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Both enantiomers of functionalized Hajos-Parrish ketone (HPK) analogs were prepared with excellent diastereoselectivities and enantioselectivities using the same chiral catalyst under two slightly different conditions. In condition A, dioxane was used as the solvent with 3 equivalents of water. In condition B, acetonitrile was used as the solvent with 30 equivalents of water, followed by epimerization with a base in a one-pot. The reaction consisted of a domino reaction including a diphenylprolinol silyl ether-mediated asymmetric Michael reaction and an intramolecular Henry reaction. In the Michael reaction, depending on the solvent and water amounts, syn- and anti-isomers were selectively synthesized with excellent enantioselectivity, in which the absolute configuration at C5 (indanone numbering) was opposite. The subsequent Henry reaction was diastereoselective, in which the C5 substituent controlled the three chiral centers in a highly diastereoselective manner. The final base treatment in condition B caused epimerization, changing the stereochemistry at C6. Switching more than two chiral centers with high enantioselectivity is extremely difficult using the same chiral catalyst; the present reaction is a very rare enantiodivergent reaction that switches five continuous chiral centers with high enantioselectivity., (© 2024 Wiley‐VCH GmbH.)

Changing a window width (WW) alters appearance of noise and contrast of CT images. The aim of this study was to investigate the impact of adjusted WW for deep learning reconstruction (DLR) in detecting hepatocellular carcinomas (HCCs) on CT with DLR. This retrospective study included thirty-five patients who underwent abdominal dynamic contrast-enhanced CT. DLR was used to reconstruct arterial, portal, and delayed phase images. The investigation of the optimal WW involved two blinded readers. Then, five other blinded readers independently read the image sets for detection of HCCs and evaluation of image quality with optimal or conventional liver WW. The optimal WW for detection of HCC was 119 (rounded to 120 in the subsequent analyses) Hounsfield unit (HU), which was the average of adjusted WW in the arterial, portal, and delayed phases. The average figures of merit for the readers for the jackknife alternative free-response receiver operating characteristic analysis to detect HCC were 0.809 (reader 1/2/3/4/5, 0.765/0.798/0.892/0.764/0.827) in the optimal WW (120 HU) and 0.765 (reader 1/2/3/4/5, 0.707/0.769/0.838/0.720/0.791) in the conventional WW (150 HU), and statistically significant difference was observed between them (p < 0.001). Image quality in the optimal WW was superior to those in the conventional WW, and significant difference was seen for some readers (p < 0.041). The optimal WW for detection of HCC was narrower than conventional WW on dynamic contrast-enhanced CT with DLR. Compared with the conventional liver WW, optimal liver WW significantly improved detection performance of HCC., (© 2024. The Author(s).)

Purpose: The quality and bias of annotations by annotators (e.g., radiologists) affect the performance changes in computer-aided detection (CAD) software using machine learning. We hypothesized that the difference in the years of experience in image interpretation among radiologists contributes to annotation variability. In this study, we focused on how the performance of CAD software changes with retraining by incorporating cases annotated by radiologists with varying experience., Methods: We used two types of CAD software for lung nodule detection in chest computed tomography images and cerebral aneurysm detection in magnetic resonance angiography images. Twelve radiologists with different years of experience independently annotated the lesions, and the performance changes were investigated by repeating the retraining of the CAD software twice, with the addition of cases annotated by each radiologist. Additionally, we investigated the effects of retraining using integrated annotations from multiple radiologists., Results: The performance of the CAD software after retraining differed among annotating radiologists. In some cases, the performance was degraded compared to that of the initial software. Retraining using integrated annotations showed different performance trends depending on the target CAD software, notably in cerebral aneurysm detection, where the performance decreased compared to using annotations from a single radiologist., Conclusions: Although the performance of the CAD software after retraining varied among the annotating radiologists, no direct correlation with their experience was found. The performance trends differed according to the type of CAD software used when integrated annotations from multiple radiologists were used., (© 2024. The Author(s).)

This study aimed to investigate the performance of a fine-tuned large language model (LLM) in extracting patients on pretreatment for lung cancer from picture archiving and communication systems (PACS) and comparing it with that of radiologists. Patients whose radiological reports contained the term lung cancer (3111 for training, 124 for validation, and 288 for test) were included in this retrospective study. Based on clinical indication and diagnosis sections of the radiological report (used as input data), they were classified into four groups (used as reference data): group 0 (no lung cancer), group 1 (pretreatment lung cancer present), group 2 (after treatment for lung cancer), and group 3 (planning radiation therapy). Using the training and validation datasets, fine-tuning of the pretrained LLM was conducted ten times. Due to group imbalance, group 2 data were undersampled in the training. The performance of the best-performing model in the validation dataset was assessed in the independent test dataset. For testing purposes, two other radiologists (readers 1 and 2) were also involved in classifying radiological reports. The overall accuracy of the fine-tuned LLM, reader 1, and reader 2 was 0.983, 0.969, and 0.969, respectively. The sensitivity for differentiating group 0/1/2/3 by LLM, reader 1, and reader 2 was 1.000/0.948/0.991/1.000, 0.750/0.879/0.996/1.000, and 1.000/0.931/0.978/1.000, respectively. The time required for classification by LLM, reader 1, and reader 2 was 46s/2539s/1538s, respectively. Fine-tuned LLM effectively extracted patients on pretreatment for lung cancer from PACS with comparable performance to radiologists in a shorter time., (© 2024. The Author(s).)

