scholarly journals Imaging Biomarkers of Contrast-enhanced Computed Tomography Predict Survival in Oesophageal Cancer After Definitive Concurrent Chemoradiotherapy

2020 ◽  
Author(s):  
Chengbing Zeng ◽  
Tiantian Zhai ◽  
Jianzhou Chen ◽  
Longjia Guo ◽  
Baotian Huang ◽  
...  
Keyword(s):  
Validation Cohort ◽  
Imaging Biomarkers ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Treatment Contrast ◽  
Pre Treatment ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Abstract Background: This study aimed to evaluate the predictive potential of contrast-enhanced computed tomography (CT)-based imaging biomarkers (IBMs) for the treatment outcomes of oesophageal squamous cell carcinoma (OSCC) patients after definitive concurrent chemoradiotherapy (CCRT).Methods: A total of 151 ESCC patients who underwent definitive CCRT were included in this retrospective study. All patients were separated randomly to a training cohort (n=97) and the validation cohort (n=54). Pre-treatment contrast-enhanced CT scans were obtained for all patients and used for the extraction of IBMs. An IBM score was constructed by using the least absolute shrinkage and selection operator with logistic regression analysis in training cohort and tested in the validation cohort. IBMsnomograms were built based on IBM score. The concordance index (C-index) was used to assess the performance of the nomograms. Finally, decision curve analysis was performed to estimate the clinical usefulness of the nomograms.Results: A total of 96 IBMs were extracted from each contrast-enhanced CT scan. The IBM score were consisted of 13 CT-based IBMs and were significantly correlated with 3-year overall survival (OS) and 3-year progression-free survival (PFS). Multivariate analysis revealed that IBM score was the independent prognostic factor. In the training cohort, the IBM score yielded an area under the curves (AUCs) of 0.802 (95% CI: 0.713–0.891, p<0.001) and 0.742 (95% CI: 0.620–0.889, p<0.001) in terms of 3-year OS and 3-year PFS, respectively. In validation cohort, the AUCs were 0.761(95% CI: 0. 639–0.900, p<0.001) and 0.761(95% CI: 0.629–0.893, p=0.001) for 3-year OS and 3-year PFS,respectively. Kaplan-Meier survival analysis showed significantly different between risk subgroups in training and validation cohort. The nomograms were built based on the IBM score showed good discrimination. In the training cohort, with the C-indices of IBMsnomograms were 0.732 (95%CI, 0.661–0.803) and 0.670(95%CI, 0.595–0.745) for OS and PFS, respectively. In the validation cohort C-indices were 0.677(95%CI, 0.583–0.771) and 0.678(95%CI, 0.591–0.765) for OS and PFS, respectively. The decision curve showed the clinical usefulness of nomograms.Conclusions: TheIBM score based on pre-treatment contrast-enhanced CT could predict the 3-year OS and 3-year PFS for OSCC patients after definitive CCRT. Further multicenter studies with larger sample sizes are warranted.

scholarly journals Imaging biomarkers of contrast-enhanced computed tomography predict survival in oesophageal cancer after definitive concurrent chemoradiotherapy

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Chengbing Zeng ◽  
Tiantian Zhai ◽  
Jianzhou Chen ◽  
Longjia Guo ◽  
Baotian Huang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Imaging Biomarkers ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Treatment Contrast ◽  
Pre Treatment ◽  
Enhanced Computed Tomography

