Objectives: Gas is a common finding in cervical intervertebral separation. However, intervertebral gas is also found in many decedents without intervertebral separation. Here, we quantified intervertebral gas and examined its value in the diagnosis of cervical intervertebral separation. Methods: We retrospectively reviewed data from 1118 decedents who underwent post-mortem computed tomography (CT) and autopsy from May 2011 to July 2016 and selected those with cervical intervertebral gas with or without intervertebral separation. These data comprised 56 cervical intervertebral spaces with gas [intervertebral separation in 19 (33.9%)] in 43 subjects [intervertebral separation in 17 (39.5%)]. We categorised the decedents according to gas volume, position, and shape and determined the significance of the differences between the decedents with and without separation. Results: The gas volume did not differ significantly between decedents with and without separation (p = 0.063). However, there were significant differences in the gas position between decedents with and without separation. In the sagittal plane: gas was seen in the "centred" position in the ventral-to-dorsal direction in more decedents without separation than in those with separation (p = 0.018). Gas was seen in the ventral-to-dorsal positions in more decedents with separation than in those without separation (p = 0.049). In the cranio-caudal direction, gas in the upper position was more common in decedents with separation than in those without separation in the sagittal plane (p = 0.03). In the coronal plane: gas was seen in the upper position more frequently in decedents with separation in the cranio-caudal direction than in those without separation (p = 0.001). A significant difference in gas shape was observed only in the coronal plane (p = 0.024); irregular gas was associated with decedents without separation. Conclusion: Gas in the ventral-to-dorsal and upper positions in the sagittal plane and in the upper position in the coronal plane was rather indicative of cervical intervertebral separation. An irregular gas shape in the coronal plane was indicative of degenerative changes. (c) 2021 Elsevier B.V. All rights reserved.

In mammography, detection and categorization of micro-calcification clusters (MCCs) using computer-aided diagnosis (CAD) systems are very important tasks because MCCs are important signs at an early stage of breast cancer. However, the conventional methods of CAD only classify MCCs into benign and malignant types, and no method has been developed for a medical requirement to classify the MCCs into more detailed categories according to the spatial distribution of MCCs. To provide a cogent second opinion, we specifically focus on analyzing MCCs' spatial distribution and propose an adaptive Gaussian mixture model-based method to extract the statistical features of the spatial distribution in this study. By mimicking the radiologists' workflow, the proposed method used the main feature of each spatial distributions to classify the MCCs and then provide a cogent second opinion to increase the confidence level of diagnosis decisions. The experiments have been performed on 100 mammographic images with MCCs from a clinical dataset. The experimental results showed that the proposed method was able to detect the MCCs and classify the spatial distribution of the MCCs effectively.

In recent years, deep convolutional neural network (DCNN) has widely been applied for image recognition, and shown a remarkable performance in various natural image-related applications. However, for medical image-related application such as computer-aided diagnosis (CAD), due to the limitation of training data and the modality difference between the natural and medical images, training the DCNN for medical image recognition is still a research topic. In this paper, we propose a DCNN-based method for lesion detection in mammograms. The proposed method consists of the following two steps. Given a mammogram, lesion candidates are firstly detected from the mammogram based on their intensity characteristics. Secondly, a transfer learning-based method is applied for training an existing DCNN to classify the lesion candidates into lesions or normal tissues. The proposed method is tested on a public mammogram database. Compared with several previous studies, our proposed method achieved a higher true positive rate and a lower false positive in lesion detection.