We aimed to develop a new artificial intelligence software that can automatically extract and measure the volume of white matter hyperintensities (WMHs) in head magnetic resonance imaging (MRI) using only thick-slice fluid-attenuated inversion recovery (FLAIR) sequences from multiple centers. We enrolled 1092 participants in Japan, comprising the thick-slice Private Dataset. Based on 207 randomly selected participants, neuroradiologists annotated WMHs using predefined guidelines. The annotated images of participants were divided into training (n = 138) and test (n = 69) datasets. The WMH segmentation model comprised a U-Net ensemble and was trained using the Private Dataset. Two other models were trained for validation using either both thin- and thick-slice MRI datasets or the thin-slice dataset alone. The voxel-wise Dice similarity coefficient (DSC) was used as the evaluation metric. The model trained using only thick-slice MRI showed a DSC of 0.820 for the test dataset, which is comparable to the accuracy of human readers. The model trained with the additional thin-slice dataset showed only a slightly improved DSC of 0.822. This automatic WMH segmentation model comprising a U-Net ensemble trained on a thick-slice FLAIR MRI dataset is a promising new method. Despite some limitations, this model may be applicable in clinical practice., (© 2024. The Author(s).)

Macrolide antibiotics are biosynthesized via enzymatic modifications, including glycosylation, methylation, and oxidation, after the core macro-lactone ring is generated by a polyketide synthase system. This study explored the diversification of macrolides by combining biosynthetic enzymes and reports an approach to produce unnatural hybrid macrolide antibiotics. The cytochrome (CYP) P450 monooxygenase MycG exhibits bifunctional activity, catalyzing late-stage hydroxylation at C-14 followed by epoxidation at C-12/13 during mycinamicin biosynthesis. The mycinose sugar of mycinamicin serves as a key molecular recognition element for binding to MycG. Thus, we subjected the hybrid macrolide antibiotic 23-O-mycinosyl-20-deoxo-20-dihydro-12,13-deepoxyrosamicin (IZI) to MycG, and confirmed that MycG catalyzed hydroxylation at C-22 and epoxidation at C-12/13 in IZI. In addition, the introduction of mycinose biosynthesis-related genes and mycG into rosamicin-producing Micromonospora rosaria enabled the fermentative production of 22-hydroxylated and 12,13-epoxidized forms of IZI. Interestingly, MycG catalyzed the sequential oxidation of hydroxylation and epoxidation in mycinamicin biosynthesis, but only single reactions in IZI. These findings highlight the potential for expanding the application of the multifunctional P450 monooxygenase MycG for the production of unnatural compounds., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)

Background COVID-19 vaccination-related axillary lymphadenopathy has become an important problem in cancer imaging. Data are needed to update or support imaging guidelines for conducting appropriate follow-up. Purpose To investigate the prevalence, predisposing factors, and MRI characteristics of COVID-19 vaccination-related axillary lymphadenopathy. Materials and Methods Prospectively collected prevaccination and postvaccination chest MRI scans were secondarily analyzed. Participants who underwent two doses of either the Pfizer-BioNTech or Moderna COVID-19 vaccine and chest MRI from June to October 2021 were included. Enlarged axillary lymph nodes were identified on postvaccination MRI scans compared with prevaccination scans. The lymph node diameter, signal intensity with T2-weighted imaging, and apparent diffusion coefficient (ADC) of the largest enlarged lymph nodes were measured. These values were compared between prevaccination and postvaccination MRI by using the Wilcoxon signed-rank test. Results Overall, 433 participants (mean age, 65 years ± 11 [SD]; 300 men and 133 women) were included. The prevalence of axillary lymphadenopathy in participants 1-14 days after vaccination was 65% (30 of 46). Participants with lymphadenopathy were younger than those without lymphadenopathy ( P < .001). Female sex and the Moderna vaccine were predisposing factors ( P = .005 and P = .003, respectively). Five or more enlarged lymph nodes were noted in 2% (eight of 433) of participants. Enlarged lymph nodes greater than or equal to 10 mm in the short axis were noted in 1% (four of 433) of participants. The median signal intensity relative to the muscle on T2-weighted images was 4.0; enlarged lymph nodes demonstrated a higher signal intensity ( P = .002). The median ADC of enlarged lymph nodes after vaccination in 90 participants was 1.1 × 10 -3 mm 2 /sec (range, 0.6-2.0 × 10 -3 mm 2 /sec), thus ADC values remained normal. Conclusion Axillary lymphadenopathy after the second dose of the Pfizer-BioNTech or Moderna COVID-19 vaccines was frequent within 2 weeks after vaccination, was typically less than 10 mm in size, and had a normal apparent diffusion coefficient. © RSNA, 2022.

