Prevalence and associated factors of low vigor in patients living with HIV and hemophilia in Japan: A cross-sectional observational study.

People living with human immunodeficiency virus (HIV) are at high risk of mental health problems. However, little is known about this risk in HIV-infected patients with hemophilia (HPH) who contracted the virus through blood products. This cross-sectional, observational study assessed patients' mood states and the factors associated with them among Japanese HPH to evaluate the need for psychosocial support. HPH completed self-administered questionnaires (Profile of Mood States [POMS] and General Health Questionnaire-28), neuropsychological tests, and brain magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography/computerized tomography scans. HIV-infected patients with no hemophilia (HPnH) completed POMS and neuropsychological tests. Socio-demographic characteristics and HIV- and hemophilia-related data were obtained from participants' medical records and interviews. A Mann-Whitney U test and chi-squared analyses were conducted. Fifty-six HPH and 388 HPnH completed the questionnaires and neuropsychological tests. HPH had a significantly lower prevalence of tension-anxiety (HPH, 7%; HPnH, 18%; p = 0.049) and a significantly higher prevalence of low vigor (HPH, 63%; HPnH, 32%; p < 0.001). Low vigor in HPH was significantly associated with impaired executive function (low vigor, 66%; high vigor, 33%; p = 0.019) and a social dysfunction score ≥ 3 (moderate; low vigor, 26%; high vigor, 5%; p = 0.047). Our results highlight the high prevalence of low vigor among HPH, leading to impairments in executive and social functions. Therefore, healthcare workers need to pay attention to the vigor, executive function, and social function of HPH.

Assessment of skeletal muscle using deep learning on low-dose CT images.

The visceral fat area obtained by computed tomography (CT) at the navel level is clinically used as an indicator of visceral fat obesity in Japan. Analysis of skeletal muscle mass using CT images at the navel level may potentially support concurrent assessment of sarcopenia and sarcopenic obesity. The purpose of this study was to assess the performance of deep learning models (DLMs) for skeletal muscle mass measurement using low-dose abdominal CT. The primary dataset used in this study included 11,494 low-dose abdominal CT images at navel level acquired in 7,370 subjects for metabolic syndrome screening. The publicly available Cancer Imaging Archive (TCIA) dataset, including 5,801 abdominal CT images, was used as a complementary dataset. For abdominal CT image segmentation, we used the SegU-net DLM with different filter size and hierarchical depth. The segmentation accuracy was assessed by measuring the dice similarity coefficient (DSC), cross-sectional area (CSA) error, and Bland-Altman plots. The proposed DLM achieved a DSC of 0.992 ± 0.012, a CSA error of 0.41 ± 1.89%, and a Bland-Altman percent difference of -0.1 ± 3.8%. The proposed DLM was able to automatically segment skeletal muscle mass measurements from low-dose abdominal CT with high accuracy.

Different hemodynamics of basal ganglia between moyamoya and non-moyamoya diseases using intravoxel incoherent motion imaging and single-photon emission computed tomography.

BACKGROUND: Moyamoya disease (MMD) and non-MMD have different pathogenesis, clinical presentation, and treatment policy. PURPOSE: To identify differences in hemodynamics between MMD and non-MMD using intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT). MATERIAL AND METHODS: Patients who had undergone 99mTc-ECD or 123I-IMP SPECT, and IVIM imaging were retrospectively studied. IVIM imaging was acquired using six different b-values. Cerebral blood flow ratio (CBFR) in the basal ganglia was calculated using a standardized volume-of-interest template. The cerebellum was used as a reference region. IVIM perfusion fraction (f) was obtained using a two-step fitting algorithm. Elliptical regions of interest were placed in bilateral basal ganglia on the IVIM f map. Patients were classified into MMD and non-MMD groups. The correlation between CBFR and mean IVIM f (fmean) in the basal ganglia was evaluated using Spearman's rank correlation coefficient. RESULTS: In total, 20 patients with MMD and 28 non-MMD patients were analyzed. No significant differences in fmean were observed among MMD, affected hemisphere with non-MMD (non-MMDaff), and unaffected hemispheres with non-MMD (non-MMDunaff). A negative correlation was seen between fmean and CBFR in the MMD group (r = -0.40, P = 0.0108), but not in the non-MMD group (non-MMDaff, r = 0.07, P = 0.69; non-MMDunaff, r = -0.22, P = 0.29). No significant differences were found among MMD and non-MMD patients, irrespective of SPECT tracers. CONCLUSION: The combination of IVIM MRI and SPECT appears to allow non-invasive identification of differences in hemodynamics between MMD and non-MMD.