Objectives: The presence of an intervertebral separation indicates vertebral ligamentous injuries, and it is occasionally associated with fatal spinal cord injuries. However, it is often difficult to identify the separation using post-mortem computed tomography (CT). This study retrospectively evaluated the correlation between the post-mortem CT findings and autopsy results of cervical intervertebral separation. Materials and methods: Forty-two subjects (8 females and 34 males) with cervical intervertebral separation were evaluated. The average age was 67 (range, 29-88) years. A radiologist retrospectively reviewed the cervical spines on axial, sagittal, and coronal CT images and determined whether intervertebral separations could be detected. The radiologist also classified the CT findings in cases with detectable separations. Results: Of the 57 cervical intervertebral separations, 39 were detectable on the CT images. The CT findings were grouped into the following six categories: intervertebral gas (n=19; 40.4%); forward intervertebral widening (n=10; 21.3%); backward intervertebral widening (n=1; 2.1%); anteroposterior misalignment (n=6; 12.8%); spur fracture (n=7; 14.9%); and hematoma in front of a vertebral body (n=4; 8.5%). The sensitivity and specificity of intervertebral gas in the diagnosis of cervical intervertebral separation were 33.9% and 99.7%, respectively. Conclusion: Approximately 70% of the cases with cervical intervertebral separations had various abnormal findings on CT imaging. The most common finding was intervertebral gas, but the sensitivity of intervertebral gas was not adequate.

Post-mortem computed tomography (CT) is a valuable tool in forensic medicine. Determination of cause of death may require examination of a corpse found in a frozen state. However, most radiologists are unfamiliar with the post-mortem appearance of frozen organs on CT. Here we present two cases that included CT study of the frozen brain. Both bodies were naturally frozen, and autopsies showed that the cause of death was hypothermia in both instances. On post-mortem CT images, the frozen brains exhibited hypodense areas resembling infarctions, but these were not in regions dominated by blood vessels. Residual open sulci were evident, suggesting that oedema was absent. These two features are helpful when diagnosing a frozen brain on CT images.

Poster: ECR 2016 / C-0932 / Post-mortem lung features on computed tomography in cardiac death cases: ischemic cardiac death vs. non-ischemic cardiac death. by: Kawasumi, A. Usui, Y. Hosokai, K. Matsumoto, Y. Ishizuka, K. Takahashi, Y. Hayashizaki, T. Ishibashi, M. Funayama; Sendai/JP

In recent years, a deep convolutional neural network (DCNN) has attracted great attention due to its outstanding performance in recognition of natural images. However, the DCNN performance for medical image recognition is still uncertain because collecting a large amount of training data is difficult. To solve the problem of the DCNN, we adopt a transfer learning strategy, and demonstrate feasibilities of the DCNN and of the transfer learning strategy for mass detection in mammographic images. We adopt a DCNN architecture that consists of 8 layers with weight, including 5 convolutional layers, and 3 fully-connected layers in this study. We first train the DCNN using about 1.2 million natural images for classification of 1,000 classes. Then, we modify the last fully-connected layer of the DCNN and subsequently train the DCNN using 1,656 regions of interest in mammographic image for two classes classification: mass and normal. The detection test is conducted on 198 mammographic images including 99 mass images and 99 normal images. The experimental results showed that the sensitivity of the mass detection was 89.9 % and the false positive was 19.2 %. These results demonstrated that the DCNN trained by transfer learning strategy has a potential to be a key system for mammographic mass detection computer-aided diagnosis (CAD). In addition, to the best of our knowledge, our study is the first demonstration of the DCNN for mammographic CAD application.

Purpose:To develop a deep convolutional neural network (DCNN)‐based computer‐aided diagnosis (CAD) system for detecting the masses in digital mammographic images.Methods:A DCNN architecture, which consists of 5 convolutional layers and 3 fully connected layers, is constructed in this study. The DCNN parameters are then trained by the following two procedures. We first train the DCNN using about 1.3 million natural images for classification of 1,000 categories. Then, we modify the last fully connected layer and subsequently train the modified DCNN using 1,656 mammographic region of interest (ROI) images for two categories classification: mass and normal.Results:The trained DCNN is tested by using 198 mammographic ROI images including 99 mass images and 99 normal images. The experimental results show that the sensitivity of the mass detection is about 89.9% and the false positive is 19.2%. These results demonstrated that the DCNN has a potential for mammographic CAD.Conclusion:In recent years, the DCNN, as one of the most successful techniques in deep learning technology, made a remarkable impact on image recognition application. For medical image recognition, however, its performance is uncertainty because collecting a large amount of training image data for a particularly medical image modality is difficult. In this study, our preliminary experiments demonstrated a feasibility to apply the DCNN in mammographic CAD system. To the best of our knowledge, this study is also the first demonstration of DCNN for detecting the masses in mammographic images.

