues within a typical physiological range using 3T scanners from four different MRI manufacturers.

Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity.

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Development of a scoring system to predict local recurrence in brain metastases following complete resection and observation.

PURPOSE: Postoperative stereotactic radiosurgery to the resection cavity in patients with brain metastases is guideline-recommended therapy. However, Japanese Clinical Oncology Group 0504 study showed that postoperative observation could be a therapeutic option in patients with completed resected brain metastases. We hereby investigated the incidence and risk factors for local recurrence after complete resection without immediate radiotherapy and developed a scoring system for its prediction. METHODS: We included 53 patients with 54 brain metastases, who underwent complete resection between January 2016 and December 2021. We identified risk factors for local recurrence and developed a scoring system to predict it using the extracted risk factors, by assigning one point to each risk factor and calculating the total scores for each patient. We evaluated the correlation between the prognostic score and time to local recurrence. RESULTS: Local recurrence occurred in 37 of 54 tumors (68.5%), with a median follow-up duration of 21.0 months. The median time to local recurrence was 5.1 months. Univariate and multivariate analyses revealed that non-lung adenocarcinoma, infratentorial tumors, and no postoperative systemic therapy were identified as risk factors for local recurrence (non-lung adenocarcinoma, p = 0.035; infratentorial tumors, p = 0.044; and no postoperative systemic therapy, p = 0.0069). A score ≥ 2 showed a median time to local recurrence of 2.1 months, starkly contrasting with 30.8 months for a score ≤ 1 (p = 0.0002). CONCLUSIONS: Non-lung adenocarcinoma, infratentorial tumors, and no postoperative systemic therapy were risk factors for local recurrence. Our scoring system can predict local recurrence, thus potentially aiding treatment decisions.

Simultaneous relaxometry and morphometry of human brain structures with 3D magnetic resonance fingerprinting: a multicenter, multiplatform, multifield-strength study.

Relaxation times and morphological information are fundamental magnetic resonance imaging-derived metrics of the human brain that reflect the status of the underlying tissue. Magnetic resonance fingerprinting (MRF) enables simultaneous acquisition of T1 and T2 maps inherently aligned to the anatomy, allowing whole-brain relaxometry and morphometry in a single scan. In this study, we revealed the feasibility of 3D MRF for simultaneous brain structure-wise morphometry and relaxometry. Comprehensive test-retest scan analyses using five 1.5-T and three 3.0-T systems from a single vendor including different scanner types across 3 institutions demonstrated that 3D MRF-derived morphological information and relaxation times are highly repeatable at both 1.5 T and 3.0 T. Regional cortical thickness and subcortical volume values showed high agreement and low bias across different field strengths. The ability to acquire a set of regional T1, T2, thickness, and volume measurements of neuroanatomical structures with high repeatability and reproducibility facilitates the ability of longitudinal multicenter imaging studies to quantitatively monitor changes associated with underlying pathologies, disease progression, and treatments.

Remnant gastritis in gastric cancer patients causes loss of muscle mass 6 months after gastrectomy: a retrospective cohort study of Helicobacter pylori infection.

PURPOSE: In this study, we assessed the relationship between remnant gastritis and muscle mass loss and then investigated the potential relationship between Helicobacter pylori (HP) infection and remnant gastritis and muscle loss. METHODS: We reviewed the medical records of 463 patients who underwent distal gastrectomy between January 2017 and March 2020. Of these patients, 100 with pStage I after laparoscopic surgery were included in this analysis. RESULTS: A multivariate analysis showed that the total Residue, Gastritis, Bile (RGB) classification score, which indicates the degree of gastritis, was significantly associated with the rate of change (rate of decrease) in the psoas muscle area (PMA) during the first 6 months after surgery (p = 0.014). Propensity score matching was performed according to HP infection, and the rate of change in the PMA and the degree of remnant gastritis in 56 patients were compared. Neither was significantly associated with HP infection. CONCLUSIONS: Remnant gastritis did contribute to psoas muscle mass loss during the initial 6 months after gastrectomy, and HP infection was not significantly associated with either remnant gastritis or psoas muscle mass loss. Nevertheless, the potential for HP eradication to prevent muscle loss and improve the survival prognosis for gastrectomy patients merits further research.