Flow reactions using an immobilized diphenylprolinol alkyl ether catalyst 2 were investigated in three reactions of α,β-unsaturated aldehydes and nitroalkanes such as nitromethane 3, nitroethanol 10, and nitroalkane 11, bearing two carbonyl groups. Whereas reactions using the corresponding monomer catalyst diphenylprolinol silyl ether 1 were slow, fast reactions were found with the immobilized polymer catalyst 2 in a batch system, and the latter was then applied to a flow system. In the Michael reaction of nitromethane 3, the polymer catalyst showed high reactivity in the initial 30 h and then decreased gradually. Good overall yield (72%) and turnover number (TON, 495) were obtained for a 60 h flow reaction, and the enantioselectivity of the product was excellent throughout. The TONs of domino reactions of nitroethanol 10 and nitroalkane 11, with two carbonyl groups, were 48 and 81, respectively., (© 2022 Wiley-VCH GmbH.)

Background: Diffusion-weighted imaging performed shortly after brain injury has been shown to facilitate visualization of acute corticospinal tract injury known as "pre-Wallerian degeneration.", Objective: The aim of this study was to determine whether diffusion restriction in the corticospinal tract and corpus callosum occurs within the first 2 weeks after birth in neonates with neonatal hypoxic-ischemic encephalopathy., Materials and Methods: We enrolled a consecutive series of 66 infants diagnosed with hypoxic-ischemic encephalopathy who underwent MRI. We evaluated diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values to assess the presence of restricted diffusion in the corticospinal tract and corpus callosum. Next, we compared ADC values in the corticospinal tract and in the splenium and genu of the corpus callosum of infants with abnormal pattern on MRI with those of control infants, who showed a normal pattern on MRI. We attempted to follow all infants with hypoxic-ischemic encephalopathy until 18 months of age and assess them using a standardized neurologic examination., Results: After exclusions, we recruited 25 infants with abnormal MRI and 20 with normal MRI (controls). Among these 45 neonates, pre-Wallerian degeneration was visualized in the corticospinal tract in 10 neonates and in the corpus callosum in 12. The ADC values in the corticospinal tract in the first week were significantly lower than they were in the second week. Infants with pre-Wallerian degeneration in the corticospinal tract showed an unfavorable outcome., Conclusion: Pre-Wallerian degeneration was visualized in the corticospinal tract and corpus callosum and was associated with extensive brain injury caused by hypoxic-ischemic encephalopathy. The changes in signal were observed to evolve over time within the first 2 weeks. The clinical outcome of infants having pre-Wallerian degeneration in the corticospinal tract was unfavorable., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Enantiodivergent one-pot synthesis of biaryls was developed using a catalytic amount of a single chiral source. A domino organocatalyst-mediated enantioselective Michael reaction and aldol condensation provided centrally chiral dihydronaphthalenes with excellent enantioselectivity, from which an enantiodivergent chirality conversion from central-to-axial chirality was achieved. Both enantiomers of biaryls were obtained with excellent enantioselectivity. All transformations can be conducted in a single reaction vessel. A plausible reaction mechanism for the enantiodivergence is proposed., (© 2021 Wiley-VCH GmbH.)

Substituted 9-methyldecalin derivatives containing an all carbon quaternary chiral center were synthesized with excellent enantioselectivity via an organocatalyst-mediated domino reaction. The first reaction is a diphenylprolinol silyl ether-mediated Michael reaction, and the second reaction is an intramolecular aldol reaction. The enantiomerically pure catalyst is involved in both reactions.

