Qualitative and quantitative image analysis of 16 cm wide-coverage computed tomography compared to new-generation dual-source CT

2020 ◽  
Vol 28 (3) ◽  
pp. 527-539
Author(s):  
Liang Jin ◽  
Yiyi Gao ◽  
Yuqing Shan ◽  
Yingli Sun ◽  
Ming Li ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Quantitative Image Analysis ◽  
Dual Source Ct ◽  
Qualitative And Quantitative ◽  
Quantitative Image ◽  
Dual Source ◽  
New Generation

The qualitative and quantitative image analysis of MR imaging in patients with acute-on-chronic liver failure

2018 ◽  
Vol 47 ◽  
pp. 18-24
Author(s):  
Tae Wook Kang ◽  
Mimi Kim ◽  
Young Kon Kim ◽  
Seong Hyun Kim ◽  
Dong Hyun Sinn ◽  
...  
Keyword(s):  
Image Analysis ◽  
Mr Imaging ◽  
Liver Failure ◽  
Quantitative Image Analysis ◽  
Chronic Liver ◽  
Chronic Liver Failure ◽  
Qualitative And Quantitative ◽  
Quantitative Image

scholarly journals Comparison of quantitative and qualitative scoring approaches for radiation-induced pulmonary fibrosis as applied to a preliminary investigation into the efficacy of mesenchymal stem cell delivery methods in a rat model

BJR|Open ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 20210006
Author(s):  
Li Ming Wang ◽  
Sungmi Jung ◽  
Monica Serban ◽  
Avishek Chatterjee ◽  
Sangkyu Lee ◽  
...  
Keyword(s):  
Image Analysis ◽  
Stem Cell ◽  
Mesenchymal Stem Cell ◽  
Pulmonary Fibrosis ◽  
Quantitative Image Analysis ◽  
Qualitative And Quantitative ◽  
Gm Csf ◽  
Quantitative Image ◽  
Radiation Induced ◽  
Quantitative Scoring

Objectives: Compare a quantitative, algorithm-driven, and qualitative, pathologist-driven, scoring of radiation-induced pulmonary fibrosis (RIPF). And using these scoring models to derive preliminary comparisons on the effects of different mesenchymal stem cell (MSC) administration modalities in reducing RIPF. Methods 25 rats were randomized into 5 groups: non-irradiated control (CG), irradiated control (CR), intraperitoneally administered granulocyte-macrophage colony stimulating factor or GM-CSF (Drug), intravascularly administered MSC (IV), and intratracheally administered MSC (IT). All groups, except CG, received an 18 Gy conformal dose to the right lung. Drug, IV and IT groups were treated immediately after irradiation. After 24 weeks of observation, rats were euthanized, their lungs excised, fixed and stained with Masson’s Trichrome. Samples were anonymized and RIPF was scored qualitatively by a certified pathologist and quantitatively using ImageScope. An analysis of association was conducted, and two binary classifiers trained to validate the integrity of both qualitative and quantitative scoring. Differences between the treatment groups, as assessed by the pathologist score, were then tested by variance component analysis and mixed models for differences in RIPF outcomes. Results: There is agreement between qualitative and quantitative scoring for RIPF grades from 4 to 7. Both classifiers performed similarly on the testing set (AUC = 0.923) indicating accordance between the qualitative and quantitative scoring. For comparisons between MSC infusion modalities, the Drug group had better outcomes (mean pathologist scoring of 3.96), correlating with significantly better RIPF outcomes than IV [lower by 0.97, p = 0.047, 95% CI = (0.013, 1.918)] and resulting in an improvement over CR [lower by 0.93, p = 0.037, 95% CI = (0.062, 1.800]. Conclusion: Quantitative image analysis may help in the assessment of therapeutic interventions for RIPF and can serve as a scoring surrogate in differentiating between severe and mild cases of RIPF. Preliminary data demonstrate that the use of GM-CSF was best correlated with lower RIPF severity. Advances in knowledge Quantitative image analysis can be a viable supplemental system of quality control and triaging in situations where pathologist work hours or resources are limited. The use of different MSC administration methods can result in different degrees of MSC efficacy and study outcomes.

Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade

2021 ◽  
pp. 679-694
Author(s):  
Alessandra Pulvirenti ◽  
Rikiya Yamashita ◽  
Jayasree Chakraborty ◽  
Natally Horvat ◽  
Kenneth Seier ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Ct Scan ◽  
Predictive Value ◽  
Quantitative Computed Tomography ◽  
Tumor Grade ◽  
Quantitative Image Analysis ◽  
Arterial Phase ◽  
Imaging Method ◽  
Quantitative Image

PURPOSE The therapeutic management of pancreatic neuroendocrine tumors (PanNETs) is based on pathological tumor grade assessment. A noninvasive imaging method to grade tumors would facilitate treatment selection. This study evaluated the ability of quantitative image analysis derived from computed tomography (CT) images to predict PanNET grade. METHODS Institutional database was queried for resected PanNET (2000-2017) with a preoperative arterial phase CT scan. Radiomic features were extracted from the primary tumor on the CT scan using quantitative image analysis, and qualitative radiographic descriptors were assessed by two radiologists. Significant features were identified by univariable analysis and used to build multivariable models to predict PanNET grade. RESULTS Overall, 150 patients were included. The performance of models based on qualitative radiographic descriptors varied between the two radiologists (reader 1: sensitivity, 33%; specificity, 66%; negative predictive value [NPV], 63%; and positive predictive value [PPV], 37%; reader 2: sensitivity, 45%; specificity, 70%; NPV, 72%; and PPV, 47%). The model based on radiomics had a better performance predicting the tumor grade with a sensitivity of 54%, a specificity of 80%, an NPV of 81%, and a PPV of 54%. The inclusion of radiomics in the radiographic descriptor models improved both the radiologists' performance. CONCLUSION CT quantitative image analysis of PanNETs helps predict tumor grade from routinely acquired scans and should be investigated in future prospective studies.

scholarly journals Quantitative image analysis for the detection of motion artefacts in coronary artery computed tomography

2009 ◽  
Vol 26 (1) ◽  
pp. 77-87 ◽  
Author(s):  
Wisnumurti Kristanto ◽  
Peter M. van Ooijen ◽  
Riksta Dikkers ◽  
Marcel J. Greuter ◽  
Felix Zijlstra ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Coronary Artery ◽  
Quantitative Image Analysis ◽  
Motion Artefacts ◽  
Quantitative Image
Sign in / Sign up

Export Citation Format

Share Document