Faster acquisition of magnetic resonance imaging sequences of the knee via deep learning reconstruction: a volunteer study

AIM

To evaluate whether deep learning reconstruction (DLR) can accelerate the acquisition of magnetic resonance imaging (MRI) sequences of the knee for clinical use.

MATERIALS AND METHODS

Using a 1.5-T MRI scanner, sagittal fat-suppressed T2-weighted imaging (fs-T2WI), coronal proton density-weighted imaging (PDWI), and coronal T1-weighted imaging (T1WI) were performed. DLR was applied to images with a number of signal averages (NSA) of 1 to obtain 1DLR images. Then 1NSA, 1DLR, and 4NSA images were compared subjectively, and by noise (standard deviation of intra-articular water or medial meniscus) and contrast-to-noise ratio between two anatomical structures or between an anatomical structure and intra-articular water.

RESULTS

Twenty-seven healthy volunteers (age: 40.6 ± 11.9 years) were enrolled. Three 1DLR image sequences were obtained within 200 s (approximately 12 minutes for 4NSA image). According to objective evaluations, PDWI 1DLR images showed the smallest noise and significantly higher contrast than 1NSA and 4NSA images. For fs-T2WI, smaller noise and higher contrast were observed in the order of 4NSA, 1DLR, and 1NSA images. According to the subjective analysis, structure visibility, image noise, and overall image quality were significantly better for PDWI 1DLR than 1NSA images; moreover, the visibility of the meniscus and bone, image noise, and overall image quality were significantly better for 1DLR than 4NSA images. Fs-T2WI and T1WI 1DLR images showed no difference between 1DLR and 4NSA images.

CONCLUSION

Compared to PDWI 4NSA images, PDWI 1DLR images were of higher quality, while the quality of fs-T2WI and T1WI 1DLR images was similar to that of 4NSA images.

Prognostic impact of MRI-derived feature tracking myocardial strain in patients with non-ischaemic dilated cardiomyopathy: a systematic review and meta-analysis

AIM

To evaluate the clinical utility of feature tracking (FT)-derived myocardial strain in patients with non-ischaemic dilated cardiomyopathy (NIDCM).

MATERIALS AND METHODS

Electronic database searches of PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE were performed. Studies on NIDCM were divided into categories according to left ventricular ejection fraction (LVEF; <30%, 30-40%, >40%), and correlations between strains and prevalence of late gadolinium enhancement (LGE) were evaluated by weighted correlation coefficients. Global longitudinal strain (GLS) hazard ratios were also integrated for prediction of future adverse events.

RESULTS

The present meta-analysis analysed data from 5,767 patients with NIDCM from 30 eligible studies. GLS and global circumferential strain significantly differed across the three LVEF categories (all p<0.05); however, global radial strain did not. Only GLS showed a strong correlation with the prevalence of LGE (Spearman's correlation coefficient = 0.61). The pooled HR of GLS for predicting adverse events was 1.15 (95% confidence interval [CI]: 1.07-1.23, p<0.001).

CONCLUSION

In this meta-analysis, FT-derived GLS was strongly correlated with myocardial fibrosis and was an important predictor of future adverse events. These results suggest that FT-derived GLS may be useful in the pathological evaluation and risk stratification of NIDCM.

The automatic diagnosis artificial intelligence system for preoperative magnetic resonance imaging of uterine sarcoma

OBJECTIVE

Magnetic resonance imaging (MRI) is efficient for the diagnosis of preoperative uterine sarcoma; however, misdiagnoses may occur. In this study, we developed a new artificial intelligence (AI) system to overcome the limitations of requiring specialists to manually process datasets and a large amount of computer resources.

METHODS

The AI system comprises a tumor image filter, which extracts MRI slices containing tumors, and sarcoma evaluator, which diagnoses uterine sarcomas. We used 15 types of MRI patient sequences to train deep neural network (DNN) models used by tumor filter and sarcoma evaluator with 8 cross-validation sets. We implemented tumor filter and sarcoma evaluator using ensemble prediction technique with 9 DNN models. Ten tumor filters and sarcoma evaluator sets were developed to evaluate fluctuation accuracy. Finally, AutoDiag-AI was used to evaluate the new validation dataset, including 8 cases of sarcomas and 24 leiomyomas.

RESULTS

Tumor image filter and sarcoma evaluator accuracies were 92.68% and 90.50%, respectively. AutoDiag-AI with the original dataset accuracy was 89.32%, with 90.47% sensitivity and 88.95% specificity, whereas AutoDiag-AI with the new validation dataset accuracy was 92.44%, with 92.25% sensitivity and 92.50% specificity.

CONCLUSION

Our newly established AI system automatically extracts tumor sites from MRI images and diagnoses them as uterine sarcomas without human intervention. Its accuracy is comparable to that of a radiologist. With further validation, the system could be applied for diagnosis of other diseases. Further improvement of the system's accuracy may enable its clinical application in the future.

Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction

The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-DLR) is superior to conventional deep learning reconstruction (DLR) with respect to interobserver agreement in the evaluation of neuroforaminal stenosis using 1.5T cervical spine MRI. This retrospective study included 39 patients who underwent 1.5T cervical spine MRI. T2-weighted sagittal images were reconstructed with SR-DLR and DLR. Three blinded radiologists independently evaluated the images in terms of the degree of neuroforaminal stenosis, depictions of the vertebrae, spinal cord and neural foramina, sharpness, noise, artefacts and diagnostic acceptability. In quantitative image analyses, a fourth radiologist evaluated the signal-to-noise ratio (SNR) by placing a circular or ovoid region of interest on the spinal cord, and the edge slope based on a linear region of interest placed across the surface of the spinal cord. Interobserver agreement in the evaluations of neuroforaminal stenosis using SR-DLR and DLR was 0.422-0.571 and 0.410-0.542, respectively. The kappa values between reader 1 vs. reader 2 and reader 2 vs. reader 3 significantly differed. Two of the three readers rated depictions of the spinal cord, sharpness, and diagnostic acceptability as significantly better with SR-DLR than with DLR. Both SNR and edge slope (/mm) were also significantly better with SR-DLR (12.9 and 6031, respectively) than with DLR (11.5 and 3741, respectively) (p < 0.001 for both). In conclusion, compared to DLR, SR-DLR improved interobserver agreement in the evaluations of neuroforaminal stenosis using 1.5T cervical spine MRI.

White and Gray Matter Abnormality in Burning Mouth Syndrome Evaluated with Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging

PURPOSE

Burning mouth syndrome (BMS) is defined by a burning sensation or pain in the tongue or other oral sites despite the presence of normal mucosa on inspection. Both psychiatric and neuroimaging investigations have examined BMS; however, there have been no analyses using the neurite orientation dispersion and density imaging (NODDI) model, which provides detailed information of intra- and extracellular microstructures. Therefore, we performed voxel-wise analyses using both NODDI and diffusion tensor imaging (DTI) models and compared the results to better comprehend the pathology of BMS.

METHODS

Fourteen patients with BMS and 11 age- and sex-matched healthy control subjects were prospectively scanned using a 3T-MRI machine using 2-shell diffusion imaging. Diffusion tensor metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], and radial diffusivity [RD]) and neurite orientation and dispersion index metrics (intracellular volume fraction [ICVF], isotropic volume fraction [ISO], and orientation dispersion index [ODI]) were retrieved from diffusion MRI data. These data were analyzed using tract-based spatial statistics (TBSS) and gray matter-based spatial statistics (GBSS).

RESULTS

TBSS analysis showed that patients with BMS had significantly higher FA and ICVF and lower MD and RD than the healthy control subjects (family-wise error [FWE] corrected P < 0.05). Changes in ICVF, MD, and RD were observed in widespread white matter areas. Fairly small areas with different FA were included. GBSS analysis showed that patients with BMS had significantly higher ISO and lower MD and RD than the healthy control subjects (FWE-corrected P < 0.05), mainly limited to the amygdala.

CONCLUSION

The increased ICVF in the BMS group may represent myelination and/or astrocytic hypertrophy, and microstructural changes in the amygdala in GBSS analysis indicate the emotional-affective profile of BMS.

Viewing the immune checkpoint VISTA: landscape and outcomes across cancers

BACKGROUND

Optimizing immune checkpoint inhibitor (ICI) therapy may require identification of co-targetable checkpoint pathways via immune profiling. Herein, we analyzed the transcriptomic expression and clinical correlates of V-domain immunoglobulin suppressor of T-cell activation (VISTA), a promising targetable checkpoint.

PATIENTS AND METHODS

RNA sequencing was carried out on 514 tissues reflecting diverse advanced/metastatic cancers. Expression of eight immune checkpoint markers [lymphocyte-activation gene 3 (LAG-3), tumor necrosis factor receptor superfamily 14 (TNFRSF14), programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), programmed death-ligand 2 (PD-L2), B- and T-lymphocyte attenuator (BTLA), T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), cytotoxic T-lymphocyte antigen 4 (CTLA-4)], in addition to VISTA, was analyzed, along with clinical outcomes.