Abstract Background This study aimed to evaluate the predictive potential of contrast-enhanced computed tomography (CT)-based imaging biomarkers (IBMs) for the treatment outcomes of patients with oesophageal squamous cell carcinoma (OSCC) after definitive concurrent chemoradiotherapy (CCRT). Methods Altogether, 154 patients with OSCC who underwent definitive CCRT were included in this retrospective study. All patients were randomised to the training cohort (n = 99) or the validation cohort (n = 55). Pre-treatment contrast-enhanced CT scans were obtained for all patients and used for the extraction of IBMs. An IBM score, was constructed by using the least absolute shrinkage and selection operator with Cox regression analysis, which was equal to the log-partial hazard of the Cox model in the training cohort and tested in the validation cohort. IBM nomograms were built based on IBM scores for individualised survival estimation. Finally, a decision curve analysis was performed to estimate the clinical usefulness of the nomograms. Results Altogether, 96 IBMs were extracted from each contrast-enhanced CT scan. IBM scores were constructed from 11 CT-based IBMs for overall survival (OS) and 8 IBMs for progression-free survival (PFS), using the LASSO-Cox regression method in the training cohort. Multivariate analysis revealed that IBM score was an independent prognostic factor correlated with OS and PFS. In the training cohort, the C-indices of IBM scores were 0.734 (95% CI 0.664–0.804) and 0.658 (95% CI 0.587–0.729) for OS and PFS, respectively. In the validation cohort, C-indices were 0.672 (95% CI 0.578–0.766) and 0.666 (95% CI 0.574–0.758) for OS and PFS, respectively. Kaplan–Meier survival analysis showed a significant difference between risk subgroups in the training and validation cohorts. Decision curve analysis confirmed the clinical usefulness of the IBM score. Conclusions The IBM score based on pre-treatment contrast-enhanced CT could predict the OS and PFS for patients with OSCC after definitive CCRT. Further multicentre studies with larger sample sizes are warranted.

scholarly journals Imaging biomarkers of contrast-enhanced computed tomography predict survival in oesophageal cancer after definitive concurrent chemoradiotherapy

2020 ◽  
Author(s):  
Chengbing Zeng ◽  
Tiantian Zhai ◽  
Jianzhou Chen ◽  
Longjia Guo ◽  
Baotian Huang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Imaging Biomarkers ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Treatment Contrast ◽  
Pre Treatment ◽  
Enhanced Computed Tomography

Abstract Background: This study aimed to evaluate the predictive potential of contrast-enhanced computed tomography (CT)-based imaging biomarkers (IBMs) for the treatment outcomes of patients with oesophageal squamous cell carcinoma (OSCC) after definitive concurrent chemoradiotherapy (CCRT).Methods: Altogether, 154 patients with OSCC who underwent definitive CCRT were included in this retrospective study. All patients were randomised to the training cohort (n=99) or the validation cohort (n=55). Pre-treatment contrast-enhanced CT scans were obtained for all patients and used for the extraction of IBMs. An IBM score, was constructed by using the least absolute shrinkage and selection operator with Cox regression analysis, which was equal to the log-partial hazard of the Cox model in the training cohort and tested in the validation cohort. IBM nomograms were built based on IBM scores for individualised survival estimation. Finally, a decision curve analysis was performed to estimate the clinical usefulness of the nomograms.Results: Altogether, 96 IBMs were extracted from each contrast-enhanced CT scan. IBM scores were constructed from 11 CT-based IBMs for overall survival (OS) and 8 IBMs for progression-free survival (PFS), using the LASSO-Cox regression method in the training cohort. Multivariate analysis revealed that IBM score was an independent prognostic factor correlated with OS and PFS. In the training cohort, the C-indices of IBM scores were 0.734 (95%CI, 0.664–0.804) and 0.658 (95%CI, 0.587–0.729) for OS and PFS, respectively. In the validation cohort, C-indices were 0.672 (95%CI, 0.578–0.766) and 0.666 (95%CI, 0.574–0.758) for OS and PFS, respectively. Kaplan-Meier survival analysis showed a significant difference between risk subgroups in the training and validation cohorts. Decision curve analysis confirmed the clinical usefulness of the IBM score.Conclusions: The IBM score based on pre-treatment contrast-enhanced CT could predict the OS and PFS for patients with OSCC after definitive CCRT. Further multicentre studies with larger sample sizes are warranted.

scholarly journals Imaging biomarkers of contrast-enhanced computed tomography predict survival in oesophageal cancer after definitive concurrent chemoradiotherapy

2020 ◽  
Author(s):  
Chengbing Zeng ◽  
Tiantian Zhai ◽  
Jianzhou Chen ◽  
Longjia Guo ◽  
Baotian Huang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Imaging Biomarkers ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Treatment Contrast ◽  
Pre Treatment ◽  
Enhanced Computed Tomography