Background: Unsupervised learning can discover various unseen abnormalities, relying on large-scale unannotated medical images of healthy subjects. Towards this, unsupervised methods reconstruct a 2D/3D single medical image to detect outliers either in the learned feature space or from high reconstruction loss. However, without considering continuity between multiple adjacent slices, they cannot directly discriminate diseases composed of the accumulation of subtle anatomical anomalies, such as Alzheimer's disease (AD). Moreover, no study has shown how unsupervised anomaly detection is associated with either disease stages, various (i.e., more than two types of) diseases, or multi-sequence magnetic resonance imaging (MRI) scans., Results: We propose unsupervised medical anomaly detection generative adversarial network (MADGAN), a novel two-step method using GAN-based multiple adjacent brain MRI slice reconstruction to detect brain anomalies at different stages on multi-sequence structural MRI: (Reconstruction) Wasserstein loss with Gradient Penalty + 100 [Formula: see text] loss-trained on 3 healthy brain axial MRI slices to reconstruct the next 3 ones-reconstructs unseen healthy/abnormal scans; (Diagnosis) Average [Formula: see text] loss per scan discriminates them, comparing the ground truth/reconstructed slices. For training, we use two different datasets composed of 1133 healthy T1-weighted (T1) and 135 healthy contrast-enhanced T1 (T1c) brain MRI scans for detecting AD and brain metastases/various diseases, respectively. Our self-attention MADGAN can detect AD on T1 scans at a very early stage, mild cognitive impairment (MCI), with area under the curve (AUC) 0.727, and AD at a late stage with AUC 0.894, while detecting brain metastases on T1c scans with AUC 0.921., Conclusions: Similar to physicians' way of performing a diagnosis, using massive healthy training data, our first multiple MRI slice reconstruction approach, MADGAN, can reliably predict the next 3 slices from the previous 3 ones only for unseen healthy images. As the first unsupervised various disease diagnosis, MADGAN can reliably detect the accumulation of subtle anatomical anomalies and hyper-intense enhancing lesions, such as (especially late-stage) AD and brain metastases on multi-sequence MRI scans.

Introduction: Oscillating gradient spin-echo (OGSE) sequences enable acquisitions with shorter diffusion times. There is growing interest in the effect of diffusion time on apparent diffusion coefficient (ADC) values in patients with cancer. However, little evidence exists regarding its usefulness for differentiating between high-grade and low-grade brain tumors. The purpose of this study is to investigate the utility of changes in the ADC value between short and long diffusion times in distinguishing low-grade and high-grade brain tumors., Material and Methods: Eleven patients with high-grade brain tumors and ten patients with low-grade brain tumors were scanned using a 3 T magnetic resonance imaging with diffusion-weighted imaging (DWI) using OGSE and PGSE (effective diffusion time [Δ eff ]: 6.5 ms and 35.2 ms) and b-values of 0 and 1000 s/mm 2 . Using a region of interest (ROI) analysis of the brain tumors, we measured the ADC for two Δeff (ADC Δeff ) values and computed the subtraction ADC (ΔADC = ADC 6.5 ms  - ADC 35.2 ms ) and the relative ADC (ΔADC = (ADC 6.5 ms  - ADC 35.2 ms ) / ADC 35.2 ms  × 100). The maximum values for the subtraction ADC (ΔADC max ) and the relative ADC (rADC max ) on the ROI were compared between low-grade and high-grade tumors using the Wilcoxon rank-sum test. A P-value <.05 was considered significant. The ROIs were also placed in the normal white matter of patients with high- and low-grade brain tumors, and ΔADC max values were determined., Results: High-grade tumors had significantly higher ΔADC max and rADC max than low-grade tumors. The ΔADC max values of the normal white matter were lower than the ΔADC max of high- and low-grade brain tumors., Conclusion: The dependence of ADC values on diffusion time between 6.5 ms and 35.2 ms was stronger in high-grade tumors than in low-grade tumors, suggesting differences in internal tissue structure. This finding highlights the importance of reporting diffusion times in ADC evaluations and might contribute to the grading of brain tumors using DWI., Competing Interests: Declaration of Competing Interest Thorsten Feiweier is an employee of Siemens Healthcare GmbH, Germany. Katsutoshi Murata is and employee of Siemens Healthcare K.K., Japan. All remaining authors declare no conflicts of interest associated with this manuscript., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Perinatal hypoxic-ischemic encephalopathy (HIE) is a major cause of death and disability in infants. Magnetic resonance imaging (MRI) is valuable for predicting the outcome in high-risk neonates. The relationship of pontine and cerebellar injury to outcome has not been explored sufficiently., Purpose: To characterize MRI features of pontine and cerebellar injury and to assess the clinical outcomes of these neonates., Material and Methods: The retrospective study included 59 term neonates (25 girls) examined by MRI using 1.5-T scanner in the first two weeks of life between 2008 and 2017. Involvement of the pons and cerebellum was judged as a high signal intensity on diffusion-weighted image (DWI) and a restricted diffusion on an apparent diffusion coefficient (ADC) map., Results: Pontine involvement was observed in the dorsal portion of pons in eight neonates and cerebellar involvement was observed in dentate nucleus (n = 8), cerebellar vermis (n = 3), and hemisphere (n = 1) in 11 neonates. Combined pontine and cerebellar involvement was observed in eight neonates and only cerebellar involvement in three. The pontine and cerebellar injuries were always associated with very severe brain injury including a basal ganglia/thalamus injury pattern and a total brain injury pattern. In terms of clinical outcome, all but four lost to follow-up, had severe cerebral palsy., Conclusion: Pontine and cerebellar involvement occurred in the dorsal portion of pons and mostly dentate nucleus and was always associated with a more severe brain injury pattern as well as being predictive of major disability.