RESULTS

High VISTA RNA expression was observed in 32% of tumors (66/514) and was the most common highly expressed checkpoint among the nine assessed. High VISTA expression was independently correlated with high BTLA, TIM-3, and TNFRSF14, and with a diagnosis of pancreatic, small intestine, and stomach cancer. VISTA transcript levels did not correlate with overall survival (OS) from metastatic/advanced disease in the pan-cancer cohort or with immunotherapy outcome (progression-free survival and OS from the start of ICI) in 217 ICI-treated patients. However, in ICI-treated pancreatic cancer patients (n = 16), median OS was significantly shorter (from immunotherapy initiation) for the high- versus not-high-VISTA groups (0.28 versus 1.21 years) (P = 0.047); in contrast, VISTA levels were not correlated with OS in 36 pancreatic cancer patients who did not receive ICI.

CONCLUSION

High VISTA expression correlates with high BTLA, TIM-3, and TNFRSF14 checkpoint-related molecules and with poorer post-immunotherapy survival in pancreatic cancer, consistent with prior literature indicating that VISTA is prominently expressed on CD68+ macrophages in pancreatic cancers and requiring validation in larger prospective studies. Immunomic analysis may be important for individualized precision immunotherapy.

Pth1r in Neural Crest Cells Regulates Nasal Cartilage Differentiation

Neural crest cells (NCC) arise from the dorsal margin of the neural plate border and comprise a unique cell population that migrates to and creates the craniofacial region. Although factors including Shh, Fgf8, and bone morphogenetic proteins have been shown to regulate these biological events, the role of parathyroid hormone 1 receptor (Pth1r) has been less studied. We generated an NCC-specific mouse model for Pth1r and researched gene expression, function, and interaction focusing on nasal cartilage framework and midfacial development. Wnt1-Cre;Pth1rfl/fl;Tomatofl/+ mice had perinatal lethality, but we observed short snout and jaws, tongue protrusion, reduced NCC-derived cranial length, increased mineralization in nasal septum and hyoid bones, and less bone mineralization at interfrontal suture in mutants at E18.5. Importantly, the mutant nasal septum and turbinate cartilage histologically revealed gradual, premature accelerated hypertrophic differentiation. We then studied the underlying molecular mechanisms by performing RNA seq analysis and unexpectedly found that expression of Ihh and related signaling molecules was enhanced in mutant nasomaxillary tissues. To see if Pth1r and Ihh signaling are associated, we generated a Wnt1-Cre; Ihhfl/fl;Pth1rfl/fl;Tomatofl/+ (DKO) mouse and compared the phenotypes to those of each single knockout mouse: Wnt1-Cre; Ihhfl/fl;Pth1rfl/+;Tomatofl/+ (Ihh-CKO) and Wnt1-Cre;Ihhfl/+;Pth1rfl/fl;Tomatofl/+ (Pth1r-CKO). Ihh-CKO mice displayed a milder effect. Of note, the excessive hypertrophic conversion of the nasal cartilage framework observed in Pth1r-CKO was somewhat rescued DKO embryos. Further, a half cAMP responsive element and the 4 similar sequences containing 2 mismatches were identified from the promoter to the first intron in Ihh gene. Gli1-CreERT2;Pth1rfl/fl;Tomatofl/+, a Pth1r-deficient model targeted in hedgehog responsive cells, demonstrated the enlarged hypertrophic layer and significantly more Tomato-positive chondrocytes accumulated in the nasal septum and ethmoidal endochondral ossification. Collectively, the data suggest a relevant Pth1r/Ihh interaction. Our findings obtained from novel mouse models for Pth1r signaling illuminate previously unknown aspects in craniofacial biology and development.

Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Genomic characterization of thymic epithelial tumors in a real-world dataset

BACKGROUND

Thymic epithelial tumors (TETs) are rare neoplasms arising in the mediastinum, including thymic carcinomas and thymomas. Due to their rarity, little is known about the genomic profiles of TETs. Herein, we investigated the genomic characteristics of TETs evaluated in a large comprehensive genomic profiling database in a real-world setting.

METHODS

We included data from two different cohorts: Foundation Medicine Inc. (FMI) in the United States and the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) in Japan. Samples profiled were examined for all classes of alterations in 253 genes targeted across all assays. Tumor mutational burden (TMB) and microsatellite instability (MSI) were also evaluated.

RESULTS

A total of 794 patients were collected in our study, including 722 cases from FMI and 72 cases from C-CAT. In the FMI data, CDKN2A (39.9%), TP53 (30.2%) and CDKN2B (24.6%) were frequently altered in thymic carcinoma, versus TP53 (7.8%), DNMT3A (6.8%), and CDKN2A (5.8%) in thymoma. TMB-high (≥10 mutations/Mb) and MSI were present in 7.0% and 2.3% of thymic carcinomas, and 1.6% and 0.3% of thymomas, respectively. Within C-CAT data, CDKN2A (38.5%), TP53 (36.5%) and CDKN2B (30.8%) were also frequently altered in thymic carcinoma, while alterations of TSC1, SETD2 and LTK (20.0% each) were found in thymoma.

CONCLUSIONS

To the best of our knowledge, this is the largest cohort in which genomic alterations, TMB and MSI status of TETs were investigated. Potential targets for treatment previously unbeknownst in TETs are identified in this study, entailing newfound opportunities to advance therapeutic development.

Pth1r Signal in Gli1+ Cells Maintains Postnatal Cranial Base Synchondrosis

Cranial base synchondroses are the endochondral ossification centers for cranial base growth and thus indispensable for proper skull, brain, and midfacial development. The synchondroses are composed of mirror-image growth plates that are continuously maintained from the embryonic to postnatal stage through chondrocyte differentiation. Several factors, including Pth1r signaling, are known to control fetal synchondrosis development. However, there are currently no reports regarding any role for Pth1r signaling in postnatal cranial base and synchondrosis development. Also, the mesenchymal cells that source Pth1r signaling for synchondroses are not known. Here, we employed an inducible mouse model, a hedgehog-responsive Gli1-CreERT2 driver, focusing on the postnatal study. We performed 2 inducible protocols using Gli1-CreERT2;Tomatofl/+ mice that uncovered distinct patterning of Gli1-positive and Gli1-negative chondrocytes in the synchondrosis cartilage. Moreover, we generated Gli1-CreERT2;Pth1rfl/fl;Tomatofl/+ mice to assess their functions in postnatal synchondrosis and found that the mutants had survived postnatally. The mutant skulls morphologically presented unambiguous phenotypes where we noticed the shortened cranial base and premature synchondrosis closure. Histologically, gradual disorganization in mutant synchondroses caused an uncommon remaining central zone between hypertrophic zones on both sides while the successive differentiation of round, flat, and hypertrophic chondrocytes was observed in control sections. These mutant synchondroses disappeared and were finally replaced by bone. Of note, the mutant fusing synchondroses lost their characteristic patterning of Gli1-positive and Gli1-negative chondrocytes, suggesting that loss of Pth1r signaling alters the distribution of hedgehog-responsive chondrocytes. Moreover, we performed laser microdissection and RNA sequencing to characterize the flat proliferative and round resting chondrocytes where we found flat chondrocytes have a characteristic feature of both chondrocyte proliferation and maturation. Taken together, these data demonstrate that Pth1r signaling in Gli1-positive cells is essential for postnatal development and maintenance in cranial base synchondroses. Our findings will elucidate previously unknown aspects of Pth1r functions in cranial biology and development.

Neuroimaging of hypophysitis: etiologies and imaging mimics

Hypophysitis is an inflammatory disease affecting the pituitary gland. Hypophysitis can be classified into multiple types depending on the mechanisms (primary or secondary), histology (lymphocytic, granulomatous, xanthomatous, plasmacytic/IgG4 related, necrotizing, or mixed), and anatomy (adenohypophysitis, infundibulo-neurohypophysitis, or panhypophysitis). An appropriate diagnosis is vital for managing these potentially life-threatening conditions. However, physiological morphological alterations, remnants, and neoplastic and non-neoplastic lesions may masquerade as hypophysitis, both clinically and radiologically. Neuroimaging, as well as imaging findings of other sites of the body, plays a pivotal role in diagnosis. In this article, we will review the types of hypophysitis and summarize clinical and imaging features of both hypophysitis and its mimickers.

MR imaging features to predict the type of bone metastasis in prostate cancer

Bone metastases (BMs) of prostate cancer (PCa) have been considered predominantly osteoblastic, but non-osteoblastic (osteolytic or mixed osteoblastic and osteolytic) BMs can occur. We investigated the differences in prostate MRI and clinical findings between patients with osteoblastic and non-osteoblastic BMs. Between 2014 and 2021, patients with pathologically proven PCa without a history of other malignancies were included in this study. Age, Gleason score, prostate-specific antigen (PSA) density, normalized mean apparent diffusion coefficient and normalized T2 signal intensity (nT2SI) of PCa, and Prostate Imaging Reporting and Data System category on MRI were compared between groups. A multivariate logistic regression analysis using factors with P-values < 0.2 was performed to detect the independent parameters for predicting non-osteoblastic BM group. Twenty-five (mean 73 ± 6.6 years) and seven (69 ± 13.1 years) patients were classified into the osteoblastic and non-osteoblastic groups, respectively. PSA density and nT2SI were significantly higher in the non-osteoblastic group than in the osteoblastic group. nT2SI was an independent predictive factor for non-osteoblastic BMs in the multivariate logistic regression analysis. These results indicated that PCa patients with high nT2SI and PSA density should be examined for osteolytic BMs.