Abstract Background: This study aimed to evaluate the predictive potential of contrast-enhanced computed tomography (CT)-based imaging biomarkers (IBMs) for the treatment outcomes of patients with oesophageal squamous cell carcinoma (OSCC) after definitive concurrent chemoradiotherapy (CCRT).Methods: Altogether, 154 patients with OSCC who underwent definitive CCRT were included in this retrospective study. All patients were randomised to the training cohort (n=99) or the validation cohort (n=55). Pre-treatment contrast-enhanced CT scans were obtained for all patients and used for the extraction of IBMs. An IBM score was constructed by using the least absolute shrinkage and selection operator with Cox regression analysis in the training cohort and tested in the validation cohort. IBM nomograms were built based on IBM scores for individualised survival estimation. Finally, a decision curve analysis was performed to estimate the clinical usefulness of the nomograms.Results: Altogether, 96 IBMs were extracted from each contrast-enhanced CT scan. IBM scores were constructed from 11 CT-based IBMs for overall survival (OS) and 8 IBMs for progression-free survival (PFS), using the LASSO-Cox regression method in the training cohort. Multivariate analysis revealed that IBM score was an independent prognostic factor correlated with OS and PFS. In the training cohort, the C-indices of IBM scores were 0.734 (95%CI, 0.664–0.804) and 0.658 (95%CI, 0.587–0.729) for OS and PFS, respectively. In the validation cohort, C-indices were 0.672 (95%CI, 0.578–0.766) and 0.666 (95%CI, 0.574–0.758) for OS and PFS, respectively. Kaplan-Meier survival analysis showed a significant difference between risk subgroups in the training and validation cohorts. Decision curve analysis confirmed the clinical usefulness of the IBM score.Conclusions: The IBM score based on pre-treatment contrast-enhanced CT could predict the OS and PFS for patients with OSCC after definitive CCRT. Further multicentre studies with larger sample sizes are warranted.

scholarly journals Imaging biomarkers of contrast-enhanced computed tomography predict survival in oesophageal cancer after definitive concurrent chemoradiotherapy

2020 ◽  
Author(s):  
Chengbing Zeng ◽  
Tiantian Zhai ◽  
Jianzhou Chen ◽  
Longjia Guo ◽  
Baotian Huang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Imaging Biomarkers ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Treatment Contrast ◽  
Pre Treatment ◽  
Enhanced Computed Tomography

Abstract Background: This study aimed to evaluate the predictive potential of contrast-enhanced computed tomography (CT)-based imaging biomarkers (IBMs) for the treatment outcomes of oesophageal squamous cell carcinoma (OSCC) patients after definitive concurrent chemoradiotherapy (CCRT). Methods: Altogether, 154 patients with OSCC who underwent definitive CCRT were included in this retrospective study. All patients were separated randomly to a training cohort (n=99) and the validation cohort (n=55). Pre-treatment contrast-enhanced CT scans were obtained for all patients and used for the extraction of IBMs. An IBM score was constructed by using the least absolute shrinkage and selection operator with Cox regression analysis in the training cohort and tested in the validation cohort. IBM nomograms were built based on IBM scores for individualized survival estimation. Finally, a decision curve analysis was performed to estimate the clinical usefulness of the nomograms. Results: Altogether, 96 IBMs were extracted from each contrast-enhanced CT scan. The IBM score constructed by 11 CT-based IBMs, using LASSO-Cox regression method in training cohort. The multivariate analysis revealed that IBM score was the independent prognostic factor correlated with overall survival (OS) and progression-free survival (PFS). In the training cohort, the C-indices of IBM scores were 0.734 (95%CI, 0.664–0.804) and 0.678 (95%CI, 0.607–0.745) for OS and PFS, respectively. In the validation cohort, C-indices were 0.672 (95%CI, 0.578–0.766) and 0.662 (95%CI, 0.573–0.751) for OS and PFS, respectively. Kaplan-Meier survival analysis showed significantly different between risk subgroups in training and validation cohort. The decision curve showed the clinical usefulness of IBM score. Conclusions: The IBM score based on pre-treatment contrast-enhanced CT could predict the OS and PFS for patients with OSCC after definitive CCRT. Further multicentre studies with larger sample sizes are warranted.