Purpose: The most severe form of profound asphyxia in neonates is now known as "total brain injury," which forms part of the clinical spectrum of hypoxic-ischemic encephalopathy (HIE). Although the magnetic resonance (MR) imaging features of total brain injury remain to be determined, a widespread hyperintensity of the supratentorial brain, known as the "white cerebrum sign," has been reported in diffusion-weighted images (DWI)., Methods: We examined four neonates who developed severe profound asphyxia., Results: In the first week of life, all neonates showed the white cerebrum sign on DWI. A follow-up of these cases over a period of 1 month revealed diffuse bilateral multicystic encephalomalacia (MCE) as well as shrinkage of the basal ganglia and thalami (BG/T). These MR findings were common to all neonates, and all the neonates had severe adverse clinical outcomes., Conclusion: Neonates, who exhibit the white cerebrum sign on MR imaging due to profound asphyxia, develop major disabilities, and MCE with shrinkage of the BG/T suggests miserable outcomes.

The pot-economical, highly enantioselective synthesis of axially chiral biaryls was developed by using one-pot organocatalyst-mediated domino and aromatization reactions as key steps. The axial information of the precursor, which also has central chirality, was completely inverted in the final biaryls. The inversion of the axial information occurred in the conversion of the central chirality to the axial chirality of an oxidative aromatization step., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Purpose: Flowing blood sometimes appears bright on synthetic T 1 -weighted images, which could be misdiagnosed as a thrombus. This study aimed to investigate the frequency of hyperintensity within cerebral venous sinuses on synthetic MR images and to evaluate the influence of increasing flow rates on signal intensity using a flow phantom., Materials and Methods: Imaging data, including synthetic and conventional MRI scans, from 22 patients were retrospectively analyzed. Signal intensities at eight locations of cerebral venous sinuses on synthetic images were graded using the following three-point scale: 0, "dark vessel"; 1, "hyperintensity within the walls"; and 2, "hyperintensity within the lumen." A phantom with gadolinium solution inside a U-shaped tube was acquired without flow and then with increasing flow rates (60, 100, 200, 300, 400 ml/min)., Results: Considering all sinus locations, the venous signal intensity on synthetic T 1 -weighted images was graded as 2 in 79.8% of the patients. On synthetic T 2 -weighted images, all sinuses were graded as 0. On fluid-attenuated inversion recovery (FLAIR) images, sinuses were almost always graded as 0 (99.4%). In the phantom study, the signal initially became brighter on synthetic T 1 -weighted images as the flow rate increased. Above a certain flow rate, the signal started to decrease., Conclusion: High signal intensity within the cerebral venous sinuses is a frequent finding on synthetic T 1 -weighted images. This corresponds to the hyperintensity noted at certain flow rates in the phantom experiment.

Single nucleotide polymorphisms in Tolloid-like 1 (TLL1) and the expression of TLL1 are known to be closely related to hepatocarcinogenesis after hepatitis C virus elimination or liver fibrosis in patients with nonalcoholic fatty liver disease. TLL1 is a type of matrix metalloprotease and has two isoforms in humans, with the short isoform showing higher activity. However, the functional role of TLL1 in human liver development is unknown. Here, we attempted to elucidate the function of human TLL1 using hepatocyte-like cells generated from human pluripotent stem cells. First, we generated TLL1-knockout human induced pluripotent stem (iPS) cells and found that hepatic differentiation was promoted by TLL1 knockout. Next, we explored TLL1-secreting cells using a model of liver development and identified that kinase insert domain receptor (FLK1)-positive cells (mesodermal cells) highly express TLL1. Finally, to elucidate the mechanism by which TLL1 knockout promotes hepatic differentiation, the expression profiles of transforming growth factor beta ( TGFβ ), a main target gene of TLL1, and its related genes were analyzed in hepatic differentiation. Both the amount of active TGFβ and the expression of TGFβ target genes were decreased by TLL1 knockout. It is known that TGFβ negatively regulates hepatic differentiation. Conclusion: TLL1 appears to negatively regulate hepatic differentiation of human iPS cells by up-regulating TGFβ signaling. Our findings will provide new insight into the function of TLL1 in human liver development., (© 2020 The Authors. Hepatology Communications published by Wiley Periodicals, Inc., on behalf of the American Association for the Study of Liver Diseases.)