Phase-contrast mammography (PCM) systems characteristically yield sharp images with edge enhancement and high-resolution 25-μm/pixel mammograms. However, not all PCM image information can be shown on the display at a resolution of 5-megapixel (5-MP), although 5-MP monitors are recommended for interpretation of digital mammograms. Therefore, we investigated the potential utility of a 15-mega-sub-pixel (15-MsP) display for PCM images.

To evaluate the difference in sinus fluid volume and density between saltwater and freshwater drowning and diagnose saltwater drowning in distinction from freshwater drowning.

OBJECTIVES:Infant cases frequently show a diffuse increase in the concentration of lung fields on post-mortem computed tomography (PMCT). However, the lungs often show simply atelectasis at autopsy in the absence of any other abnormal changes. Thus, we retrospectively reviewed the PMCT findings of lungs following sudden infant death and correlated them with the autopsy results.MATERIALS AND METHODS:We retrospectively reviewed infant cases (0 year) who had undergone PMCT and a forensic autopsy at our institution between May 2009 and June 2013. Lung opacities were classified according to their type; consolidation, ground-glass opacity and mixed, as well as distribution; bilateral diffuse and areas of sparing. Statistical analysis was performed to assess the relationships among lung opacities, causes of death and resuscitation attempt.RESULTS:Thirty infant cases were selected, which included 22 sudden and unexplained deaths and 8 other causes of death. Resuscitation was attempted in 22 of 30 cases. Bilateral diffuse opacities were observed in 21 of the 30 cases. Of the 21 cases, 18 were sudden and unexplained deaths. Areas of sparing were observed in 4 sudden and unexplained deaths and 5 other causes of death. Distribution of opacities was not significantly associated with causes of death or resuscitation attempt. The 21 cases with bilateral diffuse opacities included 6 consolidations (4 sudden and unexplained deaths, 2 other causes of death), 4 ground-glass opacities (3 sudden and unexplained deaths and 1 other) and 11 mixed (11 sudden and unexplained deaths). Types of opacities were not significantly associated with causes of death or resuscitation attempt.CONCLUSION:Atelectasis is very common in sudden and unexplained death of infants. Bilateral diffuse mixed opacity was observed only in sudden and unexplained deaths. Bilateral diffuse pure consolidation or ground-glass opacity was also observed in other causes of death.

Approximately 10% of cases of hypertension in Japan are caused by primary aldosteronism (PA), amounting to about 4 million patients in total. Primary aldosteronism due to unilateral aldosterone hypersecretion is potentially curable by adrenalectomy. The clinical benefits of identifying and treating PA have been reported internationally, but its cost-effectiveness is unclear. We examined whether diagnosing and treating hidden PA in hypertensive population was cost-effective compared with suboptimal treatment. Our hypothetical patient was a 50-year-old man diagnosed with stage I-III hypertension. We established a Markov decision model based on plausible clinical pathways and prognoses of PA. We applied cost-effectiveness analysis comparing a comprehensive diagnostic strategy for PA (measurement of plasma aldosterone/renin ratio, 2 loading tests, imaging, and selective adrenal venous sampling) with a suboptimal strategy to manage hypertension by medication unless the typical signs of PA or other complication were manifest. Outcome measures were expected costs, expected effectiveness, and incremental cost-effectiveness ratio. The robustness of the findings was established by one-way and scenario sensitivity analyses. The comprehensive PA diagnostic strategy increased the expected costs by 64 004 JPY and expected life-years by 0.013 compared with standard treatment. The incremental cost-effectiveness ratio for the diagnosis of PA was 4 923 385 JPY per year. Our findings were sensitive to the outcomes of screening and treatment, and the costs of continuous or periodic medication for hypertension and the treatment of stroke and its complications.

