Shaken adult syndrome due to ocean wave: an autopsy case.

Severe intracranial trauma during torture or assault is reportedly caused by shaken adult syndrome. However, intracranial traumas caused by natural forces, excluding human factors and collision impact, are extremely rare. We report an autopsy case of shaken adult syndrome caused by ocean wave forces. A man in his 40s without any medical history was washed away by a wave during recreational fishing. He was found approximately 500 m away from the fishing point drifting on the ocean in a state of cardiopulmonary arrest and was confirmed dead, with no response to cardiopulmonary resuscitation, 3 h after the accident. The autopsy revealed no mechanical trauma to the entire body surface, including the head. Both lungs were inflated, and pleural effusion was observed. The brain was swollen and congested, and subarachnoid hemorrhage was observed in the interhemispheric fissure and the convexity of the parietal occipital lobe. Macroscopic and microscopic hemorrhage spots were found in the brain, and the results of the blood alcohol test and urinary toxicological screening were negative. The cause of death was determined as drowning. This case demonstrates a rare but notable mechanism of injury observed in immersed bodies.

Distinguishing true from pseudo hematoma in the cervical spinal canal using postmortem computed tomography.

Spinal cord injury is difficult to detect directly on postmortem computed tomography (PMCT) and it is usually diagnosed by indirect findings such as a hematoma in the spinal canal. However, we have encountered cases where the hematoma-like high-attenuation area in the cervical spinal canal was visible on PMCT, while no hematoma was observed at autopsy; we called it a "pseudo hematoma in the cervical spinal canal (pseudo-HCSC)." In this retrospective study, we performed statistical analysis to distinguish true from pseudo-HCSC. The cervical spinal canal was dissected in 35 autopsy cases with a hematoma-like high-attenuation area (CT values 60-100 Hounsfield Unit (HU)) in the spinal canal from the first to the fourth cervical vertebrae in axial slices of PMCT images. Of these 22 had a hematoma and 13 did not (pseudo-HCSC). The location and length of the hematoma-like high-attenuation and spinal cord areas were assessed on reconstructed PMCT images, true HCSC cases had longer the posterior hematoma-like area and shorter the spinal cord area in the midline of the spinal canal (P < 0.05). Furthermore, we found that true HCSC cases were more likely to have fractures and gases on PMCT while pseudo-HCSC cases were more likely to have significant facial congestion (P < 0.05). We suggest that pseudo-HCSC on PMCT is related to congestion of the internal vertebral venous plexus. This study raises awareness about the importance of distinguishing true HCSC from pseudo-HCSC in PMCT diagnosis, and it also presents methods for differentiation between these two groups.

Frequency of subclinical interstitial lung disease in COVID-19 autopsy cases: potential risk factors of severe pneumonia.

Risk factors of severe coronavirus disease 2019 (COVID-19) have been previously reported; however, histological risk factors have not been defined thus far. The aim of this study was to clarify subclinical hidden interstitial lung disease (ILD) as a risk factor of severe pneumonia associated with COVID-19. We carefully examined autopsied lungs and chest computed tomography scanning (CT) images from patients with COVID-19 for interstitial lesions and then analyzed their relationship with disease severity. Among the autopsy series, subclinical ILD was found in 13/27 cases (48%) in the COVID-19 group, and in contrast, 8/65 (12%) in the control autopsy group (p = 0.0006; Fisher's exact test). We reviewed CT images from the COVID-19 autopsy cases and verified that subclinical ILD was histologically detectable in the CT images. Then, we retrospectively examined CT images from another series of COVID-19 cases in the Yokohama, Japan area between February-August 2020 for interstitial lesions and analyzed the relationship to the severity of COVID-19 pneumonia. Interstitial lesion was more frequently found in the group with the moderate II/severe disease than in the moderate I/mild disease (severity was evaluated according to the COVID-19 severity classification system of the Ministry of Health, Labor, and Welfare [Japan]) (moderate II/severe, 11/15, 73.3% versus moderate I/mild, 108/245, 44.1%; Fisher exact test, p = 0.0333). In conclusion, it was suggested that subclinical ILD could be an important risk factor for severe COVID-19 pneumonia. A benefit of these findings could be the development of a risk assessment system using high resolution CT images for fatal COVID-19 pneumonia.