Recent trends in AI applications for pelvic MRI: a comprehensive review.

Magnetic resonance imaging (MRI) is an essential tool for evaluating pelvic disorders affecting the prostate, bladder, uterus, ovaries, and/or rectum. Since the diagnostic pathway of pelvic MRI can involve various complex procedures depending on the affected organ, the Reporting and Data System (RADS) is used to standardize image acquisition and interpretation. Artificial intelligence (AI), which encompasses machine learning and deep learning algorithms, has been integrated into both pelvic MRI and the RADS, particularly for prostate MRI. This review outlines recent developments in the use of AI in various stages of the pelvic MRI diagnostic pathway, including image acquisition, image reconstruction, organ and lesion segmentation, lesion detection and classification, and risk stratification, with special emphasis on recent trends in multi-center studies, which can help to improve the generalizability of AI.

MR Fingerprinting for Liver Tissue Characterization: A Histopathologic Correlation Study.

Background Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies. Materials and Methods This prospective study included participants with diffuse liver disease undergoing MRI from July 2021 to January 2022. Participants underwent two-dimensional single-section liver MRF and separate reference quantitative MRI. Linear regression, Bland-Altman plots, and coefficients of variation were used to assess the bias and repeatability of liver MRF measurements. For participants undergoing liver biopsy, the association between mapping and histologic grading was evaluated by using the Spearman correlation coefficient. Results Fifty-six participants (mean age, 59 years ± 15 [SD]; 32 women) were included to compare mapping techniques and 23 participants were evaluated with liver biopsy (mean age, 52.7 years ± 12.7; 14 women). The linearity of MRF with reference measurements in participants with diffuse liver disease (R2 value) for T1, T2, T2*, and PDFF maps was 0.86, 0.88, 0.54, and 0.99, respectively. The overall coefficients of variation for repeatability in the liver were 3.2%, 5.5%, 7.1%, and 4.6% for T1, T2, T2*, and PDFF maps, respectively. MRF-derived metrics showed high diagnostic performance in differentiating moderate or severe changes from mild or no changes (area under the receiver operating characteristic curve for fibrosis, inflammation, steatosis, and siderosis: 0.62 [95% CI: 0.52, 0.62], 0.92 [95% CI: 0.88, 0.92], 0.97 [95% CI: 0.96, 0.97], and 0.74 [95% CI: 0.57, 0.74], respectively). Conclusion Liver MR fingerprinting provided repeatable T1, T2, T2*, and proton density fat fraction maps in high agreement with reference quantitative mapping and may correlate with pathologic grades in participants with diffuse liver disease. © RSNA, 2022 Online supplemental material is available for this article.

Feasibility of Quantitative MRI Using 3D-QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast.

BACKGROUND: Two-dimensional synthetic MRI of the breast has limited spatial coverage. Three-dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast. PURPOSE: To evaluate the feasibility of 3D synthetic MRI using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki-67 expression in IDC. STUDY TYPE: Prospective observational study. POPULATION: A total of 33 females with IDC of the breast (mean, 52.3 years). FIELD STRENGTH/SEQUENCE: A 3-T, 3D-QALAS gradient-echo and fat-suppressed T1-weighted 3D fast spoiled gradient-echo sequences. ASSESSMENT: Two radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1-weighted images acquired from 3D-QALAS. The mean T1 and T2 were measured for each IDC. STATISTICAL TESTS: Intraclass correlation coefficient for assessing interobserver agreement. Mann-Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant. RESULTS: The interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR-positive and HR-negative lesions, while the mean T2 value differed between HR-positive and HR-negative lesions, between the triple-negative and HR-positive or HER2-positive lesions, and between the Ki-67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR-negative IDC than in HR-positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple-negative status, and Ki-67 level. DATA CONCLUSION: 3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.