Current status and challenges of percutaneous vertebroplasty (PVP).

A narrative review regarding percutaneous vertebroplasty (PVP) for osteoporotic vertebral fracture (OVF) is provided herein, addressing the epidemic of OVF in Japan, the latest response to the criticism of PVP for OVFs, the indications and potential risks of PVP for OVFs, and a future perspective for PVP. Each year in Japan, approximately 32,000 patients aged 55 years or older suffer from chronic low back pain for several months to several years due to a compression fracture. PVP is one of the surgical treatments for an OVF, and it is less invasive compared to the traditional open surgery. PVP is suitable for OVF patients who have difficulty walking as assessed by the modified Yokoyama's activities of daily living (ADL) scoring system, and for patients with Kummell's disease diagnosed by CT and MRI examinations. Serious adverse events related to PVP occur in 1.1-3.3% of the cases, but direct deaths from PVP are extremely rare at less than 1%. Recent studies demonstrated that OVF patients treated with PVP are less likely to die after the treatment than non-surgically treated patients, which conflicts with the Cochran reviews' conclusion not supporting PVP for OVFs. Novel robotic systems and procedure-support devices are being developed, providing a next step toward fully automated PVP procedures.

Analysis of "visible in retrospect" to monitor false-negative findings in radiological reports.

PURPOSE: False-negative findings in radiological reports can lead to serious adverse patient outcomes. We determined the frequency and tendency of false-negative findings in radiological reports by searching for words related to "visible in retrospect". METHODS: In the period of 34 months, we extracted radiological reports containing words related to "visible in retrospect". Of these reports, we extracted false-negative findings that were not described in past reports and were first detected retrospectively. Misinterpretations were excluded. The occurrences of the terms that we identified were analyzed by all examinations, modality, month, and anatomical and lesion classifications were analyzed. RESULTS: Of the 135,251 examinations, 941 reports (0.71%) with 962 findings were detected, with an average of 1.4 findings per business day. By modality, 713 of 81,899 (0.87%) CT examinations, 208 of 36,174 (0.57%) MR, 34 of 9,585 (0.35%) FDG-PET-CT, 2 of 2,258 (0.09%) digital radiography, and 5 of 5,335 (0.09%) other nuclear medicine examinations were found. By anatomical classification, there were 383 (40%) in chest, 353 (37%) in abdomen, 162 (17%) in head, 42 (4.4%) in face and neck, 9 (0.93%) in extremity, and 13 (1.4%) in others. By lesion classification, we identified 665 (69%) for localized lesion, 170 (18%) for vascular lesion, 83 (8.6%) for inflammatory lesion, 14 (1.5%) for traumatic lesion, 12 (1.2%) for organ dysfunction, 11 (1.1%) for degenerative lesion, and 7 (0.7%) for the others. Notable high-frequency specific site diseases by modality were 210 (22%) of localized lesions in lung on CT. CONCLUSION: Our results demonstrated that missed lung localized lesions on CT, which account for about a fifth of false-negative findings, were the most common false-negative finding.

Right adrenal vein identification using unenhanced magnetic resonance imaging.

