Sadamitsu Nishihara

Accuracy of computed tomography attenuation measurements for diagnosing anemia

PurposeThe purpose of this study was to determine which computed tomography (CT) attenuation parameter was the most appropriate to predict the presence or severity of anemia.Materials and methodsThe subjects of the study wer 500 patients who had undergone a peripheral blood examination within 24 h of an unenhanced CT scan. Regions of interest were placed in the left ventricular (LV) cavity, thoracic and abdominal aortic lumens, inferior vena cava, and interventricular septum. The CT attenuation difference between the LV cavity and interventricular septum was also calculated. The relation between these measurements and the blood hemoglobin level was analyzed. In addition, using several selected parameters, a receiver operating characteristic (ROC) analysis was also performed.ResultsThe difference in CT attenuation between the LV cavity and interventricular septum revealed the greatest correlation. ROC analyses also revealed the greatest area under the ROC curve in the differences between CT attenuation.ConclusionThe best quantitative method for the diagnosis of anemia was the difference in CT attenuation between the left ventricle and interventricular septum.

Postprocessing technique with MDCT data improves the accuracy of the detection of lung nodules

PurposeThe aim of this study was to determine whether postprocessing techniques could improve the accuracy of detecting lung nodules.Materials and methodsA total of 154 segmented lung volumes of multidetector-row computed tomography (MDCT) data were the subject of the study. Lung nodules were present in 88 volumes and absent in 66 volumes. We prepared four groups: (1) 7- or 10-mm thick-section axial images; (2) 1-mm thin-section axial images; (3) sliding slab maximum intensity projection (MIP) images with a slab thickness of 15 mm; and (4) sliding slab volume rendering (VR) images with a slab thickness of 15 mm. Sixteen physicians reviewed each group in interactive cine mode. The observers’ performance in the detection of lung nodule was evaluated by receiver operating characteristic (ROC) analysis.ResultsThe observers’ performance of the MIP and VR groups was significantly better than in other two groups. There was no significant difference statistically between the thin and thick groups.ConclusionThe detectability of lung nodules is improved with the use of sliding slab MIP and VR using thin-section image data. Thin-section volume data are essential for improving diagnostic accuracy, but observation of thin-section images without utilization of image-processing techniques dose not improve diagnostic accuracy.

320 列CT 装置のX 線スペクトル測定時に使用する円柱カーボン散乱体の適切な長さに関する検討

A short length scatterer is adopted to measure the X-ray spectrum of computed tomography (CT) equipment with a wide irradiation field in the body axis direction. The purpose of this study is to compare X-ray spectra measured using different length scatterers and determine the most appropriate length for the scatterer. 320-slice CT equipment (Aquilion ONE) was used in this study. Circular carbonrods (3 cm diameter) with five different lengths (1-16 cm) were used as scatterers. The effect of the beam hardening phenomenon from different length carbon rods was evaluated according to the effective energy. The measurement accuracy for photon information was also evaluated based on the photon count corresponding to the characteristic X-ray. As a result, the beam hardening effect was scarcely observed when the 1 cm long scatterer was used, and the number of the photons measured for the characteristic X-ray was the most. Therefore, it was concluded that the 1 cm long circular carbon rod scatterer was the most suitable.

Basic study for automatic recognition of osteoporosis using abdominal x-ray CT images

We have developed an algorithm that can be used to distinguish the central part of the vertebral body from an abdominal X-ray CT image and to automatically calculate three measures to diagnose the degree of osteoporosis in a patient. In addition, we examined whether it is possible to use these CT images as an aid in diagnosing osteoporosis. Three measures that were automatically extracted from the central part of a vertebral body in the CT images were compared with the bone mineral density (BMD) values that were obtained from the same vertebral body. We calculated the mean CT number, coefficient of variation, and the first moment of power spectrum in the recognized vertebral body. We judged whether a patient had osteoporosis using the diagnostic criteria for primary osteoporosis (Year 2000 revision, published by the Japanese Society for Bone and Mineral Research). We classified three measures for normal and abnormal groups using the principal component analysis, and the two groups were compared with the results obtained from the diagnostic criteria. As a result, it was found that the algorithm could be used to distinguish the central part of the vertebral body in the CT images and to calculate these measures automatically. When distinguishing whether a patient was osteoporotic or not with the three measures obtained from the CT images, the ratio (sensitivity) usable for diagnosing a patient as osteoporotic was 0.93 (14/15), and the ratio (specificity) usable for diagnosing a patient as normal was 0.64 (7/11). Based on these results, we believe that it is possible to utilize the measures obtained from these CT images to aid in diagnosing osteoporosis.