Quantitative Computed Tomography Analysis of the Longitudinal Change Between Centrilobular and Paraseptal Emphysema Subtypes: A Retrospective Study.

OBJECTIVE: This study aimed to investigate the difference between the extent of centrilobular emphysema (CLE) and paraseptal emphysema (PSE) on follow-up chest CT scans and their relationship to the cross-sectional area (CSA) of small pulmonary vessels. METHODS: Sixty-two patients (36 CLE and 26 PSE) who underwent 2 chest CT scans were enrolled in this study. The percentage of low attenuation volume (%LAV) and total CSA of the small pulmonary vessels <5 mm 2 (%CSA < 5) were measured at the 2 time points. Analysis of the initial %CSA < 5 and the change in the %LAV and %CSA < 5 on follow-up imaging was performed. RESULTS: The initial %CSA < 5 was not significantly different between the CLE and the PSE groups (CLE, 0.66 vs. PSE, 0.71; P = 0.78). There was no significant difference in the longitudinal change in the %LAV between the 2 groups (CLE, -0.048% vs. PSE, 0.005%; P = 0.26). The longitudinal change in the %CSA < 5 in patients with PSE significantly decreased compared with those with CLE (CLE, 0.025% vs. PSE, -0.018%; P = 0.02). CONCLUSIONS: The longitudinal change in the %CSA < 5 was significantly different for patients with CLE and PSE, demonstrating an important pathophysiological difference between the subtypes.

Chronic thromboembolic pulmonary hypertension is associated with a loss of total lung volume on computed tomography.

BACKGROUND: Although lung volumes are usually normal in individuals with chronic thromboembolic pulmonary hypertension (CTEPH), approximately 20%-29% of patients exhibit a restrictive pattern on pulmonary function testing. AIM: To quantify longitudinal changes in lung volume and cardiac cross-sectional area (CSA) in patients with CTEPH. METHODS: In a retrospective cohort study of patients seen in our hospital between January 2012 and December 2019, we evaluated 15 patients with CTEPH who had chest computed tomography (CT) performed at baseline and after at least 6 mo of therapy. We matched the CTEPH cohort with 45 control patients by age, sex, and observation period. CT-based lung volumes and maximum cardiac CSAs were measured and compared using the Wilcoxon signed-rank test and the Mann-Whitney u test. RESULTS: Total, right lung, and right lower lobe volumes were significantly reduced in the CTEPH cohort at follow-up vs baseline (total, P = 0.004; right lung, P = 0.003; right lower lobe; P = 0.01). In the CTEPH group, the reduction in lung volume and cardiac CSA was significantly greater than the corresponding changes in the control group (total, P = 0.01; right lung, P = 0.007; right lower lobe, P = 0.01; CSA, P = 0.0002). There was a negative correlation between lung volume change and cardiac CSA change in the control group but not in the CTEPH cohort. CONCLUSION: After at least 6 mo of treatment, CT showed an unexpected loss of total lung volume in patients with CTEPH that may reflect continued parenchymal remodeling.

Prediction of prognosis in patients with severe COVID-19 pneumonia using CT score by emergency physicians: a single-center retrospective study.