Purpose: Unenhanced magnetic resonance imaging (MRI) is known to be useful in characterizing adrenal adenomas through the implementation of in-phase (IPI) and opposed-phase imaging (OPI) based on chemical shift artifacts. However, whether unenhanced MRI can contribute to the identification of right adrenal vein (RAV) remains unclear. The aim of this study was to evaluate the feasibility of unenhanced MRI for the identification of RAV. Material and methods: This retrospective study reviewed 30 patients (16 men; median age 60 years; range 34-76 years) who underwent MRI and subsequent adrenal venous sampling (AVS). Chemical shift MRI was acquired using echo times of 2.3 ms (OPI) and 4.6 ms (IPI) with a slice thickness of 3 mm and a gap of 1 mm. T2-weighted imaging (T2WI) was also performed. Identification of RAVs was performed by 2 independent radiologists. Inter-observer agreement on a 3-point rating scale was evaluated using κ statistics. The identification rate of RAVs was compared between OPI, IPI, and T2WI using McNemar's test. Results: Good inter-observer agreement was found for the OPI (κ = 0.744), whereas fair agreement was obtained for both other sequences (IPI: κ = 0.375; T2WI: 0.348). For both raters, the identification rate of RAVs was higher with OPI (36/60; 60.0%) than with other sequences (IPI: 16/60, 26.7%; T2WI: 9/60, 15.0%; p < 0.05, each). Conclusions: OPI may play a screening role in the identification of RAVs preceding AVS, which could reduce the required radiation exposure and doses of contrast agent.

The usefulness of vertebral needle targeting simulation training system using ray-summation imaging: experimental study.

PURPOSE: Using the multi-detector computed tomography and related three-dimensional imaging technology, we developed a vertebral needle targeting simulation training system named spinal needling intervention practice using ray-summation imaging (SNIPURS). Herein, we assessed the utility of SNIPURS by evaluating changes in the learning curves of SNIPURS trainees. METHODS: Twenty-one examinees were enrolled: seven experienced operators (expert group), seven trainees with coaching (coaching group), and seven trainees without coaching (non-coaching group). They performed six tests of vertebral needle targeting simulation on the workstation-generated spinal ray-summation images of six patients with vertebral fractures. In each test, they determined the bilateral trans-pedicular puncture points and angles on two thoracic and two lumbar vertebrae on ray-summation imaging (i.e., 8 simulations per test). The coaching group received coaching by a trainer after Tests 1 and 4, while the others did not. Scores were given based on the trans-pedicular pathway (1 point) or not (0 point). Eight virtual needles were evaluated in each of Tests 1-6. RESULTS: Among the three groups, the expert group had the highest average scores on Tests 1-4 (expert: 3.86, 6.57, 7.43, and 7.57; coaching: 1.86, 6.14, 6, and 6.29; and non-coaching: 1.14, 4.14, 4.71, and 4.86). The coaching group's scores caught up with the expert groups' average scores on Tests 5 and 6, whereas those of the non-coaching group did not (expert and coaching: 7.86 and 8.00, non-coaching: 5.86 and 7.14). All examinees in the expert and coaching groups achieved a perfect score on the final Test 6, whereas three of the seven non-coaching trainees did not. CONCLUSION: SNIPURS might be suitable for vertebral needle targeting training. The coaching provided during SNIPURS training helped the trainees to acquire the spinal puncture techniques in PVP.

Unusual imaging characteristics of cystic meningioma in cerebellopontine angle.

We report a case of cystic meningioma at the left cerebellopontine angle (CPA). Magnetic resonance imaging demonstrated both solid and cystic components in the tumor. The cystic component appeared slightly hyperintense compared to cerebrospinal fluid on fluid-attenuated inversion recovery (FLAIR) imaging. A hypointense tubular structure was identified in the cystic component on 3D driven equilibrium sequencing. These imaging findings are unusual for cystic meningioma. However, awareness of these unusual imaging features is important to determine appropriate treatment strategies although cystic meningioma at the CPA is extremely rare.

Preoperative Prediction of Intracranial Meningioma Grade Using Conventional CT and MRI.