Significance of Hypofractionated Radiotherapy in Postoperative Irradiation for Breast Cancer: An Asian Multi-institutional Prospective Study

AIMS

There is a need for the adequate distribution of healthcare resources in Southeast Asia. Many countries in the region have more patients with advanced breast cancer who are eligible for postmastectomy radiotherapy (PMRT). Therefore, it is critical that hypofractionated PMRT is effective in most of these patients. This study investigated the significance of postoperative hypofractionated radiotherapy in patients with breast cancer, including advanced breast cancer, in these countries.

MATERIALS AND METHODS

Eighteen facilities in 10 Asian countries participated in this prospective, interventional, single-arm study. The study included two independent regimens: hypofractionated whole-breast irradiation (WBI) for patients who had undergone breast-conserving surgery and hypofractionated PMRT for patients who had undergone total mastectomy at a dose of 43.2 Gy in 16 fractions. In the hypofractionated WBI group, patients with high-grade factors received additional 8.1 Gy boost irradiation sessions for the tumour bed in three fractions.

RESULTS

Between February 2013 and October 2019, 227 and 222 patients were enrolled in the hypofractionated WBI and hypofractionated PMRT groups, respectively. The median follow-up periods in the hypofractionated WBI and hypofractionated PMRT groups were 61 and 60 months, respectively. The 5-year locoregional control rates were 98.9% (95% confidence interval 97.4-100.0) and 96.3% (95% confidence interval 93.2-99.4) in the hypofractionated WBI and hypofractionated PMRT groups, respectively. Regarding adverse events, grade 3 acute dermatitis was observed in 2.2% and 4.9% of patients in the hypofractionated WBI and hypofractionated PMRT groups, respectively. However, no other adverse events were observed.

CONCLUSION

Although further follow-up is required, hypofractionated radiotherapy regimens for postoperative patients with breast cancer in East and Southeast Asian countries are effective and safe. In particular, the proven efficacy of hypofractionated PMRT indicates that more patients with advanced breast cancer can receive appropriate care in these countries. Hypofractionated WBI and hypofractionated PMRT are reasonable approaches that can contain cancer care costs in these countries. Long-term observation is required to validate our findings.

Cancer: slaying the nine-headed Hydra

Modern medicine continues to evolve, and the treatment armamentarium for various diseases grows more individualized across a breadth of medical disciplines. Cure rates for infectious diseases that were previously pan-fatal approach 100% because of the identification of the specific pathogen(s) involved and the use of appropriate combinations of drugs, where needed, to completely extinguish infection and hence prevent emergence of resistant strains. Similarly, with the assistance of technologies such as next-generation sequencing and immunomic analysis as part of the contemporary oncology armory, therapies can be tailored to each tumor. Importantly, molecular interrogation has revealed that metastatic cancers are distinct from each other and complex. Therefore, it is conceivable that rational personalized drug combinations will be needed to eradicate cancers, and eradication will be necessary to mitigate clonal evolution and resistance.

Computer-aided detection improves brain metastasis identification on non-enhanced CT in less experienced radiologists

Background

Brain metastases (BMs) are the most common intracranial tumors causing neurological complications associated with significant morbidity and mortality.

Purpose

To evaluate the effect of computer-aided detection (CAD) on the performance of observers in detecting BMs on non-enhanced computed tomography (NECT).

Material and Methods

Three less experienced and three experienced radiologists interpreted 30 NECT scans with 89 BMs in 25 cases to detect BMs with and without the assistance of CAD. The observers’ sensitivity, number of false positives (FPs), positive predictive value (PPV), and reading time with and without CAD were compared using paired t-tests. The sensitivity of CAD and the observers were compared using a one-sample t-test

Results

With CAD, less experienced radiologists’ sensitivity significantly increased from 27.7% ± 4.6% to 32.6% ± 4.8% ( P = 0.007), while the experienced radiologists’ sensitivity did not show a significant difference (from 33.3% ± 3.5% to 31.9% ± 3.7%; P = 0.54). There was no significant difference between conditions with CAD and without CAD for FPs (less experienced radiologists: 23.0 ± 10.4 and 25.0 ± 9.3; P = 0.32; experienced radiologists: 18.3 ± 7.4 and 17.3 ± 6.7; P = 0.76) and PPVs (less experienced radiologists: 57.9% ± 8.3% and 50.9% ± 7.0%; P = 0.14; experienced radiologists: 61.8% ± 12.7% and 64.0% ± 12.1%; P = 0.69). There were no significant differences in reading time with and without CAD (85.0 ± 45.6 s and 73.7 ± 36.7 s; P = 0.09). The sensitivity of CAD was 47.2% (with a PPV of 8.9%), which was significantly higher than that of any radiologist ( P < 0.001).

Conclusion

CAD improved BM detection sensitivity on NECT without increasing FPs or reading time among less experienced radiologists, but this was not the case among experienced radiologists.

Alleviative effects of glutamate against chemotherapeutic agent-induced intestinal mucositis

5-Fluorouracil (5-FU) is one of the most widely used chemotherapeutic agents; however, it often causes intestinal mucositis with severe diarrhea. An efficient treatment strategy to reduce this side effect is lacking. Glutamate (Glu), a nonessential amino acid, is the most important energy source in the small intestine and has been shown to maintain intestinal morphology, barrier function, and antioxidative capacity. However, the effects of Glu on intestinal mucositis induced by chemotherapeutic agents have not been explored. This study aimed to demonstrate the alleviative effects of Glu on 5-FU-induced intestinal mucositis. Mucositis was induced in C57B/6N mice by intraperitoneal injection of 5-FU (50 mg/kg) for 6 days and assessed by histological and physiological analyses. Glu (500 or 1000 mg/kg) was orally administered as a pretreatment twice daily for 7 days before the initial treatment of 5-FU. Cellular proliferation and apoptosis were assessed using Ki-67 immunostaining and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay, respectively. Furthermore, fluorescein isothiocyanate-dextran infiltration was assessed to measure intestinal permeability. In vitro experiments using rat intestinal epithelial cells (IEC-6 cells) were performed to clarify the effect of Glu on 5-FU-induced barrier dysfunction. Glu alleviated 5-FU-induced intestinal mucositis by reducing villi shortening, enhancing cell proliferation, and suppressing apoptosis. It also alleviated the 5-FU-induced increased intestinal permeability. In vitro studies revealed significantly increased trans-epithelial electrical resistance (TEER) in Glu-pretreated IEC-6 cells compared to that in 5-FU-treated and control cells. In conclusion, the findings of this study provide evidence for the potential of Glu to protect against 5-FU-induced intestinal mucositis in patients with cancer.

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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08555-3.

Association of differential expression of immunoregulatory molecules and presence of targetable mutations may inform rational design of clinical trials

Background

Immune checkpoint inhibitors (ICIs) and genomic biomarker-driven targeted therapies have revolutionized the modern oncologic treatment arsenal. The next step has been to combine targeted agents and ICIs. In doing so, some combination regimens may be more logical than others.

Patients and methods

Whole-exome and whole-transcriptome sequencing were performed on 2739 unselected later-stage clinical cases from 24 solid tumor subtypes in the NantHealth database, and data were also curated from 5746 similarly sequenced patients across 28 solid tumor subtypes in The Cancer Genome Atlas (TCGA). Significant differential expression of 10 immunoregulatory molecules [IRMs (genes)] was analyzed for association with mutant versus wild-type genes.

Results

Twenty-three significant associations between currently actionable variants and RNA-expressed checkpoint genes were identified in the TCGA cases; 10 were validated in the external cohort of 2739 clinical cases from NantHealth (P values were adjusted using Benjamini–Hochberg multiple hypothesis correction to reduce false-discovery rate). Within the same 5746 TCGA profiles, 2740 TCGA patients were identified as having one or more potentially oncogenic single-nucleotide variant (SNV) mutation within an established 50-gene hotspot panel. Of the 50 genes, SNVs within 15 were found to be significantly associated with differential expression of at least one IRM after adjusting for tissue enrichment; six were confirmed significant associations in an independent set of 2739 clinical cases from NantHealth.

Conclusions

Logically combining ICIs with targeted therapies may offer unique treatment strategies for patients with cancer. The presence of specific mutations impacts the expression of IRMs, an observation of potential importance for selecting combinations of gene- and immune-targeted therapeutics.

•

Altered actionable genes correlated with specific checkpoint transcripts.

•

Associations between IRMs and altered genes were validated in independent datasets.

•

Combining immune- and gene-targeted drugs based on IRM/gene correlations merits study.