A three-pot synthetic method that features the use of an organocatalyst as the key step was developed for the preparation of biaryl atropisomers. The first reaction is an asymmetric domino Michael-Henry reaction catalyzed by diphenylprolinol silyl ether to afford the substituted nitrocyclohexanecarbaldehyde with four stereogenic centers and one defined configuration of a stereogenic axis with excellent enantioselectivity. Removal of the central chirality from the domino products afforded biaryl atropisomers having axial chirality with excellent enantioselectivity., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Purpose: Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are representative disorders of dementia of the elderly and the neuroimaging has contributed to early diagnosis by estimation of alterations of brain volume, blood flow and metabolism. A brain network analysis by MR imaging (MR connectome) is a recently developed technique and can estimate the dysfunction of the brain network in AD and DLB. A graph theory which is a major technique of network analysis is useful for a group study to extract the feature of disorders, but is not necessarily suitable for the disorder differentiation at the individual level. In this investigation, we propose a deep learning technique as an alternative method of the graph analysis for recognition and classification of AD and DLB at the individual subject level., Materials and Methods: Forty-eight brain structural connectivity data of 18 AD, 8 DLB and 22 healthy controls were applied to the machine learning consisting of a six-layer convolution neural network (CNN) model. Estimation of the deep learning model to classify AD, DLB and non-AD/DLB was performed using the 4-fold cross-validation method., Results: The accuracy, average precision and recall of our CNN model were 0.73, 0.78 and 0.73, and the specificity precision and recall were 0.68 and 0.79 in AD, 0.94 and 0.65 in DLB and 0.73 and 0.75 in non-AD/DLB. The triangular probability map of the MR connectome revealed the probability of AD, DLB and non-AD/DLB in each subject., Conclusion: Our preliminary investigation revealed the adaptation of deep learning to the MR connectome and proposed its utility in the differentiation of dementia disorders at the individual subject level.

Quantitative magnetic resonance imaging (MRI) with multislice, multi-echo, and multi-delay acquisition enables simultaneous quantification of R 1 and R 2 relaxation rates, proton density, and the B 1 field in a single acquisition, and requires only about 6 minutes for full-head coverage. Using dedicated SyMRI software, radiologists can generate any contrast-weighted image by manipulating the acquisition parameters, including repetition time, echo time, and inversion time. Moreover, automatic brain tissue segmentation, volumetry, and myelin measurement can also be performed. Using the SyMRI approach, a shorter scan time, an objective examination, and personalized MR imaging parameters can be obtained in daily clinical pediatric imaging. Here we summarize and review the use of SyMRI in imaging of the pediatric brain, including the basic principles of MR quantification along with its features, clinical applications, and limitations., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

Introduction: Oscillating gradient spin-echo (OGSE) sequences can shorten diffusion times by replacing the long-lasting diffusion-sensitizing gradients used in pulsed gradient spin-echo (PGSE) methods with rapidly oscillating gradients. To obtain information regarding the internal structure of choroid plexus cysts that appear hyperintense on diffusion-weighted imaging (DWI), we investigated the apparent diffusion coefficient (ADC) values acquired with a shorter diffusion time using an OGSE sequence., Material and Methods: Twenty-seven patients with choroid plexus cysts were scanned using a 3 T magnetic resonance scanner. DWI was performed with both OGSE and PGSE, with effective diffusion times (Δ eff ) of 6.5 and 35.2 ms, respectively. ADC values for choroid plexus cysts, white matter (WM), and cerebrospinal fluid (CSF) were measured. The ADC values obtained with the shorter and longer diffusion times were compared using the Wilcoxon signed-rank test. P < .05 was considered significant., Results: The ADC values of choroid plexus cysts and WM were significantly higher at the Δ eff of 6.5 ms on OGSE than with the Δ eff of 35.2 ms on PGSE. The ADC values of CSF were significantly lower at the Δ eff of 6.5 ms on OGSE than with the Δ eff of 35.2 ms on PGSE. The ADC values of choroid plexus cysts were lower than the ADC values of CSF with Δ eff of 35.2 and 6.5 ms., Conclusions: The dependence of ADC values on the diffusion time in choroid plexus cysts suggested spatially restricted diffusion. In measurements obtained with short diffusion times, the lower ADC values for choroid plexus cysts in comparison with the CSF indicated the presence of spatially restricted diffusion and increased cyst viscosity., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background and Purpose: Synthetic FLAIR images are of lower quality than conventional FLAIR images. Here, we aimed to improve the synthetic FLAIR image quality using deep learning with pixel-by-pixel translation through conditional generative adversarial network training., Materials and Methods: Forty patients with MS were prospectively included and scanned (3T) to acquire synthetic MR imaging and conventional FLAIR images. Synthetic FLAIR images were created with the SyMRI software. Acquired data were divided into 30 training and 10 test datasets. A conditional generative adversarial network was trained to generate improved FLAIR images from raw synthetic MR imaging data using conventional FLAIR images as targets. The peak signal-to-noise ratio, normalized root mean square error, and the Dice index of MS lesion maps were calculated for synthetic and deep learning FLAIR images against conventional FLAIR images, respectively. Lesion conspicuity and the existence of artifacts were visually assessed., Results: The peak signal-to-noise ratio and normalized root mean square error were significantly higher and lower, respectively, in generated-versus-synthetic FLAIR images in aggregate intracranial tissues and all tissue segments (all P < .001). The Dice index of lesion maps and visual lesion conspicuity were comparable between generated and synthetic FLAIR images ( P = 1 and .59, respectively). Generated FLAIR images showed fewer granular artifacts ( P = .003) and swelling artifacts (in all cases) than synthetic FLAIR images., Conclusions: Using deep learning, we improved the synthetic FLAIR image quality by generating FLAIR images that have contrast closer to that of conventional FLAIR images and fewer granular and swelling artifacts, while preserving the lesion contrast., (© 2019 by American Journal of Neuroradiology.)

