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A systematic review of radiomics in pancreatitis: applying the evidence level rating tool for promoting clinical transferability. Insights Imaging 2022; 13:139. [PMID: 35986798 PMCID: PMC9391628 DOI: 10.1186/s13244-022-01279-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/26/2022] [Indexed: 12/16/2022] Open
Abstract
Background Multiple tools have been applied to radiomics evaluation, while evidence rating tools for this field are still lacking. This study aims to assess the quality of pancreatitis radiomics research and test the feasibility of the evidence level rating tool. Results Thirty studies were included after a systematic search of pancreatitis radiomics studies until February 28, 2022, via five databases. Twenty-four studies employed radiomics for diagnostic purposes. The mean ± standard deviation of the adherence rate was 38.3 ± 13.3%, 61.3 ± 11.9%, and 37.1 ± 27.2% for the Radiomics Quality Score (RQS), the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist, and the Image Biomarker Standardization Initiative (IBSI) guideline for preprocessing steps, respectively. The median (range) of RQS was 7.0 (− 3.0 to 18.0). The risk of bias and application concerns were mainly related to the index test according to the modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The meta-analysis on differential diagnosis of autoimmune pancreatitis versus pancreatic cancer by CT and mass-forming pancreatitis versus pancreatic cancer by MRI showed diagnostic odds ratios (95% confidence intervals) of, respectively, 189.63 (79.65–451.48) and 135.70 (36.17–509.13), both rated as weak evidence mainly due to the insufficient sample size. Conclusions More research on prognosis of acute pancreatitis is encouraged. The current pancreatitis radiomics studies have insufficient quality and share common scientific disadvantages. The evidence level rating is feasible and necessary for bringing the field of radiomics from preclinical research area to clinical stage. Supplementary Information The online version contains supplementary material available at 10.1186/s13244-022-01279-4.
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Yan G, Yan G, Li H, Liang H, Peng C, Bhetuwal A, McClure MA, Li Y, Yang G, Li Y, Zhao L, Fan X. Radiomics and Its Applications and Progress in Pancreatitis: A Current State of the Art Review. Front Med (Lausanne) 2022; 9:922299. [PMID: 35814756 PMCID: PMC9259974 DOI: 10.3389/fmed.2022.922299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 05/31/2022] [Indexed: 11/25/2022] Open
Abstract
Radiomics involves high-throughput extraction and analysis of quantitative information from medical images. Since it was proposed in 2012, there are some publications on the application of radiomics for (1) predicting recurrent acute pancreatitis (RAP), clinical severity of acute pancreatitis (AP), and extrapancreatic necrosis in AP; (2) differentiating mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC), focal autoimmune pancreatitis (AIP) from PDAC, and functional abdominal pain (functional gastrointestinal diseases) from RAP and chronic pancreatitis (CP); and (3) identifying CP and normal pancreas, and CP risk factors and complications. In this review, we aim to systematically summarize the applications and progress of radiomics in pancreatitis and it associated situations, so as to provide reference for related research.
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Affiliation(s)
- Gaowu Yan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Gaowen Yan
- Department of Radiology, The First Hospital of Suining, Suining, China
| | - Hongwei Li
- Department of Radiology, The Third Hospital of Mianyang and Sichuan Mental Health Center, Mianyang, China
| | - Hongwei Liang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chen Peng
- Department of Gastroenterology, The First Hospital of Suining, Suining, China
| | - Anup Bhetuwal
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Morgan A. McClure
- Department of Radiology and Imaging, Institute of Rehabilitation and Development of Brain Function, The Second Clinical Medical College of North Sichuan Medical College, Nanchong Central Hospital, Nanchong, China
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Yongmei Li
| | - Guoqing Yang
- Department of Radiology, Suining Central Hospital, Suining, China
- Guoqing Yang
| | - Yong Li
- Department of Radiology, Suining Central Hospital, Suining, China
- Yong Li
| | - Linwei Zhao
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Xiaoping Fan
- Department of Radiology, Suining Central Hospital, Suining, China
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Luo C, Song Y, Liu Y, Wang R, Gao J, Yue S, Ding C. Analysis of the value of enhanced CT combined with texture analysis in the differential diagnosis of pulmonary sclerosing pneumocytoma and atypical peripheral lung cancer: a feasibility study. BMC Med Imaging 2022; 22:16. [PMID: 35105314 PMCID: PMC8808962 DOI: 10.1186/s12880-022-00745-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 01/27/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND As a rare benign lung tumour, pulmonary sclerosing pneumocytoma (PSP) is often misdiagnosed as atypical peripheral lung cancer (APLC) on routine imaging examinations. This study explored the value of enhanced CT combined with texture analysis to differentiate between PSP and APLC. METHODS Forty-eight patients with PSP and fifty patients with APLC were retrospectively enrolled. The CT image features of the two groups of lesions were analysed, and MaZda software was used to evaluate the texture of CT venous phase thin-layer images. Independent sample t-test, Mann-Whitney U tests or χ2 tests were used to compare between groups. The intra-class correlation coefficient (ICC) was used to analyse the consistency of the selected texture parameters. Spearman correlation analysis was used to evaluate the differences in texture parameters between the two groups. Based on the statistically significant CT image features and CT texture parameters, the independent influencing factors between PSP and APLC were analysed by multivariate logistic regression. Extremely randomized trees (ERT) was used as the classifier to build models, and the models were evaluated by the five-fold cross-validation method. RESULTS Logistic regression analysis based on CT image features showed that calcification and arterial phase CT values were independent factors for distinguishing PSP from APLC. The results of logistic regression analysis based on CT texture parameters showed that WavEnHL_s-1 and Perc.01% were independent influencing factors to distinguish the two. Compared with the single-factor model (models A and B), the classification accuracy of the model based on image features combined with texture parameters was 0.84 ± 0.04, the AUC was 0.84 ± 0.03, and the sensitivity and specificity were 0.82 ± 0.13 and 0.87 ± 0.12, respectively. CONCLUSION Enhanced CT combined with texture analysis showed good diagnostic value for distinguishing PSP and APLC, which may contribute to clinical decision-making and prognosis evaluation.