Fungal Planet description sheets: 1284-1382

Novel species of fungi described in this study include those from various countries as follows: Antartica, Cladosporium austrolitorale from coastal sea sand. Australia, Austroboletus yourkae on soil, Crepidotus innuopurpureus on dead wood, Curvularia stenotaphri from roots and leaves of Stenotaphrum secundatum and Thecaphora stajsicii from capsules of Oxalis radicosa. Belgium, Paraxerochrysium coryli (incl. Paraxerochrysium gen. nov.) from Corylus avellana. Brazil, Calvatia nordestina on soil, Didymella tabebuiicola from leaf spots on Tabebuia aurea, Fusarium subflagellisporum from hypertrophied floral and vegetative branches of Mangifera indica and Microdochium maculosum from living leaves of Digitaria insularis. Canada, Cuphophyllus bondii from a grassland. Croatia, Mollisia inferiseptata from a rotten Laurus nobilis trunk. Cyprus, Amanita exilis on calcareous soil. Czech Republic, Cytospora hippophaicola from wood of symptomatic Vaccinium corymbosum. Denmark, Lasiosphaeria deviata on pieces of wood and herbaceous debris. Dominican Republic, Calocybella goethei among grass on a lawn. France (Corsica), Inocybe corsica on wet ground. France (French Guiana), Trechispora patawaensis on decayed branch of unknown angiosperm tree and Trechispora subregularis on decayed log of unknown angiosperm tree. Germany, Paramicrothecium sambuci (incl. Paramicrothecium gen. nov.) on dead stems of Sambucus nigra. India, Aureobasidium microtermitis from the gut of a Microtermes sp. termite, Laccaria diospyricola on soil and Phylloporia tamilnadensis on branches of Catunaregam spinosa. Iran, Pythium serotinoosporum from soil under Prunus dulcis. Italy, Pluteus brunneovenosus on twigs of broadleaved trees on the ground. Japan, Heterophoma rehmanniae on leaves of Rehmannia glutinosa f. hueichingensis. Kazakhstan, Murispora kazachstanica from healthy roots of Triticum aestivum. Namibia, Caespitomonium euphorbiae (incl. Caespitomonium gen. nov.) from stems of an Euphorbia sp. Netherlands, Alfaria junci, Myrmecridium junci, Myrmecridium juncicola, Myrmecridium juncigenum, Ophioceras junci, Paradinemasporium junci (incl. Paradinemasporium gen. nov.), Phialoseptomonium junci, Sporidesmiella juncicola, Xenopyricularia junci and Zaanenomyces quadripartis (incl. Zaanenomyces gen. nov.), from dead culms of Juncus effusus, Cylindromonium everniae and Rhodoveronaea everniae from Evernia prunastri, Cyphellophora sambuci and Myrmecridium sambuci from Sambucus nigra, Kiflimonium junci, Sarocladium junci, Zaanenomyces moderatricis-academiae and Zaanenomyces versatilis from dead culms of Juncus inflexus, Microcera physciae from Physcia tenella, Myrmecridium dactylidis from dead culms of Dactylis glomerata, Neochalara spiraeae and Sporidesmium spiraeae from leaves of Spiraea japonica, Neofabraea salicina from Salix sp., Paradissoconium narthecii (incl. Paradissoconium gen. nov.) from dead leaves of Narthecium ossifragum, Polyscytalum vaccinii from Vaccinium myrtillus, Pseudosoloacrosporiella cryptomeriae (incl. Pseudosoloacrosporiella gen. nov.) from leaves of Cryptomeria japonica, Ramularia pararhabdospora from Plantago lanceolata, Sporidesmiella pini from needles of Pinus sylvestris and Xenoacrodontium juglandis (incl. Xenoacrodontium gen. nov. and Xenoacrodontiaceae fam. nov.) from Juglans regia. New Zealand, Cryptometrion metrosideri from twigs of Metrosideros sp., Coccomyces pycnophyllocladi from dead leaves of Phyllocladus alpinus, Hypoderma aliforme from fallen leaves Fuscopora solandri and Hypoderma subiculatum from dead leaves Phormium tenax. Norway, Neodevriesia kalakoutskii from permafrost and Variabilispora viridis from driftwood of Picea abies. Portugal, Entomortierella hereditatis from a biofilm covering a deteriorated limestone wall. Russia, Colpoma junipericola from needles of Juniperus sabina, Entoloma cinnamomeum on soil in grasslands, Entoloma verae on soil in grasslands, Hyphodermella pallidostraminea on a dry dead branch of Actinidia sp., Lepiota sayanensis on litter in a mixed forest, Papiliotrema horticola from Malus communis, Paramacroventuria ribis (incl. Paramacroventuria gen. nov.) from leaves of Ribes aureum and Paramyrothecium lathyri from leaves of Lathyrus tuberosus. South Africa, Harzia combreti from leaf litter of Combretum collinum ssp. sulvense, Penicillium xyleborini from Xyleborinus saxesenii, Phaeoisaria dalbergiae from bark of Dalbergia armata, Protocreopsis euphorbiae from leaf litter of Euphorbia ingens and Roigiella syzygii from twigs of Syzygium chordatum. Spain, Genea zamorana on sandy soil, Gymnopus nigrescens on Scleropodium touretii, Hesperomyces parexochomi on Parexochomus quadriplagiatus, Paraphoma variabilis from dung, Phaeococcomyces kinklidomatophilus from a blackened metal railing of an industrial warehouse and Tuber suaveolens in soil under Quercus faginea. Svalbard and Jan Mayen, Inocybe nivea associated with Salix polaris. Thailand, Biscogniauxia whalleyi on corticated wood. UK, Parasitella quercicola from Quercus robur. USA, Aspergillus arizonicus from indoor air in a hospital, Caeliomyces tampanus (incl. Caeliomyces gen. nov.) from office dust, Cippumomyces mortalis (incl. Cippumomyces gen. nov.) from a tombstone, Cylindrium desperesense from air in a store, Tetracoccosporium pseudoaerium from air sample in house, Toxicocladosporium glendoranum from air in a brick room, Toxicocladosporium losalamitosense from air in a classroom, Valsonectria portsmouthensis from air in men's locker room and Varicosporellopsis americana from sludge in a water reservoir. Vietnam, Entoloma kovalenkoi on rotten wood, Fusarium chuoi inside seed of Musa itinerans, Micropsalliota albofelina on soil in tropical evergreen mixed forests and Phytophthora docyniae from soil and roots of Docynia indica. Morphological and culture characteristics are supported by DNA barcodes. Citation: Crous PW, Osieck ER, Jurjević Ž, et al. 2021. Fungal Planet description sheets: 1284-1382. Persoonia 47: 178-374. https://doi.org/10.3767/persoonia.2021.47.06.

Deep-learning single-shot detector for automatic detection of brain metastases with the combined use of contrast-enhanced and non-enhanced computed tomography images

PURPOSE

To develop a deep-learning object detection model for automatic detection of brain metastases that simultaneously uses contrast-enhanced and non-enhanced images as inputs, and to compare its performance with that of a model that uses only contrast-enhanced images.

METHOD

A total of 116 computed tomography (CT) scans of 116 patients with brain metastases were included in this study. They showed a total of 659 metastases, 428 of which were used for training and validation (mean size, 11.3 ± 9.9 mm) and 231 were used for testing (mean size, 9.0 ± 7.0 mm). Single-shot detector (SSD) models were constructed with a feature fusion module, and their results were compared per lesion at a confidence threshold of 50%.

RESULTS

The sensitivity was 88.7% for the model that used both contrast-enhanced and non-enhanced CT images (the CE + NECT model) and 87.6% for the model that used only contrast-enhanced CT images (the CECT model). The positive predictive value (PPV) was 44.0% for the CE + NECT model and 37.2% for the CECT model. The number of false positives per patient was 9.9 for the CE + NECT model and 13.6 for the CECT model. The CE + NECT model had a significantly higher PPV (t test, p < 0.001), significantly fewer false positives (t test, p < 0.001), and a tendency to be more sensitive (t test, p = 0.14).

CONCLUSIONS

The results indicate that the information on true contrast enhancement obtained by comparing the contrast-enhanced and non-enhanced images may prevent the detection of pseudolesions, suppress false positives, and improve the performance of deep-learning object detection models.

Denosumab-related osteonecrosis of the jaw after tooth extraction and the effects of a short drug holiday in cancer patients: a multicenter retrospective study

Pre-existing inflammation, corticosteroid therapy, periapical periodontitis, longer duration of denosumab therapy, and female sex were significantly associated with an increased risk of denosumab-related osteonecrosis of the jaw after tooth extraction in patients with cancer on oncologic doses of denosumab. A short drug holiday did not protect against this complication.

INTRODUCTION

This study retrospectively investigated the relationship between various risk factors, including brief discontinuation of denosumab, and development of denosumab-related osteonecrosis of the jaw (DRONJ) after tooth extraction in patients with cancer who were receiving oncologic doses of this agent.

METHODS

Data were collected on demographic characteristics, duration of denosumab therapy, whether or not denosumab was discontinued before tooth extraction (drug holiday), duration of discontinuation, presence of pre-existing inflammation, and whether or not additional surgical procedures were performed. Risk factors for DRONJ after tooth extraction were evaluated by univariate and multivariate analyses.