We aimed to develop a method to determine the CT score that can be easily obtained from CT images and examine its prognostic value for severe COVID pneumonia. Patients with COVID pneumonia who required ventilatory management by intubation were included. CT score was based on anatomical information in axial CT images and were divided into three sections of height from the apex to the bottom. The extent of pneumonia in each section was rated from 0 to 5 and summed. The primary outcome was the prediction of patients who died or were managed on extracorporeal membrane oxygenation (ECMO) based on the CT score at admission. Of the 71 patients included, 12 (16.9%) died or required ECMO management, and the CT score predicted death or ECMO management with ROC of 0.718 (0.561-0.875). The death or ECMO versus survival group (median [quartiles]) had a CT score of 17.75 (14.75-20) versus 13 (11-16.5), p = 0.017. In conclusion, a higher score on our generated CT score could predict the likelihood of death or ECMO management. A CT score at the time of admission allows for early preparation and transfer to a hospital that can manage patients who may need ECMO.

Earliest histopathological changes in COVID-19 pneumonia with comprehensive gene expression analyses: A case series study.

AIMS: In COVID-19 pneumonia, early detection and appropriate treatment are essential to prevent severe exacerbation. Therefore, it is important to understand the initiating events of COVID-19 pneumonia. However, at present, the literature about early stage disease has been very limited. Here, we investigated the earliest histopathological changes and gene expression profiles associated with COVID-19 pneumonia. METHODS AND RESULTS: We carefully examined 25 autopsied cases with different clinical courses. Dilation of capillaries and edematous thickening of the alveolar septa were found even in areas that macroscopically looked almost normal. Pneumocytes, histocytes/macrophages, and vascular endothelial cells were immunohistochemically positive for tissue factor, which is an important early responder to tissue injuries. Comprehensive gene expression analyses revealed that those lesions presented differential profiles compared to those of control lungs and were associated with a significant upregulation of the lysosomal pathway. CONCLUSIONS: Alveolar capillary dilation and edematous thickening may be the earliest histopathological change detected in COVID-19 pneumonia. Intensive investigations of such lesions may lead to an understanding of the initiating event of not only COVID-19 pneumonia but also of general diffuse alveolar damage.

Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis.

We investigated the feasibility of a new deep-learning (DL)-based lung analysis method for the evaluation of interstitial lung disease (ILD) by comparing it with evaluation using the traditional computer-aided diagnosis (CAD) system and patients' clinical outcomes. We prospectively included 104 patients (84 with and 20 without ILD). An expert radiologist defined regions of interest in the typical areas of normal, ground-glass opacity, consolidation, consolidation with fibrosis (traction bronchiectasis), honeycombing, reticulation, traction bronchiectasis, and emphysema, and compared them with the CAD and DL-based analysis results. Next, we measured the extent of ILD lesions with the CAD and DL-based analysis and compared them. Finally, we compared the lesion extent on computed tomography (CT) images, as measured with the DL-based analysis, with pulmonary function tests results and patients' overall survival. Pearson's correlation analysis revealed a significant correlation between DL-based analysis and CAD results. Forced vital capacity was significantly correlated with DL-based analysis (r = 0.789, p < 0.001 for normal lung volume and r = −0.316, p = 0.001 for consolidation with fibrosis volume). Consolidation with fibrosis measured using DL-based analysis was independently associated with poor survival. The lesion extent measured using DL-based analysis showed a negative correlation with the pulmonary function test results and prognosis.

Correlation between CT Value on Lung Subtraction CT and Radioactive Count on Perfusion Lung Single Photon Emission CT in Chronic Thromboembolic Pulmonary Hypertension.

