Evidence map›Paper›PMID 37840098›Full record

ArticleInsights into imaging2023

A CT-based radiomics approach to predict intra-tumoral tertiary lymphoid structures and recurrence of intrahepatic cholangiocarcinoma.

Ying Xu, Zhuo Li, Yi Yang, Lu Li, Yanzhao Zhou, Jingzhong Ouyang, Zhen Huang, Sicong Wang, Lizhi Xie, Feng Ye and 4 more

Abstract read
In one paragraph

Article in Insights into imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Ying Xu *Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Zhuo Li *Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yi Yang *Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Lu LiDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yanzhao ZhouDepartment of Hepatobiliary and Pancreatic Surgery, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Jingzhong OuyangDepartment of Hepatobiliary and Pancreatic Surgery, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Zhen HuangDepartment of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Sicong WangMagnetic Resonance Imaging Research, General Electric Healthcare, Beijing, China.
Lizhi XieMagnetic Resonance Imaging Research, General Electric Healthcare, Beijing, China.
Feng YeDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. dr_fengye_ncc@163.com.
Jinxue ZhouDepartment of Hepatobiliary and Pancreatic Surgery, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China. zhoujx888@126.com.
Jianming YingDepartment of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. jmying@cicams.ac.cn.
Hong ZhaoDepartment of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. zhaohong@cicams.ac.cn.
Xinming ZhaoDepartment of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. zhaoxinming@cicams.ac.cn.

Funding

CAMS Innovation Fund for Medical Sciences (CIFMS) 2022-I2M-C&T-B-081National Key Research and Development Program of China 2020AAA0109503National Natural Science Foundation of China 81972311National Natural Science Foundation of China 82141127Special Research Fund for Central Universities, Peking Union Medical College 3332022026
6 · The paper itself

Abstract

purposeTo predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative CT radiomics. PATIENTS AND

methodsA total of 116 ICC patients were included (training: 86; external validation: 30). The enhanced CT images were performed for the radiomics model. The logistic regression analysis was applied for the clinical model. The combined model was based on the clinical and radiomics models.

resultsA total of 107 radiomics features were extracted, and after being eliminated and selected, six features were combined to establish a radiomics model for TLSs prediction. Arterial phase diffuse hyperenhancement and AJCC 8th stage were combined to construct a clinical model. The combined (radiomics nomogram) model outperformed both the independent radiomics model and clinical model in the training cohort (AUC, 0.85 vs. 0.82 and 0.75, respectively) and was validated in the external validation cohort (AUC, 0.88 vs. 0.86 and 0.71, respectively). Patients in the rad-score no less than -0.76 (low-risk) group showed significantly better RFS than those in the less than -0.76 (high-risk) group (p < 0.001, C-index = 0.678). Patients in the nomogram score no less than -1.16 (low-risk) group showed significantly better RFS than those of the less than -1.16 (high-risk) group (p < 0.001, C-index = 0.723).

conclusionsCT radiomics nomogram could serve as a preoperative biomarker of intra-tumoral TLSs status, better than independent radiomics or clinical models; preoperative CT radiomics nomogram achieved accurate stratification for RFS of ICC patients, better than the postoperative pathologic TLSs status. CRITICAL RELEVANCE STATEMENT: The radiomics nomogram showed better performance in predicting TLSs than independent radiomics or clinical models and better prognosis stratification than postoperative pathologic TLSs status in ICC patients, which may facilitate identifying patients benefiting most from surgery and subsequent immunotherapy. KEY POINTS: • The combined (radiomics nomogram) model consisted of the radiomics model and clinical model (arterial phase diffuse hyperenhancement and AJCC 8th stage). • The radiomics nomogram showed better performance in predicting TLSs than independent radiomics or clinical models in ICC patients. • Preoperative CT radiomics nomogram achieved more accurate stratification for RFS of ICC patients than the postoperative pathologic TLSs status.

Indexed as

CTIntrahepatic cholangiocarcinomaRadiomicsRecurrenceTertiary lymphoid structures

Identifiers

PMID37840098
PMCPMC10577112

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.