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.

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.

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.

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.

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.

Predictive factors of posttreatment fracture by definitive radiotherapy for uterine cervical cancer.

PURPOSE: Fractures are known to shorten life expectancy and worsen the quality of life. The risk of fractures after radiation therapy in cervical cancer patients is known to be multifactorial. In this study, we examined risk factors for fractures in cervical cancer patients, especially by evaluating bone densities and DVH parameters for fractured bones. MATERIALS AND METHODS: For 42 patients, clinical characteristics, pretreatment CT bone densities, and radiation dose were compared between patients with and without fractures. RESULTS: Posttreatment fractures occurred in 25 bones among ten patients. Pretreatment CT bone densities were significantly lower in patients with fractures (P < 0.05-0.01 across sites, except for the ilium and the ischium). Although DVH parameters were also significantly associated with fractures in univariate analysis, only CT densities were significantly associated with fractures in multivariate analysis. CONCLUSION: Pretreatment CT densities of spinal and pelvic bones, which may reflect osteoporosis, have a significant impact on the risk for posttreatment fractures.

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.

CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer.

OBJECTIVES: To investigate the potential of computed tomography (CT)-based texture analysis and elastographic data provided by endobronchial ultrasonography (EBUS) for differentiating the mediastinal lymphadenopathy by sarcoidosis and small cell lung cancer (SCLC) metastasis. METHODS: Sixteen patients with sarcoidosis and 14 with SCLC were enrolled. On CT images showing the largest mediastinal lymph node, a fixed region of interest was drawn on the node, and texture features were automatically measured. Among the 30 patients, 19 (12 sarcoidosis and 7 SCLC) underwent endobronchial ultrasound transbronchial needle aspiration, and the fat-to-lesion strain ratio (FLR) was recorded. Texture features and FLRs were compared between the 2 patient groups. Logistic regression analysis was performed to evaluate the diagnostic accuracy of these measurements. RESULTS: Of the 31 texture features, the differences between 11 texture features of CT ROIs in the patients with sarcoidosis versus patients with SCLC were significant. Among them, the grey-level run length matrix with high gray-level run emphasis (GLRLM-HGRE) showed the greatest difference (P<0.01). Differences between FLRs were significant (P<0.05). Logistic regression analysis together with receiver operating characteristic curve analysis demonstrated that the FLR combined with the GLRLM-HGRE showed a high diagnostic accuracy (100% sensitivity, 92% specificity, 0.988 area under the curve) for discriminating between sarcoidosis and SCLC. CONCLUSION: Texture analysis, particularly combined with the FLR, is useful for discriminating between mediastinal lymphadenopathy caused by sarcoidosis from that caused by metastasis from SCLC.

Preoperative assessment of localized pleural adhesion: Utility of software-assisted analysis on dynamic-ventilation computed tomography.

PURPOSE: To assess the usefulness of software analysis using dynamic-ventilation CT for localized pleural adhesion (LPA). MATERIALS AND METHODS: Fifty-one patients scheduled to undergo surgery underwent both dynamic-ventilation CT and static chest CT as preoperative assessments. Five observers independently evaluated the presence and severity of LPA on a three-point scale (non, mild, and severe LPA) for 9 pleural regions (upper, middle, and lower pleural aspects on ventral, lateral, and dorsal areas) on the chest CT by three different methods by observing images from: static high-resolution CT (static image); dynamic-ventilation CT (movie image), and dynamic-ventilation CT while referring to the adhesion map (movie image with color map), which was created using research software to visualize movement differences between the lung surface and chest wall. The presence and severity of LPA was confirmed by intraoperative thoracoscopic findings. Parameters of diagnostic accuracy for LPA presence and severity were assessed among the three methods using Wilcoxon signed rank test in total and for each of the three pleural aspects. RESULTS: Mild and severe LPA were confirmed in 14 and 8 patients. Movie image with color map had higher sensitivity (56.9 ±â€¯10.7 %) and negative predictive value (NPV) (91.4 ±â€¯1.7 %) in LPA detection than both movie image and static image. Additionally, for severe LPA, detection sensitivity was the highest with movie image with color map (82.5 ±â€¯6.1 %), followed by movie image (58.8 ±â€¯17.0 %) and static image (38.8 ±â€¯13.9 %). For LPA severity, movie image with color map was similar to movie image and superior to static image in accuracy as well as underestimation and overestimation, with a mean value of 80.2 %. CONCLUSION: Software-assisted dynamic-ventilation CT may be a useful novel imaging approach to improve the detection performance of LPA.