Background: Lung subtraction CT (LSCT), the subtraction of noncontrast CT from CT pulmonary angiography (CTPA) without spatial misregistration, is easily applicable by utilizing a software-based deformable image registration technique without additional hardware and permits the evaluation of lung perfusion as iodine accumulation, similar to that observed in perfusion lung single photon emission CT (PL-SPECT). The aim of this study was to use LSCT to newly assess the quantitative correlation between the CT value on LSCT and radioactive count on PL-SPECT as a reference and validate the quantification of lung perfusion by measuring the CT value in chronic thromboembolic pulmonary hypertension (CTEPH). Methods: We prospectively enrolled 47 consecutive patients with CTEPH undergoing both LSCT and PL-SPECT; we used noncontrast CT, CTPA, and LSCT to measure CT values and PL-SPECT to measure radioactive counts in areas representing three different perfusion classes­no perfusion defect, subsegmental perfusion defect, and segmental perfusion defect; we compared CT values on noncontrast CT, CTPA, and LSCT and radioactive counts on PL-SPECT among the three classes, then assessed the correlation between them. Results: Both the CT values and radioactive counts differed significantly among the three classes (p < 0.01 for all) and showed weak correlation (ρ = 0.38) by noncontrast CT, moderate correlation (ρ = 0.61) by CTPA, and strong correlation (ρ = 0.76) by LSCT. Conclusions: The CT value measurement on LSCT is a novel quantitative approach to assess lung perfusion in CTEPH and only correlates strongly with radioactive count measurement on PL-SPECT.

Radiomics analysis for differentiating of cervical lymphadenopathy between cancer of unknown primary and malignant lymphoma on unenhanced computed tomography.

To investigate the usefulness of texture analysis to discriminate between cervical lymph node (LN) metastasis from cancer of unknown primary (CUP) and cervical LN involvement of malignant lymphoma (ML) on unenhanced computed tomography (CT). Cervical LN metastases in 17 patients with CUP and cervical LN involvement in 17 patients with ML were assessed by 18F-FDG PET/CT. The texture features were obtained in the total cross-sectional area (CSA) of the targeted LN, following the contour of the largest cervical LN on unenhanced CT. Values for the max standardized uptake value (SUVmax) and the mean SUV value (SUVmean), and 34 texture features were compared using a Mann-Whitney U test. The diagnostic accuracy and area under the curve (AUC) of the combination of the texture features were evaluated by support vector machine (SVM) with nested cross-validation. The SUVmax and SUVmean did not differ significantly between cervical LN metastases from CUP and cervical LN involvement from ML. However, significant differences of 9 texture features of the total CSA were observed (p = 0.001 - 0.05). The best AUC value of 0.851 for the texture feature of the total CSA were obtained from the correlation in the gray-level co-occurrence matrix features. SVM had the best AUC and diagnostic accuracy of 0.930 and 84.8%. Radiomics analysis appears to be useful for differentiating cervical LN metastasis from CUP and cervical LN involvement of ML on unenhanced CT.

Comparison of CO-RADS Scores Based on Visual and Artificial Intelligence Assessments in a Non-Endemic Area.

In this study, we first developed an artificial intelligence (AI)-based algorithm for classifying chest computed tomography (CT) images using the coronavirus disease 2019 Reporting and Data System (CO-RADS). Subsequently, we evaluated its accuracy by comparing the calculated scores with those assigned by radiologists with varying levels of experience. This study included patients with suspected SARS-CoV-2 infection who underwent chest CT imaging between February and October 2020 in Japan, a non-endemic area. For each chest CT, the CO-RADS scores, determined by consensus among three experienced chest radiologists, were used as the gold standard. Images from 412 patients were used to train the model, whereas images from 83 patients were tested to obtain AI-based CO-RADS scores for each image. Six independent raters (one medical student, two residents, and three board-certified radiologists) evaluated the test images. Intraclass correlation coefficients (ICC) and weighted kappa values were calculated to determine the inter-rater agreement with the gold standard. The mean ICC and weighted kappa were 0.754 and 0.752 for the medical student and residents (taken together), 0.851 and 0.850 for the diagnostic radiologists, and 0.913 and 0.912 for AI, respectively. The CO-RADS scores calculated using our AI-based algorithm were comparable to those assigned by radiologists, indicating the accuracy and high reproducibility of our model. Our study findings would enable accurate reading, particularly in areas where radiologists are unavailable, and contribute to improvements in patient management and workflow.

Quantitative measurements of emphysema in ultra-high resolution computed tomography using model-based iterative reconstruction in comparison to that using hybrid iterative reconstruction.

