Shoichiro Takao

Incidence of lumbar spondylolysis in the general population in Japan based on multidetector computed tomography scans from two thousand subjects.

Study Design. Epidemiological analysis using CTs. Objective. To investigate the true incidence of lumbar spondylolysis in the general population in Japan. Summary of Background Data. Although there have been several reports on the incidence of lumbar spondylolysis, they had some weakness. One of them concerns the subjects investigated, because the incidence of lumbar spondylolysis varies considerably, and some patients are asymptomatic. In addition, most of the past studies used plain radiograph films or skeletal investigation. Therefore, the past reported incidence may not correspond to that of the general population. Methods. We reviewed the computed tomography (CT) scans of 2000 subjects (age: 20–92 years) who had undergone abdominal and pelvic CT on a single multidetector CT scanner for reasons unrelated to low back pain. We reviewed them for spondylolysis, spondylolytic spondylolisthesis, and spina bifida occulta (SBO) in the lumbosacral region. The grade (I–IV) of spondylolisthesis was measured using midsagittal reconstructions. Results. Lumbar spondylolysis was found in 117 subjects (5.9%). Their male-female ratio was 2:1. Multiple-level spondylolysis was found in 5 subjects (0.3%). Among these 117 subjects, there were 124 vertebrae with spondylolysis. Of them, 112 (90.3%) corresponded to L5, and 26 (21.0%) had unilateral spondylolysis. SBO was found in 154 subjects. Of them, 25 had spondylolysis (16.2%), whereas, in 1846 subjects without SBO, 92 had spondylolysis (5.0%). The incidence of spondylolysis among the patients with SBO was significantly higher than that in subjects without SBO (Odd ratio was 3.7-fold). Of 124 vertebrae with spondylolysis, 75 (60.5%) showed low-grade (Meyerding grade I or II) spondylolisthesis, and no subject presented high-grade spondylolisthesis. Spondylolisthesis was found in 74.5% of the subjects with bilateral spondylolysis, and in 7.7% of those with unilateral spondylolysis. Conclusion. The incidence of lumbar spondylolysis in the Japanese general population was 5.9% (males: 7.9%, females: 3.9%).

Gender disparities in the association between epicardial adipose tissue volume and coronary atherosclerosis: A 3-dimensional cardiac computed tomography imaging study in Japanese subjects

BackgroundGrowing evidence suggests that epicardial adipose tissue (EAT) may contribute to the development of coronary artery disease (CAD). In this study, we explored gender disparities in EAT volume (EATV) and its impact on coronary atherosclerosis.MethodsThe study population consisted of 90 consecutive subjects (age: 63 ± 12 years; men: 47, women: 43) who underwent 256-slice multi-detector computed tomography (MDCT) coronary angiography. EATV was measured as the sum of cross-sectional epicardial fat area on CT images, from the lower surface of the left pulmonary artery origin to the apex. Subjects were segregated into the CAD group (coronary luminal narrowing > 50%) and non-CAD group.ResultsEATV/body surface area (BSA) was higher among men in the CAD group than in the non-CAD group (62 ± 13 vs. 33 ± 10 cm3/m2, p < 0.0001), but did not differ significantly among women in the 2 groups (49 ± 18 vs. 42 ± 9 cm3/m2, not significant). Multivariate logistic analysis showed that EATV/BSA was the single predictor for >50% coronary luminal narrowing in men (p < 0.0001). Predictors excluded were age, body mass index, hypertension, diabetes mellitus, and hyperlipidemia.ConclusionsIncreased EATV is strongly associated with coronary atherosclerosis in men.

Vestibular and cochlear neuritis in patients with Ramsay Hunt syndrome: a Gd-enhanced MRI study

Abstract Conclusion: It is suggested that vertigo in patients with Ramsay Hunt syndrome is mostly induced by superior vestibular neuritis consecutive to the reactivation of varicella-zoster virus (VZV) infection from the geniculate ganglion through the faciovestibular anastomosis. Refractory hearing loss in patients with Ramsay Hunt syndrome may be due to cochlear neuritis following the spread of VZV. Objectives: An attempt was made to selectively identify vestibulocochlear nerves in the internal auditory canal (IAC) on gadolinium (Gd)-enhanced MRI in patients with Ramsay Hunt syndrome. Methods: Fourteen patients with Ramsay Hunt syndrome presenting with facial palsy, herpes zoster oticus, vertigo, and/or sensorineural hearing loss were scanned on 1.5 T MRI enhanced with Gd. Perpendicular section images of the IAC were reconstructed to identify the facial, superior, and inferior vestibular nerves and the cochlear nerves separately. Results: All except one of the patients with Ramsay Hunt syndrome with vertigo showed both canal paresis on the caloric test and Gd enhancement of the superior vestibular nerve in the IAC on MRI. Among 10 patients with hearing loss, 3 patients with severe to moderate sensorineural hearing loss showed Gd enhancement of the cochlear nerve in the IAC on MRI.

Hybrid Multi-layered GMDH-type Neural Network Using Principal Component Regression Analysis and its Application to Medical Image Diagnosis of Liver Cancer☆

In this study, hybrid multi-layered Group Method of Data Handling (GMDH)-type neural network algorithm using principal component-regression analysis is proposed and applied to the computer aided image diagnosis (CAD) of lung cancer. In the GMDH-type neural network, heuristic self-organization method, which is a kind of evolutional computation, is used to organize the neural network architecture. But, multi-co linearity occurs and prediction values become unstable. In this study, hybrid multi-layered GMDH-type neural network using principal component-regression analysis is proposed. In this algorithm, multi-co linearity does not occur and accurate prediction values are obtained. This new algorithm is applied to the medical image diagnosis of lung cancer. First, the GMDH-type neural network which recognizes the lung regions, is automatically organized using multi-detector row CT (MDCT) images of the lung, and the lung regions are recognized and extracted. Then, new another GMDH-type neural network is automatically organized using the extracted image of lung, and the candidate regions of the lung cancer is recognized and extracted. The recognition results are compared with the conventional sigmoid function neural network trained using back propagation method and it is shown that this algorithm is useful for CAD of lung cancer.