Predictive model for microvascular invasion of hepatocellular carcinoma among candidates for either hepatectomy or liver transplantation.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 4079-4079
Author(s):  
Hidetoshi Nitta ◽  
Marc Antoine Allard ◽  
Mylene Sebagh ◽  
Gabriella Pittau ◽  
Oriana Ciacio ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Predictive Model ◽  
Validation Cohort ◽  
Microvascular Invasion ◽  
Roc Curve Analysis ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct

4079 Background: Microvascular invasion (MVI) is the strongest prognostic factor following surgery of hepatocellular carcinoma (HCC). However, it is usually not available on the preoperative setting. A predictive model of MVI in patients scheduled for hepatic resection (HR) or liver transplantation (LT) would thus help guiding treatment strategy. The aim of this study was to develop a predictive model for MVI of HCC before either HR or LT. Methods: HCC patients who consecutively performed HR or LT from January 1994 to June 2016 at a single institution were subdivided into a training and validation cohort. Risk factors for MVI in the training cohort were used to develop a predictive model for MVI, to be validated in the validation cohort. The outcomes of the HR and LT patients with high or low MVI probability based on the model, were compared using propensity score matching (PSM). Cut-off values for continuous factors were determined based on ROC curve analysis. Results: A total of 910 patients (425 HR, 485 LT) were included in the training (n = 637) and validation (n = 273) cohorts. In the training cohort, multivariate analysis demonstrated that alpha-fetoprotein ≥100ng/ml ( p < 0.0001), largest tumor size ≥40mm ( p = 0.0002), non-boundary HCC type on contrast-enhanced CT ( p = 0.001), neutrophils-to-lymphocytes ratio ≥3.2 ( p = 0.002), aspartate aminotransferase ≥62U/l ( p = 0.02) were independently associated with MVI. Combinations of these 5 factors varied the MVI probability from 15.5% to 91.1%. This predictive model achieved a good c-index of 0.76 in the validation cohort. In PSM (109 HR, 109 LT), there was no difference in survival between HR and LT patients among the high MVI probability (≥50%) patients, (5y-OS; 46.3% vs 42.2%, p = 0.77, 5y-RFS; 54.0% vs 28.8%, p = 0.21). Among the low probability ( < 50%), survival was significantly decreased following HR compared with LT (5y-OS; 54.1% vs 78.8%, p = 0.007, 5y-RFS; 17.3% vs 86.1%, p< 0.0001). Conclusions: This model developed from preoperative data allows reliable prediction of MVI, and may thus help with preoperative decisions about the suitability of HR or LT in patients with HCC.

scholarly journals Misdiagnosis of Rectus Abdominis Abscess Owing to Delayed Contrast-Enhanced Computed Tomography

2021 ◽  
Author(s):  
Yuichiro Nagase ◽  
Yukinori Harada
Keyword(s):  
Computed Tomography ◽  
Laboratory Tests ◽  
Rectus Abdominis ◽  
Rectus Abdominis Muscle ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
The Right ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

A 77-year-old man, who was on anticoagulation, presented with a painful lump on the right abdominal wall. Laboratory tests showed slight anaemia and elevated inflammatory markers. Abdominal plain computed tomography (CT) revealed a mass in the right rectus abdominis muscle. He was admitted with a diagnosis of primary rectus abdominis haematoma. However, on the next day, the diagnosis was corrected to primary rectus abdominis abscess, following contrast-enhanced CT of the abdomen. This case illustrates the importance of considering primary rectus abdominis abscess in patients with suspected primary rectus abdominis haematoma, and contrast should be used when performing CT.

scholarly journals Differentiating Central Lung Tumors from Atelectasis with Contrast-Enhanced CT-Based Radiomics Features