RESULTS

A total of 136 dental extractions were performed in 72 patients (31 men, 41 women) with cancer who were receiving oncologic doses of denosumab. Post-extraction DRONJ was diagnosed in 39 teeth (28.7%) in 25 patients. Tooth extraction was significantly associated with development of DRONJ only in patients with pre-existing inflammation (odds ratio [OR] 243.77), those on corticosteroid therapy (OR 73.50), those with periapical periodontitis (OR 14.13), those who had been taking oncologic doses of denosumab for a longer period (OR 4.69), and in women (OR 1.04). There was no significant difference in the occurrence of DRONJ between patients who had a drug holiday before tooth extraction and those who did not.

CONCLUSIONS

These findings suggest that inflamed teeth should be extracted immediately in patients with cancer who are receiving oncologic doses of denosumab. Drug holidays have no significant impact on the risk of DRONJ.

Long-term prognostic factors of coronary artery disease patients after out-of-hospital cardiac arrest

Background

The long-term prognosis of survival in patients with out-of-hospital cardiac arrest (OHCA) with coronary artery disease (CAD) remains poor.

Methods

There were 2391 out-of-hospital cardiac arrest (OHCA) patients transferred to 2 hospitals. We included 405 cardiovascular arrest patients, who got return of spontaneous circulation (ROSC) from January 2015 to December 2018. Among them, 204 patients had CAD that caused OHCA (39%: multi-vessel disease, 19%: chronic total occlusion (CTO), 13%: vasospastic angina (VSA)). To predict mortality, we investigated patients' characteristics, pre-hospital information and findings of CAG.

Results

At 1-year later, 104 patients (51%) survived. Younger age (P&lt;0.001), VF survivor (P&lt;0.001), pre-hospital ROSC (P&lt;0.001), bystander CPR (P=0.013), without ECMO (P&lt;0.001), lower lactate level on admission (P&lt;0.001), and higher geriatric nutritional risk index score (P&lt;0.001) were associated with low 1-year mortality, while with ST-segment elevation (P=0.778), BMI level (P=0.344), and sex (0.401) were not. And in the findings of CAG, the past history of CAD (P=0.049), the higher number of coronary vessel disease (P=0.003) such as multi-vessel disease (P=0.022), higher SYNAX score (P=0.016), and larger infarct size (max CK level; P=0.013, max CK-MB level; P&lt;0.001) were associated with high 1-year mortality. On the other hand, acute coronary syndrome (P=0.300), any coronary lesion (RCA (P=0.447), LAD (P=0.089), LCX (P=0.096), or LMT (P=0.842)), and with CTO lesion (P=0.140) were not associated. Zero-vessel disease (VSA, P=0.001) had lower mortality among the CAD patients. In the multivariate Cox proportional hazards model, age (hazards ratio; HR: 1.03, 95%confidence interval (CI) 1.00–1.06, P&lt;0.001) and bystander CPR (HR: 0.36, 95% CI 0.20–0.65, P&lt;0.001) were the independent predictors of mortality.

Conclusions

Younger age and pre-hospital support after OHCA with CAD were the predictors of low mortality. Pre-hospital information, systemic condition on arrival, or anatomical coronary complexity were important to predict low mortality.

Funding Acknowledgement

Type of funding sources: None.

Effect of endothelial nitric oxide synthase gene polymorphism on cardiovascular death and nonfatal myocardial infarction in Japanese general population

Introduction

Single nucleotide polymorphisms (SNP) of endothelial nitric oxide synthase (NOS3) have been reported to be associated with diabetes mellitus and myocardial infarction. However, few reports have prospectively investigated the effects of NOS3 SNP on cardiovascular death and nonfatal myocardial infarction.

Purpose

The purpose of this study was to investigate the impact of NOS3 SNP on cardiovascular death and the development of nonfatal myocardial infarction.

Methods

This prospective cohort study included 2,752 subjects (aged ≥40) who participated in a community based health checkup. We genotyped two SNPs within NOS3 (rs1808593, rs1799983). All subjects were prospectively followed during the median follow-up period of 15.4 years with the end point of cardiovascular death and nonfatal myocardial infarction.

Results

The homozygous G-allele (GG), heterozygous (GT), and homozygous T-allele (TT) carriers of rs1808593 were identified in 60 (2%), 706 (26%), and 1,986 (72%) subjects, respectively. Kaplan-Meier analysis demonstrated that homozygous G-allele carriers of rs1808593 had the greater risk than those without. Multivariate Cox proportional hazard regression analysis revealed that the homozygous G allele of rs1808593 was associated with cardiovascular death and the development of nonfatal myocardial infarction after adjusting for confounding risk factors.

Conclusions

NOS3 gene polymorphism could be a genetic risk factor for cardiovascular death and nonfatal myocardial infarction in the Japanese general population.

Funding Acknowledgement

Type of funding sources: None. Figure 1

Neurological outcome at 30-day as an estimator of 1-year functional status after out-of-hospital cardiac arrest with post-encephalopathy

Background

Implantation of implantable cardioverter-defibrillators (ICD) for secondary prevention is fully recommended for those with an estimated survival over 1-year with a good functional status. However, we often face the difficulty to estimate the functional status and hesitate to implant ICD for patients with post-resuscitation encephalopathy.

Methods

There were 2391 out-of-hospital cardiac arrest (OHCA) patients transferred to 2 hospitals. We included 405 cardiovascular arrest patients, who got return of spontaneous circulation (ROSC) from January 2015 to December 2018. Among the patients, 343 patients could be considered to be implanted ICD for secondary prevention according to the initial waveform or the causes of OHCA. At 1-month later, 184 patients (54%) survived. To assess the association of functional status at 30-day and 1-year, we investigated patients' characteristics, pre-hospital information and clinical findings, and evaluated the neurological outcome according to the cerebral performance category (CPC) scale.

Results

At 1-month later, 145 patients (79%) survived with CPC≤2, and 39 patients (21%) survived with CPC&gt;2. Bystander CPR (P=0.009), pre-hospital ROSC (P&lt;0.001), low lactate level on admission (P=0.001), high geriatric nutritional risk index score (P&lt;0.001) and without ECMO (P=0.002) were significantly associated with good neurological outcome at 30-day. The 1-year Kaplan-Meier event rate revealed significantly different survival rate (CPC&gt;2 at 30-day:38.5%, vs CPC≤2 at 30-day:97.2%; P&lt;0.001). In multivariate analysis, CPC scale at 30-day (OR 0.022; 95% CI 0.003–0.140; p&lt;0.001) was the independent predictor of favorable neurological outcome at 1-year. Among the patients with CPC&gt;2 at 30-day, only 3 patients (7.7%) of CPC=3 achieved the improvement of neurological outcome at 1-year (CPC≤2), while no patient of CPC=4 did. And one patient (2.5%) with CPC=3 was implanted ICD during the follow-up period. Twenty-five patients (64%) died of non-cardiovascular death with frailty of post-resuscitation encephalopathy after they were transferred to other hospital with the acceptation and intention of the do-not-attempt-resuscitation.

Conclusions

Neurological prognosis at 30-day after OHCA might be an estimator of 1-year functional status to guide us to implant ICD for secondary prevention.

Funding Acknowledgement

Type of funding sources: None.

Gender differences in the impact of plasma xanthine oxidoreductase activity on coronary artery spasm

Background

It has been reported that decreased nitric oxide bioavailability due to increased reactive oxygen species (ROS) is one of the most important causes of coronary artery spasm (CAS). Xanthine oxidoreductase (XOR) is the rate-limiting enzyme for uric acid (UA) production and plays a pivotal role in generating ROS. It was reported that the gender differences exist in the impact of serum UA levels on cardiovascular risks. We previously demonstrated that increased plasma XOR activity is significantly associated with the incidence of CAS. However, the gender differences in the impact of plasma XOR activity on CAS remain unclear.

Purpose

The aim of this study was to examine the gender differences in the clinical impact of plasma XOR activity on CAS.

Methods

We investigated plasma XOR activity in 132 patients suspected for CAS (male, n=78; female, n=54), and underwent intracoronary acetylcholine provocation test. XOR activity assay was performed using stable isotope-labeled substrate and liquid chromatography-triple quadrupole mass spectrometry. Provoked CAS was defined as total or subtotal occlusion (≥90%) with accompanying symptoms of chest pain and/or ischemic ST-segment changes on the electrocardiogram. We excluded the patients who had significant coronary artery stenosis (≥50%) and/or were taking XOR inhibitors.

Results

Plasma XOR activity was significantly lower in female compared with male patients (30.3 pmol/h/mL, interquartile range (IQR) 22.8–42.7 vs. 51.7 pmol/h/mL, IQR 34.7–101.8; P&lt;0.001). CAS was provoked in 36 male patients and 17 female patients, and they each had significantly higher plasma XOR activity compared with those without, respectively. Multivariate logistic regression analysis showed that plasma XOR activity was independently associated with the incidence of CAS in both genders after adjustment for confounding factors. The optimal cut-off values for predicting CAS were lower in female than those in male patients (52.3 vs. 91.6 pmol/h/mL). Multivariate analysis demonstrated that female patients with high XOR activity (≥52.3 pmol/h/mL; odds ratio [OR] 22.6, P&lt;0.001) exhibited a higher incidence of CAS compared with that in male patients (≥91.6 pmol/h/mL; OR 8.2, P&lt;0.001).