Background and Purpose: The effect of gadolinium on the estimation of myelin has not been reported. The aim of the current study was to investigate the effects of gadolinium on automatic myelin and brain tissue volumetry via quantitative synthetic MR imaging., Materials and Methods: The study included 36 patients who were referred for brain metastases screening, and quantitative synthetic MR imaging data before and after gadolinium-based contrast agent administration were analyzed retrospectively. Brain metastases were detected in 17 patients. WM volume, GM volume, CSF volume, non-WM/GM/CSF volume, myelin volume, brain parenchymal volume, myelin fraction (myelin volume/brain parenchymal volume), and intracranial volume were estimated. T1 and T2 relaxation times, proton density, and myelin partial volume per voxel averaged across the brain parenchyma were also analyzed., Results: In patients with and without metastases after gadolinium-based contrast agent administration, measurements of WM and myelin volumes, and myelin fraction were significantly increased (+26.65 and +29.42 mL, +10.14 and +12.46 mL, +0.88% and +1.09%, respectively), whereas measurements of GM, CSF, brain parenchymal, and intracranial volumes were significantly decreased (-36.23 and -34.49 mL, -20.77 and -18.94 mL, -6.76 and -2.84 mL, -27.41 and -21.84 mL, respectively). Non-WM/GM/CSF volume did not show a significant change. T1, T2, and proton density were significantly decreased (-51.34 and -46.84 ms, -2.67 and -4.70 ms, -1.05%, and -1.28%, respectively) after gadolinium-based contrast agent administration, whereas measurements of myelin partial volume were significantly increased (+0.78% and +0.75%, respectively)., Conclusions: Gadolinium had a significant effect on the automatic calculation of myelin and brain tissue volumes using quantitative synthetic MR imaging, which can be explained by decreases in T1, T2, and proton density., (© 2019 by American Journal of Neuroradiology.)

Magnetization transfer (MT) imaging has been widely used for estimating myelin content in the brain. Recently, two other approaches, namely simultaneous tissue relaxometry of R 1 and R 2 relaxation rates and proton density (SyMRI) and the ratio of T 1 -weighted to T 2 -weighted images (T 1 w/T 2 w ratio), were also proposed as methods for measuring myelin. SyMRI and MT imaging have been reported to correlate well with actual myelin by histology. However, for T 1 w/T 2 w ratio, such evidence is limited. In 20 healthy adults, we examined the correlation between these three methods, using MT saturation index (MT sat ) for MT imaging. After calibration, white matter (WM) to gray matter (GM) contrast was the highest for SyMRI among these three metrics. Even though SyMRI and MT sat showed strong correlation in the WM (r = 0.72), only weak correlation was found between T 1 w/T 2 w and SyMRI (r = 0.45) or MT sat (r = 0.38) (correlation coefficients significantly different from each other, with p values < 0.001). In subcortical and cortical GM, these measurements showed moderate to strong correlations to each other (r = 0.54 to 0.78). In conclusion, the high correlation between SyMRI and MT sat indicates that both methods are similarly suited to measure myelin in the WM, whereas T 1 w/T 2 w ratio may be less optimal.

We report two cases of pathologically proven intracranial epidermoid cysts. Both cases were scanned with diffusion-weighted imaging using pulsed gradient spin-echo (PGSE) and oscillating gradient spin-echo (OGSE; 50 Hz) prototype sequences with diffusion times of 47.3 ms and 8.5 ms, respectively. The apparent diffusion coefficient measured by OGSE was higher than that measured by PGSE, indicating the spatial restriction of water diffusion in the laminated keratin layers within the cyst as demonstrated by histopathology.