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Rui Chai ◽  
Qi Wang ◽  
Pinle Qin ◽  
Jianchao Zeng ◽  
Jiwei Ren ◽  
...  
Keyword(s):  
Information Gain ◽  
Ct Images ◽  
Classification Model ◽  
Lung Cancers ◽  
Contrast Enhanced Ct ◽  
Pulmonary Cancer ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Objectives. To evaluate the utility of radiomics features in differentiating central lung cancers and atelectasis on contrast-enhanced computed tomography (CT) images. This study is retrospective. Materials and Methods. In this study, 36 patients with central pulmonary cancer and atelectasis between July 2013 and June 2018 were identified. A total of 1,653 2D and 2,327 3D radiomics features were extracted from segmented lung cancers and atelectasis on contrast-enhanced CT. The refined features were investigated for usefulness in classifying lung cancer and atelectasis according to the information gain, and 10 models were trained based on these features. The classification model is trained and tested at the region level and pixel level, respectively. Results. Among all the extracted features, 334 2D features and 1,507 3D features had an information gain (IG) greater than 0.1. The highest accuracy (AC) of the region classifiers was 0.9375. The best Dice score, Hausdorff distance, and voxel AC were 0.2076, 45.28, and 0.8675, respectively. Conclusions. Radiomics features derived from contrast-enhanced CT images can differentiate lung cancers and atelectasis at the regional and voxel levels.

scholarly journals Contrast-enhanced computed tomography for optimizing the outcomes of pulmonary vein isolation with cryoablation -the role of isolation of PVs including carina-

2021 ◽  
Author(s):  
Yusuke Sakamoto ◽  
Hiroyuki Osanai ◽  
Yuki Tanaka ◽  
Shotaro Hiramatsu ◽  
Hikari Matsumoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Atrial Fibrillation ◽  
Pulmonary Vein ◽  
Clinical Course ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Early Success ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Abstract Purpose Compared with conventional pulmonary vein isolation (PVI) with radiofrequency ablation, PVI with cryoballoon is an easier and shorter procedure without reconnection, particularly in the superior pulmonary vein. However, the durability of the cryoballoon may be reduced due to anatomical factors and the position of the pulmonary vein (PV). Further, inadequate isolation of the carina leads to recurrence of atrial fibrillation (AF). We aimed to determine whether using contrast-enhanced computed tomography (CT) for patient selection improves the early success rate and prevents the recurrence of AF in PVI with cryoballoon. Methods We evaluated patients who underwent ablation for paroxysmal atrial fibrillation in our hospital between July 2019 and November 2020. After excluding patients with contraindications for cryoablation, 50 patients were selected through visual inspection of the results of preoperative contrast-enhanced CT. A treatment plan was established, and the clinical course and outcomes were followed up. Results Of the 200 PVs of the 50 patients, only 8 PVs (4%) were incompletely isolated with a single cryoablation. Six of the eight PVs were successfully isolated with additional cryoablation. Only 2 patients (4%) underwent additional PVI with radiofrequency ablation. Four patients had AF recurrence within a mean follow-up period of 14.3 ± 5.1 months. The rate of sinus rhythm maintenance was 92%. PV reconnection was observed in 2 patients. None of the patients had postoperative atrial flutter. Conclusions Selecting patients for cryoablation according to contrast-enhanced CT findings made the procedure easier to perform, leading to improved early success rates and clinical course.

scholarly journals The prevalence of undiagnosed abnormalities on non-contrast-enhanced computed tomography compared to contrast-enhanced computed tomography of the brain

2014 ◽  
Vol 18 (1) ◽  
Author(s):  
Cornelia Minné ◽  
Margaret E. Kisansa ◽  
Nazeema Ebrahim ◽  
Farhana E. Suleman ◽  
Nonjabulo Z. Makhanya
Keyword(s):  
Computed Tomography ◽  
Brain Scans ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Ct Technology ◽  
Ct Brain ◽  
Enhanced Computed Tomography ◽  
The Brain ◽  
Contrast Enhanced Computed Tomography