Time required for indocyanine green fluorescence emission for evaluating bowel perfusion in left-sided colon and rectal cancer surgery.

BACKGROUND: Indocyanine green fluorescence imaging (ICG-FI) has been reported to be useful in reducing the incidence of anastomotic leakage (AL) in colectomy. This study aimed to investigate the correlation between the required time for ICG fluorescence emission and AL in left-sided colon and rectal cancer surgery using the double-stapling technique (DST) anastomosis. METHODS: This retrospective study included 217 patients with colorectal cancer who underwent left-sided colon and rectal surgery using ICG-FI-based perfusion assessment at our department between November 2018 and July 2022. We recorded the time required to achieve maximum fluorescence emission after ICG systemic injection and assessed its correlation with the occurrence of AL. RESULTS: Among 217 patients, AL occurred in 21 patients (9.7%). The median time from ICG administration to maximum fluorescence emission was 32 s (range 25-58 s) in the AL group and 28 s (range 10-45 s) in the non-AL group (p < 0.001). The cut-off value for the presence of AL obtained from the ROC curve was 31 s. In 58 patients with a required time for ICG fluorescence of 31 s or longer, the following risk factors for AL were identified: low preoperative albumin [3.4 mg/dl (range 2.6-4.4) vs. 3.9 mg/dl (range 2.6-4.9), p = 0.016], absence of preoperative mechanical bowel preparation (53.8% vs. 91.1%, p = 0.005), obstructive tumor (61.5% vs. 17.8%, p = 0.004), and larger tumor diameter [65 mm (range 40-90) vs. 35 mm (range 4.0-100), p < 0.001]. CONCLUSION: The time required for ICG fluorescence emission was associated with AL.

Prolonged infective SARS-CoV-2 omicron variant shedding in a patient with diffuse large B cell lymphoma successfully cleared after three courses of remdesivir.

We report a case of prolonged shedding of the infective SARS-CoV-2 omicron variant BA.1.1.2 in a 79-year-old male patient with diffuse large B-cell lymphoma, after receiving chemotherapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP). The patient was admitted to our hospital in late March 2022 for the sixth course of R-CHOP chemotherapy. Initially, the patient tested negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using an in-hospital loop-mediated amplification assay with a nasopharyngeal swab, both on the day of admission and three days later. However, the patient developed fever and was diagnosed with coronavirus disease (COVID-19) six days after admission and was suspected to have contracted the infection in the ward. Viral shedding continued for more than three months, with confirmed viral infectivity. As compared to the original Wuhan-Hu-1/2019 strain, amino acid substitutions including S36 N in non-structural protein (NSP)2, S148P, S1265del and L1266I in NSP3, G105D in NSP4, G496S, A831V, or V987F in spike protein, and I45T in open-reading frame (ORF)9b were randomly detected in isolated viruses. Although the patient had received two doses of the BNT162b2 vaccine approximately six months earlier and the third dose on day 127 after the infection, both serum anti-spike and anti-nuclear protein IgG and IgM tests were negative at day 92, 114, and 149 after the infection. The patient finally cleared the virus after the third course of remdesivir and did not have further recurrence.

Relative dose intensity and 1-year psoas muscle index reduction rate as prognostic factors in gastric cancer patients with postoperative adjuvant chemotherapy.

BACKGROUND: Higher relative dose intensity (RDI) of chemotherapy improves the clinical outcomes of various cancers. The psoas muscle index (PMI) is related to sarcopenia, and patients with low PMI have worse prognoses. However, few studies have demonstrated its clinical relevance in gastric cancer. METHODS: This retrospective study included 188 stage II/III gastric cancer patients who had undergone curative gastrectomy between January 2013 and March 2017, 124 of whom had received postoperative S-1 adjuvant chemotherapy. RESULTS: Per receiver operating characteristic analysis, patients were divided into high and low RDI groups, between which relapse-free survival differed marginally significantly and disease-specific survival differed significantly. In patients who received adjuvant chemotherapy, multivariate analysis found that high RDI and low PMI reduction rate 1 year after surgery were significantly associated with better relapse-free survival. Low RDI can be predicted by a combination of low preoperative PMI and non-distal gastrectomy, whereas high PMI reduction rate at 1 year can be affected by non-distal gastrectomy. CONCLUSION: High RDI with preserved psoas muscle up to 1 year after gastrectomy may be associated with prognoses in gastric cancer requiring postoperative adjuvant chemotherapy. Since RDI and PMI reduction rate can be predicted preoperatively, respectively, interventional consideration is possible for optimal adjuvant therapy in gastric cancer.