The percentage of low attenuation volume ratio (LAVR), which is measured using computed tomography (CT), is an index of the severity of emphysema. For LAVR evaluation, ultra-high-resolution (U-HR) CT images are useful. To improve the image quality of U-HRCT, iterative reconstruction is used. There are two types of iterative reconstruction: hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR). In this study, we physically and clinically evaluated U-HR images reconstructed with HIR and MBIR, and demonstrated the usefulness of U-HR images with MBIR for quantitative measurements of emphysema. Both images were reconstructed with a slice thickness of 0.25 mm and an image matrix size of 1024 × 1024 pixels. For physical evaluation, the modulation transfer function (MTF) and noise power spectrum (NPS) of HIR and MBIR were compared. For clinical evaluation, LAVR calculated from HIR and MBIR were compared using the Wilcoxon matched-pairs signed-rank test. In addition, the correlation between LAVR and forced expiratory volume in one second (FEV1%) was evaluated using the Spearman rank correlation test. The MTFs of HIR and MBIR were comparable. The NPS of MBIR was lower than that of HIR. The mean LAVR values calculated from HIR and MBIR were 19.5 ± 12.6% and 20.4 ± 11.7%, respectively (p = 0.84). The correlation coefficients between LAVR and FEV1% that were taken from HIR and MBIR were 0.64 and 0.74, respectively (p < 0.01). MBIR is more useful than HIR for the quantitative measurements of emphysema with U-HR images.

Real-world evaluation of a computed tomography-first triage strategy for suspected Coronavirus disease 2019 in outpatients in Japan: An observational cohort study.

ABSTRACT: The Coronavirus disease 2019 pandemic continues to spread worldwide. Because of the absence of reliable rapid diagnostic systems, patients with symptoms of Coronavirus disease 2019 are treated as suspected of the disease. Use of computed tomography findings in Coronavirus disease 2019 are expected to be a reasonable method for triaging patients, and computed tomography-first triage strategies have been proposed. However, clinical evaluation of a computed tomography-first triage protocol is lacking.The aim of this study is to investigate the real-world efficacy and limitations of a computed tomography-first triage strategy in patients with suspected Coronavirus disease 2019.This was a single-center cohort study evaluating outpatients with fever who received medical examination at Yokohama City University Hospital, prospectively registered between 9 February and 5 May 2020. We treated according to the computed tomography-first triage protocol. The primary outcome was efficacy of the computed tomography-first triage protocol for patients with fever in an outpatient clinic. Efficacy of the computed tomography-first triage protocol for outpatients with fever was evaluated using sensitivity, specificity, positive predictive value, and negative predictive value. We conducted additional analyses of the isolation time of feverish outpatients and final diagnoses.In total, 108 consecutive outpatients with fever were examined at our hospital. Using the computed tomography-first triage protocol, 48 (44.9%) patients were classified as suspected Coronavirus disease 2019. Nine patients (18.8%) in this group were positive for severe acute respiratory syndrome coronavirus 2 using polymerase chain reaction; no patients in the group considered less likely to have Coronavirus disease 2019 tested positive for the virus. The protocol significantly shortened the duration of isolation for the not-suspected versus the suspected group (70.5 vs 1037.0 minutes, P < .001).Our computed tomography-first triage protocol was acceptable for screening patients with suspected Coronavirus disease 2019. This protocol will be helpful for appropriate triage, especially in areas where polymerase chain reaction is inadequate.

Unenhanced CT texture analysis with machine learning for differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma.

Differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma (ML) remains challenging on cross-sectional images. The aim of this study is to investigate the usefulness of texture features on unenhanced CT for differentiating between nasopharyngeal cancer and nasopharyngeal ML. Thirty patients with nasopharyngeal tumors, including 17 nasopharyngeal cancers and 13 nasopharyngeal MLs, were underwent 18F-FDG PET/CT. All nasopharyngeal cancers and 7 of 13 nasopharyngeal MLs were confirmed by endoscopic biopsy. On unenhanced CT, 34 texture features were analyzed following lesion segmentation in the maximum area of the target lesion. The Mann-Whitney U test and areas under the curve (AUCs) were used for analysis and to compare the maximum standardized uptake values (SUV)max, SUVmean, and 34 texture features. A support vector machine (SVM) was constructed to evaluate the diagnostic accuracy and AUCs of combinations of texture features, with 50 repetitions of 5-fold cross-validation. Differences between the SUVmax and SUVmean for nasopharyngeal cancers and nasopharyngeal MLs were not significant. Significant differences of texture features were seen, as follows: 1 histogram feature (p = 0.038), 3 gray-level co-occurrence matrix features (p < 0.05), and 1 neighborhood gray-level different matrix feature (NGLDM) (p = 0.003). Coarseness in NGLDM provided the highest diagnostic accuracy and largest AUC of 76.7% and 0.82, respectively. SVM evaluation of the combined texture features obtained the highest accuracy of 81.3%, with an AUC of 0.80. Combined texture features can provide useful information for discriminating between nasopharyngeal cancer and nasopharyngeal ML on unenhanced CT.

Nodal-based radiomics analysis for identifying cervical lymph node metastasis at levels I and II in patients with oral squamous cell carcinoma using contrast-enhanced computed tomography.

OBJECTIVE: Discriminating metastatic from benign cervical lymph nodes (LNs) in oral squamous cell carcinoma (OSCC) patients using pretreatment computed tomography (CT) has been controversial. This study aimed to investigate whether CT-based texture analysis with machine learning can accurately identify cervical lymph node metastasis in OSCC patients. METHODS: Twenty-three patients (with 201 cervical LNs [150 benign, 51 metastatic] at levels I-V) who underwent preoperative contrast-enhanced CT and subsequent cervical neck dissection were enrolled. Histopathologically proven LNs were randomly divided into the training cohort (70%; n = 141, at levels I-V) and validation cohort (30%; n = 60, at level I/II). Twenty-five texture features and the nodal size of targeted LNs were analyzed on the CT scans. The nodal-based sensitivities, specificities, diagnostic accuracy rates, and the area under the curves (AUCs) of the receiver operating characteristic curves of combined features using a support vector machine (SVM) at levels I/II, I, and II were evaluated and compared with two radiologists and a dentist (readers). RESULTS: In the validation cohort, the AUCs (0.820 at level I/II, 0.820 at level I, and 0.930 at level II, respectively) of the radiomics approach were superior to three readers (0.798-0.816, 0.773-0.798, and 0.825-0.865, respectively). The best models were more specific at levels I/II and I and accurate at each level than each of the readers (p < .05). CONCLUSIONS: Machine learning-based analysis with contrast-enhanced CT can be used to noninvasively differentiate between benign and metastatic cervical LNs in OSCC patients. KEY POINTS: • The best algorithm in the validation cohort can noninvasively differentiate between benign and metastatic cervical LNs at levels I/II, I, and II. • The AUCs of the model at each level were superior to those of multireaders. • Significant differences in the specificities at level I/II and I and diagnostic accuracy rates at each level between the model and multireaders were found.

Assessment of pleural invasion and adhesion of lung tumors with dynamic chest radiography: A virtual clinical imaging study.