Noninvasive flow evaluations of coronary artery bypass grafting using dynamic cardiac CT.

We aimed to investigate the correlation of graft flow measurements between transit-time flow measurement (TTFM) during coronary artery bypass grafting (CABG) surgery and dynamic cardiac CT after the surgery.Fourteen patients underwent CABG with TTFM and postoperative dynamic cardiac CT; 11 internal thoracic artery (ITA) grafts and 15 saphenous venous grafts (SVGs) were included for analysis. Pearsons correlation analysis was performed for the comparisons of the TTFM and cardiac dynamic CT flow parameters.TTFM was not significantly correlated with the CT flow of the ITA grafts (r = -0.23, P = .49), but it had a very strong correlation with the CT flow of the SVGs (r = 0.83, P < .01).In patients who underwent CABG surgery, dynamic cardiac CT enabled quantitative evaluation of SVG flow, with good correlation with TTFM.

Neuroendocrine carcinoma of uterine cervix findings shown by MRI for staging and survival analysis - Japan multicenter study.

OBJECTIVES: To investigate neuroendocrine carcinoma (NEC) of the uterine cervix cases for MRI features and staging, as well as pathological correlations and survival. RESULTS: FIGO was I in 42, II in 14, III in 1, and IV in 5 patients. T2-weighted MRI showed homogeneous slightly high signal intensity and obvious restricted diffusion (ADC map, low intensity; DWI, high intensity) throughout the tumor in most cases, and mild enhancement in two-thirds. In 50 patients who underwent a radical hysterectomy and lymphadenectomy without neoadjuvant chemotherapy (NAC), intrapelvic T staging by MRI overall accuracy was 88.0% with reference to pathology staging, while patient-based sensitivity, specificity, and accuracy for metastatic pelvic lymph node detection was 38.5%, 100%, and 83.3%, respectively. During a mean follow-up period of 45.6 months (range 4.3-151.0 months), 28 patients (45.2%) experienced recurrence and 24 (38.7%) died. Three-year progression-free and overall survival rates for FIGO I, II, III, and IV were 64.3% and 80.9%, 50% and 64.3%, 0% and 0%, and 0% and 0%, respectively. MATERIALS AND METHODS: Sixty-two patients with histologically surgery-proven uterine cervical NEC were enrolled. Twelve received NAC. Clinical data, pathological findings, and pretreatment pelvic MRI findings were retrospectively reviewed. Thirty-two tumors were pure NEC and 30 mixed with other histotypes. The NECs were small cell type (41), large cell type (18), or a mixture of both (3). CONCLUSIONS: Homogeneous lesion texture with obvious restricted diffusion throughout the tumor are features suggestive of cervical NEC. Our findings show that MRI is reliable for T staging of cervical NEC.

Improved Diagnostic Accuracy of Bone Metastasis Detection by Water-HAP Associated to Non-contrast CT.

We examined whether water-hydroxyapatite (HAP) images improve the diagnostic accuracy of bone metastasis compared with non-contrast CT alone. We retrospectively evaluated dual-energy computed tomography (DECT) images of 83 cancer patients (bone metastasis, 31; without bone metastasis, 52) from May 2018 to June 2019. Initially, two evaluators examined for bone metastasis on conventional CT images. In the second session, both CT and CT images plus water-HAP images on DECT. The confidence of bone metastasis was scored from 1 (benign) to 5 (malignant). The sensitivity, specificity, positive predictive values, and negative predictive values for both modalities were calculated based on true positive and negative findings. The intra-observer area under curve (AUC) for detecting bone metastasis was compared by receiver operating characteristic analysis. Kappa coefficient calculated the inter-observer agreement. In conventional CT images, sensitivity, specificity, positive predictive value, and negative predictive value of raters 1 and 2 for the identification of bone metastases were 0.742 and 0.710, 0.981 and 0.981, 0.958 and 0.957, and 0.864 and 0.850, respectively. In water-HAP, they were 1.00 and 1.00, 0.981 and 1.00, 0.969 and 1.00, and 1.00 and 1.00, respectively. In CT, AUCs were 0.861 and 0.845 in each observer. On water-HAP images, AUCs were 0.990 and 1.00. Kappa coefficient was 0.964 for CT and 0.976 for water-HAP images. The combination of CT and water-HAP images significantly increased diagnostic accuracy for detecting bone metastasis. Water-HAP images on DECT may enable accurate initial staging, reduced radiation exposure, and cost.

