Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images
BackgroundIn this work, radiomics characteristics based on CT scans were used to build a model for preoperative evaluation of CD3 and CD8 T cells expression levels in patients with non-small cell lung cancer (NSCLC).MethodsTwo radiomics models for evaluating tumor-infiltrating CD3 and CD8 T cells we...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1104316/full |
| _version_ | 1811165321984212992 |
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| author | Lujiao Chen Lulin Chen Hongxia Ni Liyijing Shen Jianguo Wei Yang Xia Jianfeng Yang Minxia Yang Zhenhua Zhao |
| author_facet | Lujiao Chen Lulin Chen Hongxia Ni Liyijing Shen Jianguo Wei Yang Xia Jianfeng Yang Minxia Yang Zhenhua Zhao |
| author_sort | Lujiao Chen |
| collection | DOAJ |
| description | BackgroundIn this work, radiomics characteristics based on CT scans were used to build a model for preoperative evaluation of CD3 and CD8 T cells expression levels in patients with non-small cell lung cancer (NSCLC).MethodsTwo radiomics models for evaluating tumor-infiltrating CD3 and CD8 T cells were created and validated using computed tomography (CT) images and pathology information from NSCLC patients. From January 2020 to December 2021, 105 NSCLC patients with surgical and histological confirmation underwent this retrospective analysis. Immunohistochemistry (IHC) was used to determine CD3 and CD8 T cells expression, and all patients were classified into groups with high and low CD3 T cells expression and high and low CD8 T cells expression. The CT area of interest had 1316 radiomic characteristics that were retrieved. The minimal absolute shrinkage and selection operator (Lasso) technique was used to choose components from the IHC data, and two radiomics models based on CD3 and CD8 T cells abundance were created. Receiver operating characteristic (ROC), calibration curve, and decision curve analyses were used to examine the models’ ability to discriminate and their clinical relevance (DCA).ResultsA CD3 T cells radiomics model with 10 radiological characteristics and a CD8 T cells radiomics model with 6 radiological features that we created both demonstrated strong discrimination in the training and validation cohorts. The CD3 radiomics model has an area under the curve (AUC) of 0.943 (95% CI 0.886-1), sensitivities, specificities, and accuracy of 96%, 89%, and 93%, respectively, in the validation cohort. The AUC of the CD8 radiomics model was 0.837 (95% CI 0.745-0.930) in the validation cohort, with sensitivity, specificity, and accuracy values of 70%, 93%, and 80%, respectively. Patients with high levels of CD3 and CD8 expression had better radiographic results than patients with low levels of expression in both cohorts (p<0.05). Both radiomic models were therapeutically useful, as demonstrated by DCA.ConclusionsWhen making judgments on therapeutic immunotherapy, CT-based radiomic models can be utilized as a non-invasive way to evaluate the expression of tumor-infiltrating CD3 and CD8 T cells in NSCLC patients. |
| first_indexed | 2024-04-10T15:35:20Z |
| format | Article |
| id | doaj.art-2da27f79ef2d46ae9d6a4bf30f6723fe |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-10T15:35:20Z |
| publishDate | 2023-02-01 |
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| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-2da27f79ef2d46ae9d6a4bf30f6723fe2023-02-13T05:59:12ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-02-011310.3389/fonc.2023.11043161104316Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT imagesLujiao Chen0Lulin Chen1Hongxia Ni2Liyijing Shen3Jianguo Wei4Yang Xia5Jianfeng Yang6Minxia Yang7Zhenhua Zhao8Department of Radiology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaDepartment of Ultrasound, Affiliated hospital of Shaoxing University, Shaoxing, Zhejiang, ChinaDepartment of Radiology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaDepartment of Radiology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaDepartment of Pathology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaDepartment of Radiology, Shaoxing Maternal and Child Health Hospital, Shaoxing, Zhejiang, ChinaDepartment of Radiology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaDepartment of Radiology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaDepartment of Radiology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, ChinaBackgroundIn this work, radiomics characteristics based on CT scans were used to build a model for preoperative evaluation of CD3 and CD8 T cells expression levels in patients with non-small cell lung cancer (NSCLC).MethodsTwo radiomics models for evaluating tumor-infiltrating CD3 and CD8 T cells were created and validated using computed tomography (CT) images and pathology information from NSCLC patients. From January 2020 to December 2021, 105 NSCLC patients with surgical and histological confirmation underwent this retrospective analysis. Immunohistochemistry (IHC) was used to determine CD3 and CD8 T cells expression, and all patients were classified into groups with high and low CD3 T cells expression and high and low CD8 T cells expression. The CT area of interest had 1316 radiomic characteristics that were retrieved. The minimal absolute shrinkage and selection operator (Lasso) technique was used to choose components from the IHC data, and two radiomics models based on CD3 and CD8 T cells abundance were created. Receiver operating characteristic (ROC), calibration curve, and decision curve analyses were used to examine the models’ ability to discriminate and their clinical relevance (DCA).ResultsA CD3 T cells radiomics model with 10 radiological characteristics and a CD8 T cells radiomics model with 6 radiological features that we created both demonstrated strong discrimination in the training and validation cohorts. The CD3 radiomics model has an area under the curve (AUC) of 0.943 (95% CI 0.886-1), sensitivities, specificities, and accuracy of 96%, 89%, and 93%, respectively, in the validation cohort. The AUC of the CD8 radiomics model was 0.837 (95% CI 0.745-0.930) in the validation cohort, with sensitivity, specificity, and accuracy values of 70%, 93%, and 80%, respectively. Patients with high levels of CD3 and CD8 expression had better radiographic results than patients with low levels of expression in both cohorts (p<0.05). Both radiomic models were therapeutically useful, as demonstrated by DCA.ConclusionsWhen making judgments on therapeutic immunotherapy, CT-based radiomic models can be utilized as a non-invasive way to evaluate the expression of tumor-infiltrating CD3 and CD8 T cells in NSCLC patients.https://www.frontiersin.org/articles/10.3389/fonc.2023.1104316/fullnon-small-cell lung cancerradiomicsmodelCD3CD8 |
| spellingShingle | Lujiao Chen Lulin Chen Hongxia Ni Liyijing Shen Jianguo Wei Yang Xia Jianfeng Yang Minxia Yang Zhenhua Zhao Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images Frontiers in Oncology non-small-cell lung cancer radiomics model CD3 CD8 |
| title | Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images |
| title_full | Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images |
| title_fullStr | Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images |
| title_full_unstemmed | Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images |
| title_short | Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images |
| title_sort | prediction of cd3 t cells and cd8 t cells expression levels in non small cell lung cancer based on radiomic features of ct images |
| topic | non-small-cell lung cancer radiomics model CD3 CD8 |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1104316/full |
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