PURPOSE: Accurate preoperative assessment of tumor invasion/adhesion is crucial for planning appropriate operative procedures. Recent advances in digital radiography allow a motion analysis of lung tumors with dynamic chest radiography (DCR) with total exposure dose comparable to that of conventional chest radiography. The aim of this study was to investigate the feasibility of preoperative evaluation of pleural invasion/adhesion of lung tumors with DCR through a virtual clinical imaging study, using a four-dimensional (4D) extended cardiac-torso (XCAT) computational phantom. METHODS: An XCAT phantom of an adult man (50th percentile in height and weight) with simulated respiratory and cardiac motions was generated to use as a virtual patient. To simulate lung tumors with and without pleural invasion, a 30-mm diameter tumor sphere was inserted into each lobe of the phantom. The virtual patient during respiration was virtually projected using an x-ray simulator in posteroanterior (PA) and oblique directions, and sequential bone suppression (BS) images were created. The measurement points (tumor, rib, and diaphragm) were automatically tracked on simulated images by a template matching technique. We calculated five quantitative metrics related to the movement distance and directions of the targeted tumor and evaluated whether DCR could distinguish between tumors with and without pleural invasion/adhesion. RESULTS: Precise tracking of the targeted tumor was achieved on the simulated BS images without undue influence of rib shadows. There was a significant difference in all five quantitative metrics between the lung tumors with and without pleural invasion both on the oblique and PA projection views (P < 0.05). Quantitative metrics related to the movement distance were effective for tumors in the middle and lower lobes, while, those related to the movement directions were effective for tumors close to the frontal chest wall on the oblique projection view. The oblique views were useful for the evaluation of the space between the chest wall and a moving tumor. CONCLUSION: DCR could help distinguish between tumors with and without pleural invasion/adhesion based on the two-dimensional movement distance and direction using oblique and PA projection views. With anticipated improved image: processing to evaluate the respiratory displacement of lung tumors in the upper lobe or behind the heart, DCR holds promise for clinical assessment of tumor invasion/adhesion in the parietal pleura.

Deep Learning for the Preoperative Diagnosis of Metastatic Cervical Lymph Nodes on Contrast-Enhanced Computed ToMography in Patients with Oral Squamous Cell Carcinoma.

We investigated the value of deep learning (DL) in differentiating between benign and metastatic cervical lymph nodes (LNs) using pretreatment contrast-enhanced computed tomography (CT). This retrospective study analyzed 86 metastatic and 234 benign (non-metastatic) cervical LNs at levels I-V in 39 patients with oral squamous cell carcinoma (OSCC) who underwent preoperative CT and neck dissection. LNs were randomly divided into training (70%), validation (10%), and test (20%) sets. For the validation and test sets, cervical LNs at levels I-II were evaluated. Convolutional neural network analysis was performed using Xception architecture. Two radiologists evaluated the possibility of metastasis to cervical LNs using a 4-point scale. The area under the curve of the DL model and the radiologists' assessments were calculated and compared at levels I-II, I, and II. In the test set, the area under the curves at levels I-II (0.898) and II (0.967) were significantly higher than those of each reader (both, p < 0.05). DL analysis of pretreatment contrast-enhanced CT can help classify cervical LNs in patients with OSCC with better diagnostic performance than radiologists' assessments alone. DL may be a valuable diagnostic tool for differentiating between benign and metastatic cervical LNs.

Milk of calcium pericardial effusion confirmed with postmortem computed tomography and autopsy findings: A case report.

We present the postmortem computed tomography and autopsy findings of a 60-year-old man who developed milk of calcium pericardial effusion and died of constrictive epicarditis. He experienced out-of-hospital cardiopulmonary arrest, and spontaneous circulation returned at the hospital. However, 7 h after recovery, the patient died. He had a swollen neck, had been experiencing coughing from 4 to 5 days earlier, and had no significant medical or surgical history. On computed tomography (CT), highly dense pericardial fluid (CT value: 130-150 Hounsfield units) and multiple calcifications along the epicardium and pericardium were visualized. The epicardium and pericardium were thick, hard, rough, and widely calcified with mild adhesions on autopsy. The pericardial cavity contained a pale, reddish brown, turbid, and highly viscous liquid. Bacteriological tests of pericardial fluid cultures revealed the presence of group G ß-hemolytic streptococci. Hence, we diagnosed the patient's cause of death as heart failure due to constrictive epicarditis. We believe that this case of milk of calcium pericardial effusion is the first case confirmed with postmortem CT and autopsy findings.