Measurement of stapes footplate thickness in otosclerosis by ultra-high-resolution computed tomography.

BACKGROUND: Ultra-high-resolution computed tomography (U-HRCT) utilizes a 1024 × 1024 matrix with 0.25-mm section thickness, offering better spatial resolution than conventional multi-detector row CT to detect anatomic data for otologic surgery. AIMS: We examined stapes footplate thickness using U-HRCT in relation to stapedotomy to predict the difficulty of the surgical procedure. MATERIALS AND METHODS: Subjects were 12 otosclerosis patients and 25 controls who underwent diagnostic U-HRCT. A profile curve (Hounsfield units) was used to measure stapes footplate thickness along a perpendicular line across the stapes footplate in a plane parallel to the lateral semicircular canal. RESULTS: Footplate thickness was smaller at the midpoint than just before the anterior crus and just after the posterior crus. Interobserver variability was lowest at the midpoint, where foot plate thickness was significantly greater in the affected ear in otosclerosis patients compared with controls (0.60 ± 0.09 mm vs 0.46 ± 0.04 mm; p < .001). Otosclerosis patients were detected using U-HRCT with a high area under the curve. Difficulty in the stapes opening procedure correlated with stapes footplate thickness. CONCLUSIONS: Footplate thickness on U-HRCT correlated with temporal bone anatomy and corresponded to surgical difficulty. Significance: U-HRCT-derived anatomic data is useful for evaluating the stapes.

CT radiomics analysis of lung cancers: Differentiation of squamous cell carcinoma from adenocarcinoma, a correlative study with FDG uptake.

BACKGROUND AND PURPOSE: Pulmonary squamous cell carcinoma (SCC) was reported to have significantly higher histogram_kurtosis obtained by unenhanced computed tomography (CT) and a greater maximum standardized uptake value (SUVmax) determined by 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) than pulmonary adenocarcinoma (AD). The first study aim was to investigate whether CT radiomics features could differentiate SCC from AD. The second aim was to investigate correlations between CT radiomics features and SUVmax. MATERIALS AND METHODS: Forty solid lung tumors < 3 cm in diameter pathologically proven to be SCC (n = 18) or AD (n = 22) were included. The SUVmax was determined by 18F-FDG-PET/CT and 42 CT radiomics features were obtained from unenhanced CT. A Mann-Whitney U test was used to compare the SUVmax and each CT radiomics feature to differentiate SCC from AD. The area under the curve (AUC) was calculated from receiver operating characteristic (ROC) analysis. A binary logistic regression analysis was performed for a combination of SUVmax with each CT radiomics feature. A Spearman rank correlation analysis was performed to determine correlations between SUVmax and CT radiomics features. RESULTS: Twenty-six of 42 CT radiomics features were significantly different between groups. The best AUC of the CT radiomics features was 0.81 for both the GLRLM_SRHGE and GLZLM_HGZE. The AUC value improved when the shape_sphericity feature was combined with SUVmax (AUC = 0.92). The CT radiomics features exhibiting strongest correlations with the SUVmax were different in both AD and SCC groups. CONCLUSION: CT radiomics features correlated with tumor structural characteristics of SCC and AD, and were closely related to metabolic information from FDG-PET/CT.

Peripheral bronchial luminal conspicuity on dynamic-ventilation computed tomography: association with radiation doses and temporal resolution by using an ex vivo porcine lung phantom.

