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

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 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.

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.

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 Morphometric analysis of the splenic artery using contrast-enhanced computed tomography (CT)

2020 ◽  
Author(s):  
David J. Brinkman ◽  
Stephanie Troquay ◽  
Wouter J. de Jonge ◽  
Eric D. Irwin ◽  
Margriet J. Vervoordeldonk ◽  
...  
Keyword(s):  
Immune Modulation ◽  
Splenic Artery ◽  
Experimental Studies ◽  
Pancreatic Tissue ◽  
Branching Pattern ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
And Gender ◽  
Enhanced Computed Tomography

Abstract Purpose To evaluate the morphology and course of the splenic artery, which might impact the surgical implantation of systems that stimulate the nerves surrounding the splenic artery. Experimental studies indicate that these nerves play an important part in immune modulation, and might be a potential target in the treatment of autoimmune diseases. Methods This retrospective cohort study made use of contrast-enhanced CT images from 40 male and 40 female patients (age 30–69) that underwent a CT examination of the aorta, kidneys or pancreas. Anatomic features were described including total splenic artery length, calibers, tortuosity, the presence of arterial loops and the branching pattern of the splenic artery. Results No age-gender-related differences could be found related to tortuosity or branching pattern. The length of splenic artery in contact with pancreatic tissue decreased with increasing age, but was not different between genders. Artery diameters were wider in male compared to female subjects. Loops of variable directions, that represent a part of the artery that curls out of the pancreatic tissue, were identified in each age-gender category and were present in nearly all subjects (86%). Conclusion This study suggests that although some anatomic features of the splenic artery are subject to factors as age and gender, the tortuosity of the splenic artery is not age dependent. Most subjects had one or multiple loops, which can serve as a target for neuromodulatory devices. Future studies should investigate whether splenic nerve stimulation is safe and feasible.

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 Chest Pain of Uncertain Aetiology: Role of Contrast Enhanced Computed Tomography in the Emergency Department

2016 ◽  
Vol 10 (1) ◽  
pp. 205-211
Author(s):  
Firas Yassin ◽  
Chris Sawh ◽  
Pankaj Garg
Keyword(s):  
Emergency Department ◽  
Chest Pain ◽  
Acute Chest Pain ◽  
Coronary Event ◽  
Computed Tomographic ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Enhanced Computed Tomography

There is increasing role of computed tomographic (CT) in the assessment of acute chest pain in the emergency department especially when the diagnosis is not clear. We report a case where non ECG gated contrast enhanced CT in the emergency department for rule-out of pulmonary embolus guided to the actual diagnosis, which was, acute coronary event, as evidenced by the presence of perfusion defect.

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.

Horseshoe Kidney Blunt Trauma With Double Laceration: Endovascular Management

2020 ◽  
Vol 54 (7) ◽  
pp. 643-645
Author(s):  
Enrico Boninsegna ◽  
Emilio Simonini ◽  
Stefano Crosara ◽  
Carlo Sozzi ◽  
Stefano Colopi
Keyword(s):  
Abdominal Trauma ◽  
Horseshoe Kidney ◽  
Left Common Iliac Artery ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Arterial Hemorrhage ◽  
Endovascular Approach ◽  
Perinephric Hematoma ◽  
Enhanced Computed Tomography

A 78-year-old male patient was admitted to our hospital after abdominal trauma. Contrast-enhanced computed tomography (CT) scan demonstrated a horseshoe kidney with a perinephric hematoma and evidence of arterial hemorrhage. An anomalous renal arterial anatomy was noted as well, with a renal artery originating from the left common iliac artery. He was successfully treated via an endovascular approach. Varying forms of vascularization may complicate angiographic treatment of patients with abdominal trauma in a setting of kidney anomalies. Obtaining and evaluating contrast-enhanced CT angiography can identify anomalous vessels and can be invaluable when deciding on the most appropriate interventional approach.

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