Analysis of synthetic magnetic resonance images by multi-channel segmentation increases accuracy of volumetry in the putamen and decreases mis-segmentation in the dural sinuses.

BACKGROUND: Voxel-based morphometry (VBM) using magnetic resonance imaging (MR) has been used to estimate cortical atrophy associated with various diseases. However, there are mis-segmentations of segmented gray matter image in VBM. PURPOSE: To study a twofold evaluation of single- and multi-channel segmentation using synthetic MR images: (1) mis-segmentation of segmented gray matter images in transverse and cavernous sinuses; and (2) accuracy and repeatability of segmented gray matter images. MATERIAL AND METHODS: A total of 13 healthy individuals were scanned with 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence on a 1.5-T scanner. Three of the 13 healthy participants were scanned five consecutive times for evaluation of repeatability. We used SyMRI software to create images with three contrasts: T1-weighted (T1W), T2-weighted (T2W), and proton density-weighted (PDW) images. Manual regions of interest (ROI) on T1W imaging were individually set as the gold standard in the transverse sinus, cavernous sinus, and putamen. Single-channel (T1W) and multi-channel (T1W + T2W, T1W + PDW, and T1W + T2W + PDW imaging) segmentations were performed with statistical parametric mapping 12 software. RESULTS: We found that mis-segmentations in both the transverse and cavernous sinuses were large in single-channel segmentation compared with multi-channel segmentations. Furthermore, the accuracy of segmented gray matter images in the putamen was high in both multi-channel T1W + PDW and T1W + T2W + PDW segmentations compared with other segmentations. Finally, the highest repeatability of left putamen volumetry was found with multi-channel segmentation T1WI + PDWI. CONCLUSION: Multi-channel segmentation with T1WI + PDWI provides good results for VBM compared with single-channel and other multi-channel segmentations.

New trend in artificial intelligence-based assistive technology for thoracic imaging.

Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggered by improvements in computing power, algorithm development, and the use of big data. In recent years, the application and development of AI technology in the medical field have intensified internationally. There is no doubt that AI will be used in clinical practice to assist in diagnostic imaging in the future. In qualitative diagnosis, it is desirable to develop an explainable AI that at least represents the basis of the diagnostic process. However, it must be kept in mind that AI is a physician-assistant system, and the final decision should be made by the physician while understanding the limitations of AI. The aim of this article is to review the application of AI technology in diagnostic imaging from PubMed database while particularly focusing on diagnostic imaging in thorax such as lesion detection and qualitative diagnosis in order to help radiologists and clinicians to become more familiar with AI in thorax.

Clinical applications of artificial intelligence in liver imaging.

This review outlines the current status and challenges of the clinical applications of artificial intelligence in liver imaging using computed tomography or magnetic resonance imaging based on a topic analysis of PubMed search results using latent Dirichlet allocation. LDA revealed that "segmentation," "hepatocellular carcinoma and radiomics," "metastasis," "fibrosis," and "reconstruction" were current main topic keywords. Automatic liver segmentation technology using deep learning is beginning to assume new clinical significance as part of whole-body composition analysis. It has also been applied to the screening of large populations and the acquisition of training data for machine learning models and has resulted in the development of imaging biomarkers that have a significant impact on important clinical issues, such as the estimation of liver fibrosis, recurrence, and prognosis of malignant tumors. Deep learning reconstruction is expanding as a new technological clinical application of artificial intelligence and has shown results in reducing contrast and radiation doses. However, there is much missing evidence, such as external validation of machine learning models and the evaluation of the diagnostic performance of specific diseases using deep learning reconstruction, suggesting that the clinical application of these technologies is still in development.