Light propagation along the helical axis of a planar cholesteric with dichroic dyes is calculated using the 2×2 Jones matrix formulation. The formulation is proved to be more useful than others for evaluating the dye LCD, as it reduces the number of parameters. The perceived contrast ratios are derived, and the dependences on the various cholesteric parameters are estimated. The results show that a small value of Δ n and a high-order parameter are essential for improving the dye LCD contrast ratios.

Objectives: To evaluate the post-mortem computed tomography (PMCT) findings of intervertebral separation.Methods: 10 subjects who had undergone PMCT and forensic autopsy were evaluated. The median age was 69 years (range, 25-89 years), and all subjects were men. 19 intervertebral separations were identified at autopsy. 2 radiologists reviewed the CT findings such as misalignment of the spine, intervertebral space widening, gas in the intervertebral space, and haemorrhage in the tissues surrounding the spine before and after autopsy using a 3D DICOM workstation.Results: The observers detected 6 of 19 (32%) intervertebral separations before autopsy. After autopsy, they reviewed the CT considering the autopsy results and detected 13 of 19 (68%) intervertebral separations; misalignment (n=7; 37%), widening (n=5; 26%), gas (n=2; 11%), arid haemorrhage (n=7; 37%). No finding indicating intervertebral separation was detected in 6 intervertebral separations.Conclusion: Re-evaluation with autopsy results improved the detectability of intervertebral separation on PMCT. Adequate experience and training regarding the interpretation are required. (C) 2014 Elsevier Ltd. All rights reserved.

We aimed to evaluate the influence of image reduction using a bi-cubic interpolation method on the accuracy of detection of clustered microcalcifications (MCLs) and masses on digital mammograms. Digital mammograms (n=194) of 97 subjects were selected retrospectively, comprising 47 patients with clustered MCLs or masses and 52 controls. Images were acquired in the craniocaudal view by phase-contrast mammography (PCM). Original PCM images comprised 25-μm pixels. The reduced images converted from the originals by bi-cubic interpolation were of 50-μm pixel size. Five observers independently interpreted all images, and rated their confidence concerning the presence of lesions on a continuous 0-100 scale. Receiver-operating characteristic (ROC) analysis was performed using the jackknife method and LABMRMC program. Differences in areas under the curve (AUC) values based on 95% confidence intervals were evaluated. The average AUC values for detection of masses were 0.8435 and 0.8646 for the original and reduced images, respectively. The difference between the average AUC values was not statistically significant (p=0.5855). Average AUC values for clustered MCLs detection were 0.9273 and 0.9574 for the original and reduced images, respectively. This difference was not statistically significant (p=0.1949). Detection of masses and clustered MCLs on digital mammograms was unaffected by bi-cubic interpolation image reduction.

Referring to our experience with post-mortem computed tomography (CT), many hypothermic death cases presented a lack of increase in lung-field concentration, blood clotting in the heart, thoracic aorta or pulmonary artery, and urine retention in the bladder. Thus we evaluated the diagnostic performance of post-mortem CT on hypothermic death based on the above-mentioned three findings. Twenty-four hypothermic death subjects and 53 non-hypothermic death subjects were examined. Two radiologists assessed the presence or lack of an increase in lung-field concentration, blood clotting in the heart, thoracic aorta or pulmonary artery, and measured urine volume in the bladder. Pearson's chi-square test and Mann-Whitney U-test were used to assess the relationship between the three findings and hypothermic death. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the diagnosis were also calculated. Lack of an increase in lung-field concentration and blood clotting in the heart, thoracic aorta or pulmonary artery were significantly associated with hypothermic death (p=0.0007, p<0.0001, respectively). The hypothermic death cases had significantly more urine in the bladder than the non-hypothermic death cases (p=0.0011). Regarding the diagnostic performance with all three findings, the sensitivity was 29.2% but the specificity was 100%. These three findings were more common in hypothermic death cases. Although the sensitivity was low, these findings will assist forensic physicians in diagnosing hypothermic death since the specificity was high.