Location of intrapelvic vessels around the acetabulum assessed by three-dimensional computed tomographic angiography: prevention of vascular-related complications in total hip arthroplasty

BackgroundDuring total hip arthroplasty (THA), the external iliac, femoral, and obturator vessels are at risk of vascular injury when penetrating the inner cortex of the pelvis. The purpose of this study was to clarify the location of these vessels using three-dimensional computed tomographic angiography (3DCT-A).MethodsWe enrolled 100 subjects (200 hips) without hip disease and performed examinations on the following. (1) External iliac–femoral vessels: we measured the shortest distance from these vessels to the pelvis on axial CT images and investigated the factors affecting distance. The anatomical course of the iliac artery was classified as straight, curved, or tortuous, and the correlation between course and age was established. (2) Obturator vessels: we measured the shortest distance from the obturator vessels to the quadrilateral surface on axial CT images. (3) Visualization of pelvic vessels was through the pelvis by dual-phase 3DCT-A.Results(1) The external iliac vein was located significantly closer to the pelvis than the artery, especially on the left side and in aged and female subjects. The single-curved and tortuous double-curved vessel types were found in aged subjects, and external iliac vessels of these types were closer to the pelvis than vessels of the straight type. In 36 subjects, the external iliac veins lay directly on the osseous surface of the pelvis (right 16, left 36). Of these 36 subjects, only one had straight-type vessels. (2) Obturator vessels were located just behind the acetabulum near the obturator foramen. (3) Reconstructed 3DCT images enabled us to visualize the pelvic vessels and demonstrated the danger area for penetrating the inner cortex of the pelvis.ConclusionUnderstanding the anatomical orientation of the pelvic vessels around the acetabulum using 3DCT-A could be helpful for preventing vascular injury during THA.

Hematoma in the cervical ligamentum flavum. Report of a case and review of the literature

Hematoma of the cervical ligamentum flavum is very rare, and its pathogenesis is unknown. We describe a case of ligamentum flavum hematoma in the cervical spine causing severe myelopathy. Postoperative histological examination suggested it was the result of the rupture of a hemangioma or of an arteriovenous malformation in the ligamentum flavum. After removal of the lesion, the patient’s condition immediately improved. Review of all three reported cases, including this one, showed that complete resection of the mass resulted in immediate relief of symptoms of incomplete paraplegia. The findings of magnetic resonance imaging (MRI) of the hematoma may vary with time, and they may show no characteristic intensity. However, MRI of this case revealed that the tissues surrounding the mass were enhanced with gadolinium diethylene triamine penta-acetic acid, and an area of homogeneous iso-intensity was clearly surrounded by a low-intensity area (flavum) on T2-weighed short-tau inversion recovery images. These findings could be characteristic of the ligamentum flavum hematoma and might help in the differentiation from a cervical epidural hematoma.

Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver

A revised group method of data handling (GMDH)-type neural network algorithm for medical image recognition is proposed, and is applied to medical image analysis of cancer of the liver. The revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback-loop calculations. In this algorithm, the polynomial type and the radial basis function (RBF)-type neurons are used for organizing the neural network architecture. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion, defined as the prediction sum of squares (PSS).

Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using principal component-regression analysis

The hybrid feedback group method of data handling (GMDH)-type neural network is proposed and applied to the medical image diagnosis of liver cancer. In this algorithm, the principal component-regression analysis is used for the learning calculation of the neural network, and the accurate and stable predicted values are obtained. Furthermore, this neural network has the feedback loop and the complexity of neural network architecture is increased using the feedback loop calculations. The neural network architecture is automatically organized so as to fit the complexity of the nonlinear system using the prediction error criterion defined as Akaike’s information criterion (AIC) or prediction sum of squares (PSS). The recognition results show that the hybrid feedback GMDH-type neural network algorithm is useful for the medical image diagnosis of liver cancer since the optimum neural network architecture is automatically organized.

Logistic GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer

The logistic group method of data handling (GMDH)-type neural network is proposed and applied to the medical image diagnosis of lung cancer. In this logistic GMDH-type neural network algorithm, the principal component-regression analysis is used to estimate the parameters of the neural network, and the multi-colinearity, which is generated in the conventional GMDH algorithm, is protected. Therefore, accurate and stable predicted values are obtained in the logistic GMDH-type neural network. Furthermore, the polynomial and logistic neurons are used, and the neural network architectures are automatically organized so as to minimize the prediction error criterion defined as Akaike’s information criterion or prediction sum of squares. The identification results show that the logistic GMDH-type neural network algorithm is useful for the medical image diagnosis of lung cancer since the optimum neural network architecture is automatically organized so as to fit the complexity of the medical images.

Hybrid GMDH-type neural network using artificial intelligence and its application to medical image diagnosis of liver cancer

A hybrid Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of the liver cancer. In this algorithm, the knowledge base for medical image diagnosis is used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Akaikes information criterion (AIC) or Prediction Sum of Squares (PSS). It is shown that the hybrid GMDH-type neural network is accurate and a useful method for the medical image diagnosis of the liver cancer.