Objective Preoperative diagnosis of tumor grade can assist in treatment-related decision-making for patients with intracranial meningioma. This study aimed to distinguish between high-grade and low-grade meningiomas using conventional CT and MRI. Methodology We retrospectively analyzed 173 consecutive patients with intracranial meningioma (149 low-grade and 24 high-grade tumors) who were treated surgically at the National Hospital Organization Kyushu Medical Center from 2008 to 2020. Clinical and radiological features, including tumor doubling time (Td) and relative growth rate (RGR), were compared between low-grade and high-grade meningiomas. Results Multivariate logistic regression analysis showed that symptomatic tumor (p=0.001), non-skull base location (p=0.006), irregular tumor shape (p=0.043), tumor heterogeneity (p=0.025), and peritumoral brain edema (p=0.003) were independent predictors of high-grade meningioma. In 53 patients who underwent surgery because of tumor progression, progression to symptoms (p=0.027), intratumoral heterogeneity (p<0.001), peritumoral brain edema (p=0.001), larger tumor volume (p=0.005), shorter Td (p<0.001), and higher RGR (P<0.001) were significantly associated with high-grade meningioma. Receiver operating characteristics (ROC) curve analysis showed that the optimal Td and annual RGR cut-off values to distinguish high-grade from low-grade meningioma were 460.5 days and 73.2%, respectively (100% sensitivity and 78.6% specificity). Conclusion Based on our findings, conventional CT and MRI are useful methods to predict meningioma grades before surgery. High-grade lesions are associated with non-skull base location, irregular tumor shape, intratumoral heterogeneity, and peritumoral brain edema. High-grade meningioma should be suspected in tumors that exhibit Td <460.5 days or annual RGR >73.2% or those that develop intratumoral heterogeneity or surrounding brain edema on surveillance imaging.

Validity of the γ-Ray Evaluation with iodoamphetamine for Cerebral Blood Flow Assessment (REICA) method for quantification of cerebral blood flow including acetazolamide challenge test.

OBJECTIVE: The γ-Ray Evaluation with iodoamphetamine for Cerebral Blood Flow Assessment (REICA) is a new method for quantifying cerebral blood flow (CBF) using single-photon emission computed tomography (SPECT) and [123I]N-isopropyl-p-iodoamphetamine (123I-IMP). The present study aimed to validate the REICA method using data including acetazolamide challenge test. METHODS: The REICA and Graph-Plot (GP) methods were used to calculate mean CBF (mCBF) for 92 acquisitions (rest: 57, stress: 35) and cerebrovascular reactivity (CVR) in 33 patients. To obtain stress data, 15 mg/kg of acetazolamide was injected intravenously 10 min before the administration of 123I-IMP, and blood samples were collected under the same conditions as rest data. The reference standard was the Autoradiograph (ARG) method using arterial blood sampling, and the accuracy of the REICA method was analyzed by comparing it with each method. RESULTS: For mCBF, the correlation coefficients (r) were 0.792 for the REICA method and 0.636 for the GP method. For CVR, r values were 0.660 for the REICA method and 0.578 for the GP method. In both acquisitions, the REICA method had a stronger correlation with the ARG method than the GP method. For mCBF, there was a significant difference in the correlation coefficient between the two correlation coefficients (p < 0.01). CONCLUSIONS: The REICA method was more accurate than the GP method in quantifying CBF and closer to the ARG method. The REICA method, which is a noninvasive method of cerebral blood flow quantification using 123I-IMP, has great medical usefulness.

Unilateral agenesis of internal carotid artery with interparaclinoid and contralateral carotid-anterior cerebral artery anastomoses diagnosed by magnetic resonance angiography: a case report.