Recent studies have reported that drowning victims frequently have fluid accumulation in the paranasal sinuses, most notably the maxillary and sphenoid sinuses. However, in our previous study, many non-drowning victims also had fluid accumulation in the sinuses. Therefore, we evaluated the qualitative difference in fluid accumulation between drowning and non-drowning cases in the present study. Thirty-eight drowning and 73 non-drowning cases were investigated retrospectively. The fluid volume and density of each case were calculated using a DICOM workstation. The drowning cases were compared with the non-drowning cases using the Mann–Whitney U-test because the data showed non-normal distribution. The median fluid volume was 1.82 (range 0.02–11.7) ml in the drowning cases and 0.49 (0.03–8.7) ml in the non-drowning cases, and the median fluid density was 22 (−14 to 66) and 39 (−65 to 77) HU, respectively. Both volume and density differed significantly between the drowning and non-drowning cases (p=0.001, p=0.0007). Regarding cut-off levels in the ROC analysis, the points on the ROC curve closest (0, 1) were 1.03ml (sensitivity 68%, specificity 68%, PPV 53%, NPV 81%) and 27.5 HU (61%, 70%, 51%, 77%). The Youden indices were 1.03ml and 37.8 HU (84%, 51%, 47%, 86%). When the cut-off level was set at 1.03ml and 27.5HU, the sensitivity was 42%, specificity 45%, PPV 29% and NPV 60%. When the cut-off level was set at 1.03ml and 37.8HU, sensitivity was 58%, specificity 32%, PPV 31% and NPV 59%.

Lurasidone is a novel antipsychotic agent with high affinity for dopamine D(2) and serotonin 5-HT(7), 5-HT(2A), and 5-HT(1A) receptors. We previously reported that in addition to its antipsychotic action, lurasidone shows beneficial effects on mood and cognition in rats, likely through 5-HT(7) receptor antagonistic actions. In this study, we evaluated binding of lurasidone to 5-HT(7) receptors in the rat brain by autoradiography using [(3)H]SB-269970, a specific radioligand for 5-HT(7) receptors. Brain slices were incubated with 4 nM [(3)H]SB-269970 at room temperature and exposed to imaging plates for 8 weeks before phosphorimager analysis. Using this method, we first investigated 5-HT(7) receptor distribution. We found that 5-HT(7) receptors are abundantly localized in brain limbic structures, including the lateral septum, thalamus, hypothalamus, hippocampus, and amygdala. On the other hand, its distribution was moderate in the cortex and low in the caudate putamen and cerebellum. Secondly, binding of lurasidone, a selective 5-HT(7) receptor antagonist SB-656104-A and an atypical antipsychotic olanzapine to this receptor was examined. Lurasidone, SB-656104-A (10–1000 nM), and olanzapine (100–10,000 nM) showed concentration-dependent inhibition of [(3)H]SB-269970 binding with IC(50) values of 90, 49, and 5200 nM, respectively. Similar inhibitory actions of these drugs were shown in in vitro [(3)H]SB-269970 binding to 5-HT(7) receptors expressed in Chinese hamster ovary cells. Since there was no marked species difference in rat and human 5-HT(7) receptor binding by lurasidone (K(i) = 1.55 and 2.10 nM, respectively), these findings suggest that binding to 5-HT(7) receptors might play some role in its beneficial pharmacological actions in schizophrenic patients.