BACKGROUND: It is still unclear which image reconstruction algorithm is appropriate for peripheral bronchial luminal conspicuity (PBLC) on dynamic-ventilation computed tomography (DVCT). PURPOSE: To assess the influence of radiation doses and temporal resolution (TR) on the association between movement velocity (MV) and PBLC on DVCT. MATERIAL AND METHODS: An ex vivo porcine lung phantom with simulated respiratory movement was scanned by 320-row CT at 240 mA and 10 mA. Peak and dip CT density and luminal area adjusted by values at end-inspiration (CTDpeak and CTDdip, luminal area ratio [LAR]) for PBLC and MVs were measured and visual scores (VS) were obtained at 12 measurement points on 13 frame images obtained at half and full reconstructions (TR 340 and 190 ms) during expiration. Size-specific dose estimate (SSDE) was applied to presume radiation dose. VS, CTDpeak, CTDdip, LAR, and their cross-correlation coefficients with MV (CCC) were compared among four methods with combinations of two reconstruction algorithms and two doses. RESULTS: The dose at 10 mA was presumed as 26 mA by SSDE for standard proportion adults. VS, CTDdip, CTDpeak, and LAR with half reconstruction at 10 mA (2.52 ± 0.59, 1.016 ± 0.221, 0.948 ± 0.103, and 0.990 ± 0.527) were similar to those at 240 mA except for VS, and different from those with full reconstruction at both doses (2.24 ± 0.85, 0.830 ± 0.209, 0.986 ± 0.065, and 1.012 ± 0.438 at 240 mA) (P < 0.05). CCC for CTDdip with half reconstruction (-0.024 ± 0.552) at 10 mA was higher compared with full reconstruction (-0.503 ± 0.291) (P < 0.05). CONCLUSION: PBLC with half reconstruction at 10 mA was comparable to that at 240 mA and better than those with full reconstruction on DVCT.

MRI findings of spring ligament injury: association with surgical findings and flatfoot deformity.

BACKGROUND: Spring ligament injury is an important cause for flatfoot deformity; however, reliability of magnetic resonance imaging (MRI) findings of spring ligament injury is still ambiguous. PURPOSE: To investigate the reliability of MRI findings for the diagnosis of spring ligament injury. MATERIAL AND METHODS: Forty-three cases with spring ligament injury proven by surgery and 29 control cases were enrolled. The spring ligament complex was demonstrated on proton density-weighted images reconstructed from 3D-isotropic MRI data. The presence of waviness, discontinuity, and abnormally high signal intensity of the spring ligament complex was evaluated by two radiologists in cooperation. Also, injury of the posterior tibial tendon (PTT) on MRI and the lateral talo-1st metatarsal angles on weight-bearing X-rays were evaluated. RESULTS: Discontinuity and abnormally high signal intensity of the superomedial calcaneonavicular ligament (SmCNL) on MRI were more frequently observed in patients with spring ligament injury than in controls (p < 0.001). Discontinuity and abnormally high signal intensity of the SmCNL were found more often in the PTT injury group than in those without (p < 0.001). The talo-1st metatarsal angle was greater in patients with discontinuity and abnormally high signal intensity of the SmCNL on MRI than in patients without these findings (p < 0.001). CONCLUSION: Discontinuity and abnormally high signal intensity are reliable MRI findings for spring ligament injury and related disorders, such as flatfoot deformity and PTT injury.

Preoperative assessment of parietal pleural invasion/adhesion of subpleural lung cancer: advantage of software-assisted analysis of 4-dimensional dynamic-ventilation computed tomography.

OBJECTIVE: To evaluate the accuracy of four-dimensional (4D) dynamic-ventilation computed tomography (CT) scanning coupled with our novel image analysis software to diagnose parietal pleural invasion/adhesion of peripheral (subpleural) lung cancer. METHODS: Eighteen patients with subpleural lung cancer underwent both 4D dynamic-ventilation CT during free breathing and conventional (static) chest CT during preoperative assessment. The absence of parietal pleural invasion/adhesion was surgically confirmed in 13 patients, while the presence of parietal pleural invasion/adhesion was confirmed in 5 patients. Two chest radiologists, who were blinded to patient status, cooperatively evaluated the presence of pleural invasion/adhesion using two different imaging modalities: (i) conventional high-resolution CT images, reconstructed in the axial, coronal, and sagittal directions, and (ii) 4D dynamic-ventilation CT images combined with a color map created by image analysis software to visualize movement differences between the lung surface and chest wall. Parameters of diagnostic accuracy were assessed, including a receiver operating characteristic analysis. RESULTS: Software-assisted 4D dynamic-ventilation CT images achieved perfect diagnostic accuracy for pleural invasion/adhesion (sensitivity, 100%; specificity, 100%; area under the curve [AUC], 1.000) compared to conventional chest CT (sensitivity, 60%; specificity, 77%; AUC, 0.846). CONCLUSION: Software-assisted 4D dynamic-ventilation CT can be considered as a novel imaging approach for accurate preoperative analysis of pleural invasion/adhesion of peripheral lung cancer. KEY POINTS: • 4D dynamic-ventilation CT can correctly assess parietal pleural invasion/adhesion of peripheral lung cancer. • A unique color map clearly demonstrates parietal pleural invasion/adhesion. • Our technique can be expanded to diagnose "benign" pleural adhesions for safer thoracoscopic surgery.