PURPOSE: Unilateral agenesis of the internal carotid artery (ICA) is a rare anatomical variant. We identified a case of unilateral ICA agenesis with interparaclinoid and contralateral carotid-ACA anastomoses. METHODS: A 65-year-old female with a long history of depressive episodes underwent MR imaging including MR angiography at National Hospital Organization Kyushu Medical Center. MR imaging was performed using a 3.0-T MR scanner to rule out vascular Parkinsonism, although drug-induced Parkinsonism was suspected from her medical history. RESULTS: The proximal left ICA was not visible on MR angiography, and an anterior communicating artery (ACoA) aneurysm was identified. The left middle cerebral artery was supplied from the right ICA via an interparaclinoid anastomosis. This interparaclinoid anastomosis showed no communication with the basilar, posterior communicating, or posterior cerebral arteries. A communicating artery connecting the interparaclinoid anastomosis and anterior cerebral artery (ACA) branched off from the presumed transition point between the interparaclinoid anastomosis and left ICA. Both right and left ophthalmic arteries (OAs) originated from the clinoid segment of the ICA. The communicating artery connecting the interparaclinoid anastomosis and ACA arose proximal to the left OA, and the communicating artery was identified as the carotid-ACA anastomosis. CONCLUSION: Neuroradiologists, physicians, and neurosurgeons need to be aware of this extremely unusual anatomical variant to determine appropriate treatment strategies in cases of aneurysmal growth or anterior cranial base surgery.

Accuracy of vertebral puncture in percutaneous vertebroplasty.

PURPOSE: To clarify the accuracy of vertebral puncture of the vertebral tertile area needling (VETERAN) method puncturing the pedicle superimposed on one-third of the width between the lateral vertebral line to the contralateral medial lamina line compared with Cathelin-needle-assisted puncture (CAP) method puncturing using the Cathelin needle as a guide in percutaneous vertebroplasty. MATERIALS AND METHODS: 449 punctures by CAP method and 125 punctures by VETERAN method were enrolled. We compared the puncture accuracy of both methods. We estimated a vertebral estimated tilting ratio (VET-ratio) defined as ratio of the distance between the lateral vertebral line and the contralateral medial laminal line to the distance between the vertebral lateral line and the puncture point measured by computed tomography. We also estimated the procedural items and clinical outcomes. RESULTS: VETERAN method with 100% of punctures within safe zone (cortical breaches within 2 mm) had significantly higher accuracy than CAP method with 97.8% (p < 0.01) for the 2 mm incremental evaluation. No cases with a VET-ratio of 36% or less had cortical breaches. VETERAN method had shorter operative time per puncture (p < 0.01) and exposure time per puncture (p < 0.05). CONCLUSION: VETERAN method reduced the occurrence of the inaccurate puncture, operative times, and exposure times. A VET-ratio with 36% or less is associated with a safe puncture using VETERAN method.

Right entorhinal cortical thickness is associated with Mini-Mental State Examination scores from multi-country datasets using MRI.

PURPOSE: To discover common biomarkers correlating with the Mini-Mental State Examination (MMSE) scores from multi-country MRI datasets. METHODS: The first dataset comprised 112 subjects (49 men, 63 women; range, 46-94 years) at the National Hospital Organization Kyushu Medical Center. A second dataset comprised 300 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (177 men, 123 women; range, 57-91 years). Three-dimensional T1-weighted MR images were collected from both datasets. In total, 14 deep gray matter volumes and 70 cortical thicknesses were obtained from MR images using FreeSurfer software. Total hippocampal volume and the ratio of hippocampus to cerebral volume were also calculated. Correlations between each variable and MMSE scores were assessed using Pearson's correlation coefficient. Parameters with moderate correlation coefficients (r > 0.3) from each dataset were determined as independent variables and evaluated using general linear model (GLM) analyses. RESULTS: In Pearson's correlation coefficient, total and bilateral hippocampal volumes, right amygdala volume, and right entorhinal cortex (ERC) thickness showed moderate correlation coefficients (r > 0.3) with MMSE scores from the first dataset. The ADNI dataset showed moderate correlations with MMSE scores in more variables, including bilateral ERC thickness and hippocampal volume. GLM analysis revealed that right ERC thickness correlated significantly with MMSE score in both datasets. Cortical thicknesses of the left parahippocampal gyrus, left inferior parietal lobe, and right fusiform gyrus also significantly correlated with MMSE score in the ADNI dataset (p < 0.05). CONCLUSION: A positive correlation between right ERC thickness and MMSE score was identified from multi-country datasets.