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Affiliation(s)
- Chenglong Luo
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China
| | - Yiman Song
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China
| | - Yiyang Liu
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China
| | - Rui Wang
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China
| | - Jianbo Gao
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China
| | - Songwei Yue
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China
| | - Changmao Ding
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, China.
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Ma X, Wang YR, Zhuo LY, Yin XP, Ren JL, Li CY, Xing LH, Zheng TT. Retrospective Analysis of the Value of Enhanced CT Radiomics Analysis in the Differential Diagnosis Between Pancreatic Cancer and Chronic Pancreatitis. Int J Gen Med 2022; 15:233-241. [PMID: 35023961 PMCID: PMC8747707 DOI: 10.2147/ijgm.s337455] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 12/13/2021] [Indexed: 12/12/2022] Open
Abstract
Purpose To investigate the feasibility of enhanced computed tomography (CT) radiomics analysis to differentiate between pancreatic cancer (PC) and chronic pancreatitis. Methods and materials The CT images of 151 PCs and 24 chronic pancreatitis were retrospectively analyzed in the three-dimensional regions of interest on arterial phase (AP) and venous phase (VP) and segmented by MITK software. A multivariable logistic regression model was established based on the selected radiomics features. The radiomics score was calculated, and the nomogram was established. The discrimination of each model was analyzed by the receiver operating characteristic curve (ROC). Decision curve analysis (DCA) was used to evaluate clinical utility. The precision recall curve (PRC) was used to evaluate whether the model is affected by data imbalance. The Delong test was adopted to compare the diagnostic efficiency of each model. Results Significant differences were observed in the distribution of gender (P = 0.034), carbohydrate antigen 19-9 (P < 0.001), and carcinoembryonic antigen (P < 0.001) in patients with PC and chronic pancreatitis. The area under the ROC curve (AUC) value of AP multivariate regression model, VP multivariate regression model, AP combined with VP features model (Radiomics), clinical feature model, and radiomics combined with clinical feature model (COMB) was 0.905, 0.941, 0.941, 0.822, and 0.980, respectively. The sensitivity and specificity of the COMB model were 0.947 and 0.917, respectively. The results of DCA showed that the COMB model exhibited net clinical benefits and PRC shows that COMB model have good precision and recall (sensitivity). Conclusion The COMB model could be a potential tool to distinguish PC from chronic pancreatitis and aid in clinical decisions.
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Affiliation(s)
- Xi Ma
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Yu-Rui Wang
- Department of Computed Tomography, Tangshan Gongren Hospital, Tangshan, Hebei Province, 063000, People's Republic of China
| | - Li-Yong Zhuo
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Xiao-Ping Yin
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Jia-Liang Ren
- GE Healthcare[Shanghai] Co Ltd, Shanghai, 210000, People's Republic of China
| | - Cai-Ying Li
- Department of Radiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, 050000, People's Republic of China
| | - Li-Hong Xing
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Tong-Tong Zheng
- Department of Radiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, 050000, People's Republic of China
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Tang X, Yang Y, Huang L, Qiu L. The Application of Texture Feature Analysis of Rectus Femoris Based on Local Binary Pattern (LBP) Combined With Gray-Level Co-Occurrence Matrix (GLCM) in Sarcopenia. JOURNAL OF ULTRASOUND IN MEDICINE 2021; 41:2169-2179. [PMID: 34825723 DOI: 10.1002/jum.15896] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 11/01/2021] [Accepted: 11/11/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES In order to detect the changes in muscle texture of sarcopenia and to explore a new method of ultrasound assessment of muscle changes in sarcopenia. METHODS we used the local binary pattern (LBP) combined with gray-level co-occurrence matrix (GLCM) method to extract and quantitatively analyze the texture information of the rectus femoris of different people, and initially verified the robustness of this method to image gain changes. We recruited young volunteers, elderly volunteers without sarcopenia, and elderly volunteers with sarcopenia in this cross-sectional study. We scanned the rectus femoris and extracted their muscle texture features. RESULTS We found that when ultrasonographic gain varied from 40% to 70%, the intraclass correlation coefficient (ICC) of contrast, entropy, and homogeneity were 0.989, 0.973, and 0.989, respectively. Body mass index was significantly related to contrast (r = 0.285, P < .05), and age had a significant correlation with contrast and homogeneity (r = -0.259 and r = 0.269, P < .05). The elderly volunteers with sarcopenia had the highest entropy (0.363 [0.342-0.403]) and homogeneity (2.203 [2.162-2.277]) in the texture of the rectus femoris among the three groups, and at the same time had the lowest contrast (44.583 [43.492-47.399]), and all P < .05. CONCLUSION LBP combined with GLCM can be a stable method for extracting muscle texture features. At the same time, the contrast, entropy, and homogeneity of the rectus femoris of the elderly with sarcopenia were significantly different from those of the young volunteers and the elderly without sarcopenia, suggesting the texture features of rectus femoris are potential parameters for evaluating muscle function and pathological changes.
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Affiliation(s)
- Xinyi Tang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China
| | - Yujia Yang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China
| | - Li Huang
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Li Qiu
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China
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