Conclusions

Plasma XOR activity was an independent predictor for the incidence of CAS in both genders. The impact of plasma XOR activity on CAS was stronger in female patients than in male patients.

Funding Acknowledgement

Type of funding sources: None. Figure 1Figure 2

Feature-fusion improves MRI single-shot deep learning detection of small brain metastases

BACKGROUND AND PURPOSE

To examine whether feature-fusion (FF) method improves single-shot detector's (SSD's) detection of small brain metastases on contrast-enhanced (CE) T1-weighted MRI.

METHODS

The study included 234 MRI scans from 234 patients (64.3 years±12.0; 126 men). The ground-truth annotation was performed semiautomatically. SSDs with and without an FF module were developed and trained using 178 scans. The detection performance was evaluated at the SSDs' 50% confidence threshold using sensitivity, positive-predictive value (PPV), and the false-positive (FP) per scan with the remaining 56 scans.

RESULTS

FF-SSD achieved an overall sensitivity of 86.0% (95% confidence interval [CI]: [83.0%, 85.6%]; 196/228) and 46.8% PPV (95% CI: [42.0%, 46.3%]; 196/434), with 4.3 FP (95% CI: [4.3, 4.9]). Lesions smaller than 3 mm had 45.8% sensitivity (95% CI: [36.1%, 45.5%]; 22/48) with 2.0 FP (95% CI: [1.9, 2.1]). Lesions measuring 3-6 mm had 92.3% sensitivity (95% CI: [86.5%, 92.0%]; 48/52) with 1.8 FP (95% CI: [1.7, 2.2]). Lesions larger than 6 mm had 98.4% sensitivity (95% CI: [97.8%, 99.4%]; 126/128) 0.5 FP (95% CI: [0.5, 0.8]) per scan. FF-SSD had a significantly higher sensitivity for lesions < 3 mm (p = 0.008, t = 3.53) than the baseline SSD, while the overall PPV was similar (p = 0.06, t = -2.16). A similar trend was observed even when the detector's confidence threshold was varied as low as 0.2, for which the FF-SSD's sensitivity was 91.2% and the FP was 9.5.

CONCLUSIONS

The FF-SSD algorithm identified brain metastases on CE T1-weighted MRI with high accuracy.

Fungal Planet description sheets: 1284-1382

Novel species of fungi described in this study include those from various countries as follows: Antartica, Cladosporium austrolitorale from coastal sea sand. Australia, Austroboletus yourkae on soil, Crepidotus innuopurpureus on dead wood, Curvularia stenotaphri from roots and leaves of Stenotaphrum secundatum and Thecaphora stajsicii from capsules of Oxalis radicosa. Belgium, Paraxerochrysium coryli (incl. Paraxerochrysium gen. nov.) from Corylus avellana. Brazil, Calvatia nordestina on soil, Didymella tabebuiicola from leaf spots on Tabebuia aurea, Fusarium subflagellisporum from hypertrophied floral and vegetative branches of Mangifera indica and Microdochium maculosum from living leaves of Digitaria insularis. Canada, Cuphophyllus bondii from a grassland. Croatia, Mollisia inferiseptata from a rotten Laurus nobilis trunk. Cyprus, Amanita exilis on calcareous soil. Czech Republic, Cytospora hippophaicola from wood of symptomatic Vaccinium corymbosum. Denmark, Lasiosphaeria deviata on pieces of wood and herbaceous debris. Dominican Republic, Calocybella goethei among grass on a lawn. France (Corsica), Inocybe corsica on wet ground. France (French Guiana), Trechispora patawaensis on decayed branch of unknown angiosperm tree and Trechispora subregularis on decayed log of unknown angiosperm tree. Germany, Paramicrothecium sambuci (incl. Paramicrothecium gen. nov.) on dead stems of Sambucus nigra. India, Aureobasidium microtermitis from the gut of a Microtermes sp. termite, Laccaria diospyricola on soil and Phylloporia tamilnadensis on branches of Catunaregam spinosa. Iran, Pythium serotinoosporum from soil under Prunus dulcis. Italy, Pluteus brunneovenosus on twigs of broadleaved trees on the ground. Japan, Heterophoma rehmanniae on leaves of Rehmannia glutinosa f. hueichingensis. Kazakhstan, Murispora kazachstanica from healthy roots of Triticum aestivum. Namibia, Caespitomonium euphorbiae (incl. Caespitomonium gen. nov.) from stems of an Euphorbia sp. Netherlands, Alfaria junci, Myrmecridium junci, Myrmecridium juncicola, Myrmecridium juncigenum, Ophioceras junci, Paradinemasporium junci (incl. Paradinemasporium gen. nov.), Phialoseptomonium junci, Sporidesmiella juncicola, Xenopyricularia junci and Zaanenomyces quadripartis (incl. Zaanenomyces gen. nov.), from dead culms of Juncus effusus, Cylindromonium everniae and Rhodoveronaea everniae from Evernia prunastri, Cyphellophora sambuci and Myrmecridium sambuci from Sambucus nigra, Kiflimonium junci, Sarocladium junci, Zaanenomyces moderatricis-academiae and Zaanenomyces versatilis from dead culms of Juncus inflexus, Microcera physciae from Physcia tenella, Myrmecridium dactylidis from dead culms of Dactylis glomerata, Neochalara spiraeae and Sporidesmium spiraeae from leaves of Spiraea japonica, Neofabraea salicina from Salix sp., Paradissoconium narthecii (incl. Paradissoconium gen. nov.) from dead leaves of Narthecium ossifragum, Polyscytalum vaccinii from Vaccinium myrtillus, Pseudosoloacrosporiella cryptomeriae (incl. Pseudosoloacrosporiella gen. nov.) from leaves of Cryptomeria japonica, Ramularia pararhabdospora from Plantago lanceolata, Sporidesmiella pini from needles of Pinus sylvestris and Xenoacrodontium juglandis (incl. Xenoacrodontium gen. nov. and Xenoacrodontiaceae fam. nov.) from Juglans regia. New Zealand, Cryptometrion metrosideri from twigs of Metrosideros sp., Coccomyces pycnophyllocladi from dead leaves of Phyllocladus alpinus, Hypoderma aliforme from fallen leaves Fuscopora solandri and Hypoderma subiculatum from dead leaves Phormium tenax. Norway, Neodevriesia kalakoutskii from permafrost and Variabilispora viridis from driftwood of Picea abies. Portugal, Entomortierella hereditatis from a biofilm covering a deteriorated limestone wall. Russia, Colpoma junipericola from needles of Juniperus sabina, Entoloma cinnamomeum on soil in grasslands, Entoloma verae on soil in grasslands, Hyphodermella pallidostraminea on a dry dead branch of Actinidia sp., Lepiota sayanensis on litter in a mixed forest, Papiliotrema horticola from Malus communis, Paramacroventuria ribis (incl. Paramacroventuria gen. nov.) from leaves of Ribes aureum and Paramyrothecium lathyri from leaves of Lathyrus tuberosus. South Africa, Harzia combreti from leaf litter of Combretum collinum ssp. sulvense, Penicillium xyleborini from Xyleborinus saxesenii, Phaeoisaria dalbergiae from bark of Dalbergia armata, Protocreopsis euphorbiae from leaf litter of Euphorbia ingens and Roigiella syzygii from twigs of Syzygium chordatum. Spain, Genea zamorana on sandy soil, Gymnopus nigrescens on Scleropodium touretii, Hesperomyces parexochomi on Parexochomus quadriplagiatus, Paraphoma variabilis from dung, Phaeococcomyces kinklidomatophilus from a blackened metal railing of an industrial warehouse and Tuber suaveolens in soil under Quercus faginea. Svalbard and Jan Mayen, Inocybe nivea associated with Salix polaris. Thailand, Biscogniauxia whalleyi on corticated wood. UK, Parasitella quercicola from Quercus robur. USA, Aspergillus arizonicus from indoor air in a hospital, Caeliomyces tampanus (incl. Caeliomyces gen. nov.) from office dust, Cippumomyces mortalis (incl. Cippumomyces gen. nov.) from a tombstone, Cylindrium desperesense from air in a store, Tetracoccosporium pseudoaerium from air sample in house, Toxicocladosporium glendoranum from air in a brick room, Toxicocladosporium losalamitosense from air in a classroom, Valsonectria portsmouthensis from air in men's locker room and Varicosporellopsis americana from sludge in a water reservoir. Vietnam, Entoloma kovalenkoi on rotten wood, Fusarium chuoi inside seed of Musa itinerans, Micropsalliota albofelina on soil in tropical evergreen mixed forests and Phytophthora docyniae from soil and roots of Docynia indica. Morphological and culture characteristics are supported by DNA barcodes. Citation: Crous PW, Osieck ER, Jurjević Ž, et al. 2021. Fungal Planet description sheets: 1284-1382. Persoonia 47: 178-374. https://doi.org/10.3767/persoonia.2021.47.06.