Thoracic manifestations of adult T-cell leukemia/lymphoma on chest CT: difference between clinical subtypes.

PURPOSE: We aimed to evaluate thoracic computed tomography (CT) findings in adult T-cell leukemia/lymphoma (ATL) and their differences among clinical subtypes. METHODS: Thoracic CT scans of 49 ATL patients were retrospectively reviewed. On CT scans, the presence of lung parenchymal abnormalities (10 patterns), enlarged lymph nodes, pleural and pericardial effusions, and subcutaneous nodules was evaluated by two radiologists in cooperation. According to the Shimoyama criteria, the patients were divided into aggressive ATL group (n=28, acute and lymphoma types) and indolent ATL group (n=21, chronic and smoldering types). Differences in the prevalence of the CT findings between the two groups were examined. In the indolent ATL group, CT scans of 10 patients who eventually underwent transformation to aggressive ATL were also evaluated. RESULTS: In aggressive ATL, enlarged lymph nodes (68%) was the most frequently observed finding. Several patterns of lung abnormalities were observed, such as ground-glass attenuation (36%), bronchial wall thickening (32%), nodules (29%), and centrilobular opacities (29%). In indolent ATL, enlarged lymph nodules (24%) and bronchiectasis (24%) were relatively frequently detected. Overall, the incidence of abnormal findings was higher in aggressive than in indolent ATL, except for bronchiectasis. Patients with transformation to aggressive ATL frequently demonstrated enlarged lymph nodes (80%). CONCLUSION: On thoracic CT, enlarged lymph nodes and various lung and airway abnormalities, such as ground-glass attenuation and bronchial wall thickening, were observed in ATL patients, particularly those with aggressive ATL. Bronchiectasis was similarly found in patients with indolent ATL and aggressive ATL.

Strain measurement on four-dimensional dynamic-ventilation CT: quantitative analysis of abnormal respiratory deformation of the lung in COPD.

PURPOSE: Strain measurement is frequently used to assess myocardial motion in cardiac imaging. This study aimed to apply strain measurement to pulmonary motion observed by four-dimensional dynamic-ventilation computed tomography (CT) and to clarify motion abnormality in COPD. MATERIALS AND METHODS: Thirty-two smokers, including ten with COPD, underwent dynamic-ventilation CT during spontaneous breathing. CT data were continuously reconstructed every 0.5 seconds. In the series of images obtained by dynamic-ventilation CT, five expiratory frames were identified starting from the peak inspiratory frame (first expiratory frame) and ending with the fifth expiratory frame. Strain measurement of the scanned lung was performed using research software that was originally developed for cardiac strain measurement and modified for assessing deformation of the lung. The measured strain values were divided by the change in mean lung density to adjust for the degree of expiration. Spearman's rank correlation analysis was used to evaluate associations between the adjusted strain measurements and various spirometric values. RESULTS: The adjusted strain measurement was negatively correlated with FEV1/FVC (ρ=-0.52, P<0.01), maximum mid-expiratory flow (ρ=-0.59, P<0.001), and peak expiratory flow (ρ=-0.48, P<0.01), suggesting that abnormal deformation of lung motion is related to various patterns of expiratory airflow limitation. CONCLUSION: Abnormal deformation of lung motion exists in COPD patients and can be quantitatively assessed by strain measurement using dynamic-ventilation CT. This technique can be expanded to dynamic-ventilation CT in patients with various lung and airway diseases that cause abnormal pulmonary motion.