Rigid real-time prospective motion-corrected three-dimensional multiparametric mapping of the human brain.

PURPOSE: To develop a rigid real-time prospective motion-corrected multiparametric mapping technique and to test the performance of quantitative estimates. METHODS: Motion tracking and correction were performed by integrating single-shot spiral navigators into a multiparametric imaging technique, three-dimensional quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). The spiral navigator was optimized, and quantitative measurements were validated using a standard system phantom. The effect of motion correction on whole-brain T1 and T2 mapping under different types of head motion during the scan was evaluated in 10 healthy volunteers. Finally, six patients with Parkinson's disease, which is known to be associated with a high prevalence of motion artifacts, were scanned to evaluate the effectiveness of our method in the real world. RESULTS: The phantom study demonstrated that the proposed motion correction method did not introduce quantitative bias. Improved parametric map quality and repeatability were shown in volunteer experiments with both in-plane and through-plane motions, comparable to the no-motion ground truth. In real-life validation in patients, the approach showed improved parametric map quality compared to images obtained without motion correction. CONCLUSIONS: Real-time prospective motion-corrected multiparametric relaxometry based on 3D-QALAS provided robust and repeatable whole-brain multiparametric mapping.

Multimodal magnetic resonance imaging quantification of gray matter alterations in relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorder.

Herein, we combined neurite orientation dispersion and density imaging (NODDI) and synthetic magnetic resonance imaging (SyMRI) to evaluate the spatial distribution and extent of gray matter (GM) microstructural alterations in patients with relapsing-remitting multiple sclerosis (RRMS) and neuromyelitis optica spectrum disorder (NMOSD). The NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) and SyMRI (myelin volume fraction [MVF]) measures were compared between age- and sex-matched groups of 30 patients with RRMS (6 males and 24 females; mean age, 51.43 ± 8.02 years), 18 patients with anti-aquaporin-4 antibody-positive NMOSD (2 males and 16 females; mean age, 52.67 ± 16.07 years), and 19 healthy controls (6 males and 13 females; mean age, 51.47 ± 9.25 years) using GM-based spatial statistical analysis. Patients with RRMS showed reduced NDI and MVF and increased ODI and ISOVF, predominantly in the limbic and paralimbic regions, when compared with healthy controls, while only increases in ODI and ISOVF were observed when compared with NMOSD. Compared to NDI and MVF, the changes in ODI and ISOVF were observed more widely, including in the cerebellar cortex. These abnormalities were associated with disease progression and disability. In contrast, patients with NMOSD only showed reduced NDI mainly in the cerebellar, limbic, and paralimbic cortices when compared with healthy controls and patients with RRMS. Taken together, our study supports the notion that GM pathologies in RRMS are distinct from those of NMOSD. However, owing to the limitations of the study, the results should be cautiously interpreted.

Radiomics with 3-dimensional magnetic resonance fingerprinting: influence of dictionary design on repeatability and reproducibility of radiomic features.