Gamma-Ray Observation of the Cygnus Region in the 100-TeV Energy Region

We report observations of gamma-ray emissions with energies in the 100-TeV energy region from the Cygnus region in our Galaxy. Two sources are significantly detected in the directions of the Cygnus OB1 and OB2 associations. Based on their positional coincidences, we associate one with a pulsar PSR J2032+4127 and the other mainly with a pulsar wind nebula PWN G75.2+0.1, with the pulsar moving away from its original birthplace situated around the centroid of the observed gamma-ray emission. This work would stimulate further studies of particle acceleration mechanisms at these gamma-ray sources.

Structural connectivity changes in the cerebral pain matrix in burning mouth syndrome: a multi-shell, multi-tissue-constrained spherical deconvolution model analysis

PURPOSE

Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome. Previous studies have attempted to determine the brain connectivity features in BMS using functional and structural magnetic resonance imaging. However, no study has investigated the structural connectivity using multi-shell, multi-tissue-constrained spherical deconvolution (MSMT-CSD), anatomically constrained tractography (ACT), and spherical deconvolution informed filtering of tractograms (SIFT). Therefore, this study aimed to assess the differences in brain structural connectivity of patients with BMS and healthy controls using probabilistic tractography with these methods, and graph analysis.

METHODS

Fourteen patients with BMS and 11 age- and sex-matched healthy volunteers underwent 3-T magnetic resonance imaging. MSMT-CSD-based probabilistic structural connectivity was computed using the second-order integration over fiber orientation distributions algorithm based on nodes set in 84 anatomical cortical regions with ACT and SIFT. A t-test was performed for comparisons between the BMS and healthy control brain networks.

RESULTS

The betweenness centrality was significantly higher in the left insula, right amygdala, and right lateral orbitofrontal cortex and significantly lower in the right inferotemporal cortex in the BMS group than that in healthy controls. However, no significant difference was found in the clustering coefficient, node degree, and small-worldness between the two groups.

CONCLUSION

Graph analysis of brain probabilistic structural connectivity, based on diffusion imaging using an MSMT-CSD model with ACT and SIFT, revealed alterations in the regions comprising the pain matrix and medial pain ascending pathway. These results highlight the emotional-affective profile of BMS, which is a type of chronic pain syndrome.

Automated detection of brain metastases on non-enhanced CT using single-shot detectors

PURPOSE

To develop and investigate deep learning-based detectors for brain metastases detection on non-enhanced (NE) CT.

METHODS

The study included 116 NECTs from 116 patients (81 men, age 66.5 ± 10.6 years) to train and test single-shot detector (SSD) models using 89 and 27 cases, respectively. The annotation was performed by three radiologists using bounding-boxes defined on contrast-enhanced CT (CECT) images. NECTs were coregistered and resliced to CECTs. The detection performance was evaluated at the SSD's 50% confidence threshold using sensitivity, positive-predictive value (PPV), and the false-positive rate per scan (FPR). For false negatives and true positives, binary logistic regression was used to examine the possible contributing factors.

RESULTS

For lesions 6 mm or larger, the SSD achieved a sensitivity of 35.4% (95% confidence interval (CI): [32.3%, 33.5%]); 51/144) with an FPR of 14.9 (95% CI [12.4, 13.9]). The overall sensitivity was 23.8% (95% CI: [21.3%, 22.8%]; 55/231) and PPV was 19.1% (95% CI: [18.5%, 20.4%]; 98/ of 513), with an FPR of 15.4 (95% CI [12.9, 14.5]). Ninety-five percent of the lesions that SSD failed to detect were also undetectable to radiologists (168/176). Twenty-four percent of the lesions (13/50) detected by the SSD were undetectable to radiologists. Logistic regression analysis indicated that density, necrosis, and size contributed to the lesions' visibility for radiologists, while for the SSD, the surrounding edema also enhanced the detection performance.

CONCLUSION

The SSD model we developed could detect brain metastases larger than 6 mm to some extent, a quarter of which were even retrospectively unrecognizable to radiologists.

Accelerated Isotropic Multiparametric Imaging by High Spatial Resolution 3D-QALAS With Compressed Sensing: A Phantom, Volunteer, and Patient Study

OBJECTIVES

The aims of this study were to develop an accelerated multiparametric magnetic resonance imaging method based on 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) combined with compressed sensing (CS) and to evaluate the effect of CS on the quantitative mapping, tissue segmentation, and quality of synthetic images.

MATERIALS AND METHODS

A magnetic resonance imaging system phantom, containing multiple compartments with standardized T1, T2, and proton density (PD) values; 10 healthy volunteers; and 12 patients with multiple sclerosis were scanned using the 3D-QALAS sequence with and without CS and conventional contrast-weighted imaging. The scan times of 3D-QALAS with and without CS were 5:56 and 11:11, respectively. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. For patients with multiple sclerosis, the mean T1, T2, PD, and the amount of myelin in plaques and contralateral normal-appearing white matter (NAWM) were measured. Simple linear regression analysis and Bland-Altman analysis were performed for each metric obtained from the datasets with and without CS. To compare overall image quality and structural delineations on synthetic and conventional contrast-weighted images, case-control randomized reading sessions were performed by 2 neuroradiologists in a blinded manner.

RESULTS

The linearity of both phantom and volunteer measurements in T1, T2, and PD values obtained with and without CS was very strong (R2 = 0.9901-1.000). The tissue segmentation obtained with and without CS also had high linearity (R2 = 0.987-0.999). The quantitative tissue values of the plaques and NAWM obtained with CS showed high linearity with those without CS (R2 = 0.967-1.000). There were no significant differences in overall image quality between synthetic contrast-weighted images obtained with and without CS (P = 0.17-0.99).

CONCLUSIONS

Multiparametric imaging of the whole brain based on 3D-QALAS can be accelerated using CS while preserving tissue quantitative values, tissue segmentation, and quality of synthetic images.

First Detection of sub-PeV Diffuse Gamma Rays from the Galactic Disk: Evidence for Ubiquitous Galactic Cosmic Rays beyond PeV Energies

We report, for the first time, the long-awaited detection of diffuse gamma rays with energies between 100 TeV and 1 PeV in the Galactic disk. Particularly, all gamma rays above 398 TeV are observed apart from known TeV gamma-ray sources and compatible with expectations from the hadronic emission scenario in which gamma rays originate from the decay of π^{0}'s produced through the interaction of protons with the interstellar medium in the Galaxy. This is strong evidence that cosmic rays are accelerated beyond PeV energies in our Galaxy and spread over the Galactic disk.

Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorders by multiparametric quantitative MRI using convolutional neural network

Multiple sclerosis and neuromyelitis optica spectrum disorders are both neuroinflammatory diseases and have overlapping clinical manifestations. We developed a convolutional neural network model that differentiates between the two based on magnetic resonance imaging data. Thirty-five patients with relapsing-remitting multiple sclerosis and eighteen age-, sex-, disease duration-, and Expanded Disease Status Scale-matched patients with anti-aquaporin-4 antibody-positive neuromyelitis optica spectrum disorders were included in this study. All patients were scanned on a 3-T scanner using a multi-dynamic multi-echo sequence that simultaneously measures R1 and R2 relaxation rates and proton density. R1, R2, and proton density maps were analyzed using our convolutional neural network model. To avoid overfitting on a small dataset, we aimed to separate features of images into those specific to an image and those common to the group, based on SqueezeNet. We used only common features for classification. Leave-one-out cross validation was performed to evaluate the performance of the model. The area under the receiver operating characteristic curve of the developed convolutional neural network model for differentiating between the two disorders was 0.859. The sensitivity to multiple sclerosis and neuromyelitis optica spectrum disorders, and accuracy were 80.0%, 83.3%, and 81.1%, respectively. In conclusion, we developed a convolutional neural network model that differentiates between multiple sclerosis and neuromyelitis optica spectrum disorders, and which is designed to avoid overfitting on small training datasets. Our proposed algorithm may facilitate a differential diagnosis of these diseases in clinical practice.

Age-Related Changes in Relaxation Times, Proton Density, Myelin, and Tissue Volumes in Adult Brain Analyzed by 2-Dimensional Quantitative Synthetic Magnetic Resonance Imaging

OBJECTIVES

Quantitative synthetic magnetic resonance imaging (MRI) enables the determination of fundamental tissue properties, namely, T1 and T2 relaxation times and proton density (PD), in a single scan. Myelin estimation and brain segmentation based on these quantitative values can also be performed automatically. This study aimed to reveal the changes in tissue characteristics and volumes of the brain according to age and provide age-specific reference values obtained by quantitative synthetic MRI.

MATERIALS AND METHODS

This was a prospective study of healthy subjects with no history of brain diseases scanned with a multidynamic multiecho sequence for simultaneous measurement of relaxometry of T1, T2, and PD. We performed myelin estimation and brain volumetry based on these values. We performed volume-of-interest analysis on both gray matter (GM) and white matter (WM) regions for T1, T2, PD, and myelin volume fraction maps. Tissue volumes were calculated in the whole brain, producing brain parenchymal volume, GM volume, WM volume, and myelin volume. These volumes were normalized by intracranial volume to a brain parenchymal fraction, GM fraction, WM fraction, and myelin fraction (MyF). We examined the changes in the mean regional quantitative values and segmented tissue volumes according to age.