Purpose: Compared with the conventional pulsed gradient spin-echo (PGSE) sequence, diffusion-weighted imaging (DWI) with the oscillating gradient spin-echo (OGSE) sequence can shorten the diffusion time by changing the frequency. The purpose was to investigate whether n-alkanes are suitable as isotropic phantoms for estimating the diffusion coefficient with the OGSE sequence., Materials and Methods: We investigated changes in the apparent diffusion coefficient (ADC) due to differences in the viscosities of nine n-alkane phantoms with different numbers of carbon atoms from C 8 H 18 to C 16 H 34 using OGSE and PGSE sequences at 21 °C. Effective diffusion times of 4.3, 5.1, 6.5, 9.3, 20, 40, and 60 ms were used. The T 2 relaxation times of each n-alkane phantom were measured using quantitative synthetic magnetic resonance imaging (MRI). Circular regions of interest were placed manually within the alkane phantoms on ADC and T 2 maps., Results: In each alkane phantom, changes in mean ADC values were almost constant with changes in diffusion times. Viscosities and ADC values showed inverse proportionality, as expected theoretically., Conclusion: The ADC values of alkanes do not depend on diffusion times. The n-alkanes can be useful phantoms for assessing the accuracy of clinical protocols of DWI with the OGSE sequence.

Background: Pseudonormalization of diffusion-weighted magnetic resonance imaging (MRI) can lead to underestimation of brain injury in newborns with hypoxic-ischemic encephalopathy (HIE), posing a significant problem. We have noticed that some neonates show pseudonormalization negativity on diffusion-weighted imaging., Objective: To compare pseudonormalization negativity with clinical outcomes., Materials and Methods: Seventeen term neonates with moderate or severe HIE underwent therapeutic hypothermia. They were examined by MRI twice at mean ages of 3 days and 10 days. We evaluated the presence of restricted diffusion, and also the presence or absence of pseudonormalization, by diffusion-weighted imaging at the time of the second MRI, and correlated the results with clinical outcome., Results: DWI demonstrated no abnormality in seven neonates. Among the 10 neonates with abnormal diffusion-weighted imaging findings, 2 were positive for pseudonormalization and 8 were negative. Among neonates with normal diffusion-weighted imaging findings and with positivity for pseudonormalization, none had major disability. Among the eight neonates with pseudonormalization negativity, all but one, who was lost to follow-up, had major disability., Conclusion: Abnormal diffusion-weighted imaging with pseudonormalization negativity might be predictive of severe brain injury and major disability. The second-week MRI is important for the judgment of pseudonormalization.

Enantioselective total synthesis of estradiol methyl ether has been accomplished in a pot-economical manner using five reaction vessels and four purifications. The key reaction is a diphenylprolinol silyl ether mediated domino Michael/aldol reaction to afford bicyclo[4.3.0]nonane derivatives, containing the A, C, and D rings of steroids, as a single isomer with excellent enantioselectivity. Six reactions such as oxidation, hydrogenation, formation of acid chloride, Friedel-Crafts reaction, deprotection, and reduction can be carried out in the last one-pot sequence., (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The role of the thalamus in high-level cognition-attention, working memory (WM), rule-based learning, and decision making-remains poorly understood, especially in comparison to that of cortical frontoparietal networks [1-3]. Studies of visual thalamus have revealed important roles for pulvinar and lateral geniculate nucleus in visuospatial perception and attention [4-10] and for mediodorsal thalamus in oculomotor control [11]. Ventrolateral thalamus contains subdivisions devoted to action control as part of a circuit involving the basal ganglia [12, 13] and motor, premotor, and prefrontal cortices [14], whereas anterior thalamus forms a memory network in connection with the hippocampus [15]. This connectivity profile suggests that ventrolateral and anterior thalamus may represent a nexus between mnemonic and control functions, such as action or attentional selection. Here, we characterize the role of thalamus in the interplay between memory and visual attention. We show that ventrolateral lesions impair the influence of WM representations on attentional deployment. A subsequent fMRI study in healthy volunteers demonstrates involvement of ventrolateral and, notably, anterior thalamus in biasing attention through WM contents. To further characterize the memory types used by the thalamus to bias attention, we performed a second fMRI study that involved learning of stimulus-stimulus associations and their retrieval from long-term memory to optimize attention in search. Responses in ventrolateral and anterior thalamic nuclei tracked learning of the predictiveness of these abstract associations and their use in directing attention. These findings demonstrate a key role for human thalamus in higher-level cognition, notably, in mnemonic biasing of attention., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

Random mutations were introduced into recombinant barley beta-amylase by modified PCR to increase its thermostability. Two clones were obtained. One was found to have a change of Ser-351 to Pro and another, a change of Ala-376 to Ser, and 2.3 degrees C and 1.0 degrees C increases, respectively, in the thermostabilities compared with that of native recombinant beta-amylase.