OBJECTIVES: We aimed to investigate the influence of magnetic resonance fingerprinting (MRF) dictionary design on radiomic features using in vivo human brain scans. METHODS: Scan-rescans of three-dimensional MRF and conventional T1-weighted imaging were performed on 21 healthy volunteers (9 males and 12 females; mean age, 41.3 ± 14.6 years; age range, 22-72 years). Five patients with multiple sclerosis (3 males and 2 females; mean age, 41.2 ± 7.3 years; age range, 32-53 years) were also included. MRF data were reconstructed using various dictionaries with different step sizes. First- and second-order radiomic features were extracted from each dataset. Intra-dictionary repeatability and inter-dictionary reproducibility were evaluated using intraclass correlation coefficients (ICCs). Features with ICCs > 0.90 were considered acceptable. Relative changes were calculated to assess inter-dictionary biases. RESULTS: The overall scan-rescan ICCs of MRF-based radiomics ranged from 0.86 to 0.95, depending on dictionary step size. No significant differences were observed in the overall scan-rescan repeatability of MRF-based radiomic features and conventional T1-weighted imaging (p = 1.00). Intra-dictionary repeatability was insensitive to dictionary step size differences. MRF-based radiomic features varied among dictionaries (overall ICC for inter-dictionary reproducibility, 0.62-0.99), especially when step sizes were large. First-order and gray level co-occurrence matrix features were the most reproducible feature classes among different step size dictionaries. T1 map-derived radiomic features provided higher repeatability and reproducibility among dictionaries than those obtained with T2 maps. CONCLUSION: MRF-based radiomic features are highly repeatable in various dictionary step sizes. Caution is warranted when performing MRF-based radiomics using datasets containing maps generated from different dictionaries. KEY POINTS: • MRF-based radiomic features are highly repeatable in various dictionary step sizes. • Use of different MRF dictionaries may result in variable radiomic features, even when the same MRF acquisition data are used. • Caution is needed when performing radiomic analysis using data reconstructed from different dictionaries.

Multiple sclerosis plaques may undergo continuous myelin degradation: a cross-sectional study with myelin and axon-related quantitative magnetic resonance imaging metrics.

PURPOSE: We hypothesize that myelin is more susceptible to damage over time than axons. We investigated the association between the estimated duration from the onset of multiple sclerosis (MS) plaques and myelin- and axon-related quantitative synthetic magnetic resonance imaging (SyMRI) and neurite orientation dispersion and density imaging (NODDI) metrics. METHODS: We analyzed 31 patients with MS with 73 newly appeared plaques. Simple linear regression analysis was performed to assess the association between the estimated duration from the onset of plaques and quantitative MRI metrics. These metrics included the myelin volume fraction (MVF), axon volume fraction, and g-ratio in plaque and normal-appearing white matter. RESULTS: MS plaques with a longer estimated duration from onset were significantly correlated with a lower MVF (slope = - 0.0070, R2 = 0.0970), higher g-ratio (slope = 0.0078, R2 = 0.0842) (all P values < 0.05). CONCLUSION: These results suggested that myelin in plaques undergoes continuous damage, more so than axons. Myelin imaging with SyMRI and NODDI may be useful for the quantitative assessment of temporal changes in MS plaques.

Impact of the coronavirus disease 2019 pandemic on first-visit patients with oesophageal cancer in the first infection wave in Saitama prefecture near Tokyo: a single-centre retrospective study.

BACKGROUND: Although the novel coronavirus disease 2019 did not lead to a serious medical collapse in Japan, its impact on treatment of oesophageal cancer has rarely been investigated. This study aimed to investigate the influence of the pandemic on consultation status and initial treatment in patients with primary oesophageal cancer. METHODS: A retrospective study was conducted among 546 patients with oesophageal cancer who visited our hospital from April 2018 to March 2021. Pre-pandemic and pandemic data were compared with the clinical features, oncological factors and initial treatment as outcome measures. RESULTS: Diagnoses of oesophageal cancer decreased during the early phase of the pandemic from April to June (P = 0.048); however, there was no significant difference between the pre-pandemic and pandemic periods throughout the year. The proportion of patients diagnosed with distant metastases significantly increased during the pandemic (P = 0.026), while the proportion of those who underwent initial radical treatment decreased (P = 0.044). The rate of definitive chemoradiotherapy decreased by 58.6% relative to pre-pandemic levels (P = 0.001). CONCLUSIONS: Patients may have refrained from consultation during the early phase of the coronavirus disease 2019 pandemic. The resultant delay in diagnosis may have led to an increase in the number of patients who were not indicated for radical treatment, as well as a decrease in the number of those who underwent definitive chemoradiotherapy. Our findings highlight the need to maintain the health care system and raise awareness on the importance of consultation.