Correlation between Computed Tomographic Analysis and Pulmonary Function Measurements in Patients with Relapsing Polychondritis.

BACKGROUND: Relapsing polychondritis (RP) is a rare systemic disease of unknown origin, with cartilaginous involvement in multiple organs. Airway involvement is the most important prognostic factor in RP. OBJECTIVES: Spirometric measurements and minimum tracheal cross-sectional area (mtCSA) have been reported as useful to assess the degree of airway stenosis. Because the length and severity of tracheal involvement in RP can vary, mtCSA might not provide enough information to assess tracheal abnormalities. We introduced tracheal volume (TrV) as a new method to evaluate correlations between chest computed tomography (CT) measurements and pulmonary function tests, including impulse oscillometry (IOS). METHOD: We analyzed chest CT images, spirometry, and IOS collected at our institution from April 2004 to March 2019. We calculated correlations between chest CT measurements using software (TrV, TrV/tracheal length [TrV/TL], and mtCSA) and pulmonary function parameters. RESULTS: Twenty-five of 73 clinically diagnosed patients with RP were included. Spirometric findings showed moderate airway obstruction. Peak flow (PEF) was strongly correlated with mtCSA, TrV, and TrV/TL (ρ = 0.74, p < 0.001). FEV1 was significantly correlated with mtCSA (ρ = 0.56, p = 0.004), TrV (ρ = 0.52, p = 0.007), and TrV/TL (ρ = 0.53, p = 0.006). Whereas respiratory resistance at 5 Hz (R5) and 20 Hz (R20) and resonant frequencies (RFs) were significantly correlated with TrV (ρ = -0.46, p = 0.021; ρ = -0.46, p = 0.046; and ρ = -0.42, p = 0.037, respectively), IOS parameters and mtCSA were not. CONCLUSIONS: In patients with RP, TrV and mtCSA were strongly correlated with spirometric measurements. Respiratory resistances assessed by IOS correlated only with TrV. This suggests TrV assessment reflects pulmonary function in patients with RP more appropriately than mtCSA.

Usability of the lateral decubitus position on four-dimensional ultra-low-dose computed tomography for the detection of localized pleural adhesion in the pulmonary apical region.

BACKGROUND: Localized pleural adhesion (LPA) evaluation in the apical region is difficult even with four-dimensional ultra-low-dose computed tomography (4D-ULDCT) in the supine position due to smaller pleural movements. PURPOSE: To assess usability of 4D-ULDCT in the lateral decubitus (LD) position for LPA detection in the apical region. MATERIAL AND METHODS: Forty-seven patients underwent 4D-ULDCT of a single respiration cycle with 16-cm coverage of body axis in supine and LD positions with the affected lung uppermost. Intraoperative thoracoscopic findings confirmed LPA presence. A pleural point and a corresponding point on costal outer edge were placed in identical axial planes at end-inspiration. Pleuro-chest wall distance between two points (PCD) was calculated at each respiratory phase. In the affected lung, average change in amount of PCD (PCDACA) was compared between patients with and without LPA in total and two sub-groups (non-COPD and COPD, non-emphysematous and emphysematous patients) in supine and non-dependent (ND) LD positions. Receiver operating characteristic (ROC) curve analysis was performed to determine optimal thresholds in PCDACA for differentiating patients with LPA from those without. RESULTS: In COPD/emphysematous patients and total population, PCDACA with LPA was smaller than in those without in the supine and NDLD positions for overall, lateral, and dorsal regions. For the lateral region in COPD patients, area under ROC curve (AUC) increased from supine (0.64) to NDLD position (0.81). For the dorsal region in emphysematous patients, AUC increased from supine (0.76) to NDLD position (0.96). CONCLUSION: 4D-ULDCT in LD position may be useful for LPA detection in apical regions for COPD and/or emphysematous patients.