Background: Even though magnetic resonance imaging (MRI) is the gold standard investigation for intracranial pathology, it is not widely available in developing countries and computed tomography (CT) of the brain remains the first-line investigation for patients with suspected intracranial pathology. It is generally accepted that certain intracranial pathology can be missed on non-contrast-enhanced CT (NECT) of the brain if a contrast-enhanced CT (CECT) is not done. We have to consider on the one hand the risk of delayed or missed diagnosis and on the other hand the cost, increased radiation exposure and contrast-induced reactions. Advances in CT technology have also improved the resolution of CT scan images, making it easier to identify pathology on an NECT of the brain. To date, no study comparing NECT to CECT of the brain, utilising 64-slice CT technology, has been published.Objectives: To determine the prevalence of undiagnosed abnormalities on non-contrast-enhanced computed tomography (NECT) scans of the brain reported as normal, on a 64-slice CT scanner.Method: A descriptive retrospective study was undertaken of CT brain scans done during a 12-month period at a tertiary provincial hospital in the Northern Tshwane district of Gauteng, South Africa. The CT brain scans were evaluated by three reviewers (general radiologists). The NECT and contrast-enhanced computed tomography (CECT) scans of the brain were reviewed independently on separate occasions. Reviewers were blinded to patient history, each other’s interpretation, and to their own interpretation of the NECT when evaluating the CECT and vice versa. Discrepancies in interpretation were resolved during a consensus meeting between all three reviewers. The reviewers also re-evaluated the NECT scans of the cases with undiagnosed abnormal findings during this session. A decision was made pertaining to the visibility of the abnormal findings on the NECT scan.Results: In this study, 3.28% of cases had abnormal findings undiagnosed by three reviewers on the NECT scans. Re-evaluation by the panel reduced this to 1.42%, indicating a reading error of 1.85%.Conclusion: There is a small prevalence of missed abnormal findings on the NECT scan when using only NECT. Omitting unnecessary CECT will reduce the radiation exposure to the patient and reduce the risk of adverse events from the use of intravenous iodinated contrast. Alternatively, doing only a CECT scan would reduce the risk of missing abnormal findings and would also decrease the patient’s exposure to radiation.

scholarly journals Morphological Changes of The Tricuspid Valve Complex in Functional Tricuspid Regurgitation On Contrast-Enhanced Computed Tomography

2021 ◽  
Author(s):  
Hiroki Uchiyama ◽  
Kazutoshi Tachibana ◽  
Koichi Osuda ◽  
Nobuyoshi Kawaharada
Keyword(s):  
Risk Factors ◽  
Odds Ratio ◽  
Papillary Muscles ◽  
Tricuspid Annulus ◽  
Functional Tricuspid Regurgitation ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Abstract Background: Whether it is possible to perform morphological evaluation of functional tricuspid regurgitation (FTR) on contrast-enhanced computed tomography (CT) was examined by evaluating the relationships between the parameters measured by contrast-enhanced CT and TR severity on transthoracic echocardiography.Methods: Fifty patients underwent contrast-enhanced CT. Tricuspid annulus area (TAA), tricuspid annulus circumference (TAC), right ventricular volume (RVV), and the distances between the tips and bases of the papillary muscles were measured on contrast-enhanced CT in diastole and systole. Fifty cases were divided into 34 in the TR ≤ mild group (none TR: 3 cases, trivial TR: 24 cases, mild TR: 7 cases), and 16 in the TR ≥ moderate group (moderate TR: 8 cases, severe TR: 8 cases) using the TR grade measured by transthoracic echocardiography, and then differences between the groups were examined.Results: Significant differences were found in TAA, TAC, and RVV (p<0.01) and the distances between the tips of the anterior and posterior papillary muscles (p<0.05) in both diastole and systole. Since the septal papillary muscle could not be identified in 18 cases (36.0%), only the distance between the anterior and posterior papillary muscles was measurable in all cases. On subgroup analysis, risk factors for FTR ≥ moderate were evaluated by multiple logistic regression analysis. The risk factors identified in the multivariable risk factor analysis were diastolic RVV (odds ratio 1.083 [95% confidence interval 1.029-1.139]) and systolic RVV (odds ratio 0.951 [95% confidence interval 0.906-0.997 ]).Conclusions: TAA, TAC, RVV, and the distance between the tips of the anterior and posterior papillary muscles measured on contrast-enhanced CT were shown to be significantly increased in the TR ≥ moderate group. Detailed morphological assessment of FTR is possible by contrast-enhanced CT.

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