A fundamental study assessing the generalized fitting method in conjunction with every possible coalition of N-combinations (G-EPOC) using the appendicitis detection task of computed tomography.

PURPOSE: Increased use of deep learning (DL) in medical imaging diagnoses has led to more frequent use of 10-fold cross-validation (10-CV) for the evaluation of the performance of DL. To eliminate some of the (10-fold) repetitive processing in 10-CV, we proposed a "generalized fitting method in conjunction with every possible coalition of N-combinations (G-EPOC)", to estimate the range of the mean accuracy of 10-CV using less than 10 results of 10-CV. MATERIAL AND METHODS: G-EPOC was executed as follows. We first provided (2N-1) coalition subsets using a specified N, which was 9 or less, out of 10 result datasets of 10-CV. We then obtained the estimation range of the accuracy by applying those subsets to the distribution fitting twice using a combination of normal, binominal, or Poisson distributions. Using datasets of 10-CVs acquired from the practical detection task of the appendicitis on CT by DL, we scored the estimation success rates if the range provided by G-EPOC included the true accuracy. RESULTS: G-EPOC successfully estimated the range of the mean accuracy by 10-CV at over 95% rates for datasets with N assigned as 2 to 9. CONCLUSIONS: G-EPOC will help lessen the consumption of time and computer resources in the development of computerbased diagnoses in medical imaging and could become an option for the selection of a reasonable K value in K-CV.

Identification of predictors for mini-mental state examination and revised Hasegawa's Dementia Scale scores using MR-based brain morphometry.

PURPOSE: The early detection of cognitive function decline is crucial to help manage or slow the progression of symptoms. The Mini-Mental State Examination (MMSE) and revised Hasegawa's Dementia Scale (HDS-R) are widely used in screening for cognitive impairment. The purpose of this study was to explore common predictors of the two different cognitive testing systems using MR-based brain morphometry. MATERIALS AND METHODS: This retrospective study included 200 subjects with clinical suspicion of cognitive impairment who underwent 3D T1-weighted MRI at our institution between February 2019 and August 2020. Variables related to the volume of deep gray matter and 70 cortical thicknesses were obtained from the MR images using voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) and FreeSurfer software. The correlation between each variable including age and MMSE/HDS-R scores was evaluated using uni- and multi-variate logistic regression analyses. RESULTS: In univariate analysis, parameters include hippocampal volume and bilateral entorhinal cortex (ERC) thickness showed moderate correlation coefficients with both MMSE and HDS-R scores. Multivariate analysis demonstrated the right ERC thickness was the common parameter which significantly correlates with both MMSE and HDS-R scores (p < 0.05). CONCLUSION: Right ERC thickness appears to offer a useful predictive biomarker for both MMSE and HDS-R scores.

MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction.

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.

Differentiating Dementia with Lewy Bodies and Alzheimer's Disease by Deep Learning to Structural MRI.

BACKGROUND AND PURPOSE: Dementia with Lewy bodies (DLB) is the second most prevalent cause of degenerative dementia next to Alzheimer's disease (AD). Though current DLB diagnostic criteria employ several indicative biomarkers, relative preservation of the medial temporal lobe as revealed by structural MRI suffers from low sensitivity and specificity, making them unreliable as sole supporting biomarkers. In this study, we investigated how a deep learning approach would be able to differentiate DLB from AD with structural MRI data. METHODS: Two-hundred and eight patients (101 DLB, 69 AD, and 38 controls) participated in this retrospective study. Gray matter images were extracted using voxel-based morphometry (VBM). In order to compare the conventional statistical analysis with deep-learning feature extraction, we built a classification model for DLB and AD with a residual neural network (ResNet) type of convolutional neural network architecture, which is one of the deep learning models. The anatomically standardized gray matter images extracted in the same way as for the VBM process were used as inputs, and the classification performance achieved by our model was evaluated. RESULTS: Conventional statistical analysis detected no significant atrophy other than fine differences on the middle temporal pole and hippocampal regions. The feature extracted by the deep learning method differentiated DLB from AD with 79.15％ accuracy compared to the 68.41% of the conventional method. CONCLUSIONS: Our results confirmed that the deep learning method with gray matter images can detect fine differences between DLB and AD that may be underestimated by the conventional method.