RESULTS

We analyzed data of 114 adults (53 men and 61 women; median age, 66.5 years; range, 21-86 years). T1, T2, and PD values showed quadratic changes according to age and stayed stable or decreased until around 60 years of age and increased thereafter. Myelin volume fraction showed a reversed trend. Brain parenchymal fraction and GM fraction decreased throughout all ages. The approximation curves showed that WM fraction and MyF gradually increased until around the 40s to 50s and decreased thereafter. A significant decline in MyF was first noted in the 60s age group (Tukey test, P < 0.001).

CONCLUSIONS

Our study showed changes according to age in tissue characteristic values and brain volumes using quantitative synthetic MRI. The reference values for age demonstrated in this study may be useful to discriminate brain disorders from healthy brains.

Automatic detection of brain metastases on contrast-enhanced CT with deep-learning feature-fused single-shot detectors

PURPOSE

Despite the potential usefulness, no automatic detector is available for brain metastases on contrast-enhanced CT (CECT). The study aims to develop and investigate deep learning-based detectors for brain metastases detection on CECT.

METHOD

The study included 127 CECTs from 127 patients (65.5 years±11.1; 87 men). The ground-truth annotation was performed semi-automatically by applying connected-component analysis to the binarized dataset by three radiologists. Single-shot detector (SSD) algorithms, with and without a feature-fusion module, were developed and trained using 97 scans. The performance was evaluated at the detector's 50 % confidence threshold with the remaining 30 scans using sensitivity, positive-predictive value (PPV), and the false-positive rate per scan (FPR).

RESULTS

Feature-fused SSD achieved an overall sensitivity of 88.1 % (95 % confidence interval [CI]: [85.2 %,88.6 %]; 214/243) and PPV of 36.0 % (95 % CI: [33.7 %,37.1 %]; 233/648), with 13.8 FPR (95 % CI: [12.7,15.0]). Lesions < 3 mm had a sensitivity of 23.1 % (95 % CI: [21.2 %,40.0 %]; 3/13), with 0.2 FPR (95 % CI: [0.23,0.65]). Lesions measuring 3-6 mm had a sensitivity of 80.0 % (95 % CI: [76.0 %,79.8 %]); 60/75) with 5.8 FPR (95 % CI: [5.0,6.2]). Lesions > 6 mm had a sensitivity of 97.4 % (95 % CI: [94.1 %,97.4 %]); 151/155) with 7.9 FPR (95 % CI: [7.2,8.5]). Feature-fused SSD had a significantly higher overall sensitivity (p = 0.03, t = 2.75) or sensitivity for lesions < 3 mm (p = 0.002, t = 4.49) than baseline SSD, while the overall PPV was similar (p = 0.96, t = -0.02).

CONCLUSIONS

The SSD algorithm identified brain metastases on CECT with reasonable accuracy for lesions > 3 mm without pre/post-processing.

Effect of hybrid of compressed sensing and parallel imaging on the quantitative values measured by 3D quantitative synthetic MRI: A phantom study

INTRODUCTION

Recently, three-dimensional (3D) quantitative synthetic magnetic resonance imaging (MRI), which quantifies tissue properties and creates multiple contrast-weighted images, has been enabled by 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). However, the relatively long scan time has hindered its introduction into clinical practice. A hybrid of compressed sensing and parallel imaging (Compressed sensing-sensitivity encoding: CS-SENSE) can accelerate 3D-QALAS; however, whether CS-SENSE affects the quantitative values acquired by 3D-QALAS remains unexplored. Therefore, this study aimed to examine the effects of reduction factors of CS-SENSE (R_CSS) on the quantitative values derived from 3D-QALAS, by assessing the signal-to-noise ratio (SNR) of the quantitative maps, as well as accuracy (linearity and bias) and repeatability of measured quantitative values.

METHODS

In this study, the ISMRM/NIST standardized phantom was scanned on a 1.5-T MRI scanner with 3D-QALAS using R_CSS in the range between 1 and 3, with intervals of 0.2, and between 3 and 10 with intervals of 0.5. The T1, T2, and proton density (PD) values were calculated from the imaging data. For each quantitative value, the SNR, the coefficient of determination (R²) of a linear regression model, the error rate, and the within-subject coefficient of variation (wCV) were calculated for each R_CSS and compared.

RESULTS

Within the clinically-relevant dynamic range of the brain of T1 and T2 (T1: 200-1400 ms; T2; 50-400 ms) and PD value of 15-100% calculated from 3D-QALAS, the effects of R_CSS on quantitative values was small between 1 and 2.8, with SNR ≧ 10, R² ≧ 0.9, error rate ≦ 10%, and wCV ≦ 10%, except for T2 values of 186.1 and 258.4 ms.

CONCLUSIONS

CS-SENSE enabled the reduction of the scan time of 3D-QALAS by 63.5% (R_CSS = 2.8) while maintaining the SNR of quantitative maps and accuracy and repeatability of the quantitative values.

3D Quantitative Synthetic MRI in the Evaluation of Multiple Sclerosis Lesions

BACKGROUND AND PURPOSE

Synthetic MR imaging creates multiple contrast-weighted images based on a single time-efficient quantitative scan, which has been mostly performed for 2D acquisition. We assessed the utility of 3D synthetic MR imaging in patients with MS by comparing its diagnostic image quality and lesion volumetry with conventional MR imaging.

MATERIALS AND METHODS

Twenty-four patients with MS prospectively underwent 3D quantitative synthetic MR imaging and conventional T1-weighted, T2-weighted, FLAIR, and double inversion recovery imaging, with acquisition times of 9 minutes 3 seconds and 18 minutes 27 seconds for the synthetic MR imaging and conventional MR imaging sequences, respectively. Synthetic phase-sensitive inversion recovery images and those corresponding to conventional MR imaging contrasts were created for synthetic MR imaging. Two neuroradiologists independently assessed the image quality on a 5-point Likert scale. The numbers of cortical lesions and lesion volumes were quantified using both synthetic and conventional image sets.

RESULTS

The overall diagnostic image quality of synthetic T1WI and double inversion recovery images was noninferior to that of conventional images (P = .23 and .20, respectively), whereas that of synthetic T2WI and FLAIR was inferior to that of conventional images (both Ps < .001). There were no significant differences in the number of cortical lesions (P = .17 and .53 for each rater) or segmented lesion volumes (P = .61) between the synthetic and conventional image sets.

CONCLUSIONS

Three-dimensional synthetic MR imaging could serve as an alternative to conventional MR imaging in evaluating MS with a reduced scan time.

Relationship between cardiac magnetic resonance derived extracellular volume fraction and myocardial strain in patients with non-ischemic dilated cardiomyopathy

Background

The feature tracking (FT) technique has been proposed as a robust method to evaluate the myocardial strain using conventional cine magnetic resonance imaging (MRI) of the left ventricle. Data is limited regarding the relationship between FT-derived myocardial strain and diffuse myocardial fibrosis evaluated by T1 mapping in patients with non-ischemic dilated cardiomyopathy (NIDCM).

Purpose

The aim of this study was to evaluate the correlation between extracellular volume (ECV) by T1 mapping and myocardial strain by FT in patients with NIDCM.

Methods

A total of sixty-four patients with NIDCM (62±12 years) and 15 controls (62±11 years) were studied. Using a 1.5T MR scanner, pre- and post- T1 mapping images of LV wall at mid-ventricular level was acquired to calculate ECV by modified Look-Locker inversion recovery (MOLLI) sequence. Radial strain (RS), circumferential strain (CS) and longitudinal strain (LS) was assessed by FT technique. ECV and myocardial strain were compared using a 6-segment model at mid-ventricular level.

Results

Compared to the controls, the NIDCM patients had a significantly higher ECV (0.30±0.02 vs. 0.24±0.01, p&lt;0.001) and impaired myocardial strain (RS, 24.2±3.0 vs. 52.2±6.2, p&lt;0.001; CS, −7.5±2.1 vs. −15.3±2.2, p&lt;0.001; LS −10.4±3.5 vs. −20.2±4.7, p&lt;0.001, respectively). Similar results were obtained when comparing all 6 myocardial segments (segment 7–12) (all p values &lt;0.001). In a segment-based analysis, a significant positive correlation was found between the ECV and CS (r=0.26 to 0.41; all p values &lt;0.05), a negative correlation was found between the ECV and RS (r=−0.31 to −0.41; all p values &lt;0.05). In a patient-based analysis, there were significant positive correlations between the ECV and CS (r=0.45, p&lt;0.001), ECV and LS from 2-chamber view (r=0.30, p=0.006), ECV and LS from 4-chamber view (r=0.37, p&lt;0.001). There was a significant negative correlation between the ECV and RS (r=−0.43, p&lt;0.001) (FIGURE)

Conclusions

In NIDCM patients, severity of myocardial fibrosis evaluated by T1 mapping is associated with impaired myocardial strain by FT technique.

Correlation between the ECV and strain

Funding Acknowledgement

Type of funding source: None