A practical system that enables physicians to respond expeditiously to significant unexpected findings (SUFs) in radiological reports.

PURPOSE: To demonstrate effectiveness of our present radiological report check flowchart enabling physicians to respond to significant unexpected findings (SUFs), by comparing the response periods from the examination date to the action date on untreated SUFs between the previous and present versions of our flowchart. METHODS: In the flowchart's previous version used February-October 2019, SUFs, which were notified by email, were audited every month. The physician received a phone call and was asked to act on the untreated SUF. In the flowchart's present version used from November 2019 to May 2020, SUFs were audited every 2 weeks. The physician and his/her chief were asked to return a written response to the untreated SUF. We evaluated the difference in the response periods between the previous and present versions of the flowchart. RESULTS: With the previous flowchart's use, untreated SUFs were 43 of 229 SUFs (18.8%) with the present flowchart untreated SUFs were 22 of 130 SUFs (16.9%). All SUFs in both periods were eventually responded. The present flowchart (median/range, 25/11-70 days) significantly had shorter response periods than the previous flowchart (70/16-290 days) (p < 0.0001). CONCLUSION: The present flowchart employing a shortened primary audit interval, a written response, and the department chief's intervention, helped reduce the response periods.

Safety and Efficacy of Percutaneous Vertebroplasty for Osteoporotic Vertebral Compression Fractures: A Multicenter Retrospective Study in Japan.

Purpose: Bone cement enhancement by percutaneous vertebroplasty (PVP) for the treatment of osteoporotic vertebral compression fractures remains unapproved, as it has not been fully evaluated in Japan. The current multicenter study was conducted in Japan to verify the safety and efficacy of PVP in patients with painful osteoporotic vertebral fractures. Material and Methods: In this retrospective study, we referred to previous studies to evaluate the non-inferiority of PVP to balloon kyphoplasty (BKP). We reviewed consecutive patient data from April 2017 to March 2018 from four institutions based on the medical records of the intervention. We statistically investigated the adverse events due to cement leakage or other factors associated with PVP, and new vertebral compression fractures after PVP were evaluated for safety, pain relief, and gait improvement. Results: This study included 485 patients; most of whom were in the middle- to oldest- age groups (mean age, 81.4 years). No serious adverse events were reported in patients available for safety evaluation (n = 485). Cement leakage and new vertebral compression fractures occurred in 35.7% and 18.6% (26.2%-38.4% and 8.9%-20.7%) of the patients undergoing PVP, respectively, both of which were also judged to be equivalent to those of BKP. The pain score improved in those undergoing PVP, and this improvement was maintained during a one-year follow-up. Of the 206 patients who had difficulty walking at baseline, 156 had restored walking at discharge. Conclusions: PVP was shown to be a safe and effective treatment, even in elderly patients with painful osteoporotic vertebral fractures.

Supraduodenal and Right Gastric Arteries Originating from A Common Trunk: A Rare Anatomical Variant.

Knowledge of the anatomic variations of the supraduodenal artery (SDA) and right gastric artery (RGA) is necessary to reduce the procedure time and radiation exposure dose, as well as to avoid unexpected complications of catheter placement before hepatic arterial infusion chemotherapy. The SDA and RGA most commonly arise from the gastroduodenal artery (GDA) and the proper hepatic artery, respectively; however, they can branch from the left hepatic artery (LHA). In addition, the SDA frequently anastomoses with the RGA and occasionally with the GDA. We observed a rare anatomic variant of SDA and RGA originating from the LHA as a common trunk. The patient also had a variant of SDA communicating with the GDA. It is important for interventional radiologists to be aware of these variations.