Evidence map›Paper›PMID 39034308›Full record

ArticleAbdominal radiology (New York)2024

Baseline hepatobiliary MRI for predicting chemotherapeutic response and prognosis in initially unresectable colorectal cancer liver metastases.

Yazheng Chen, Tao Lu, Yongchang Zhang, Hang Li, Jingxu Xu, Mou Li

Abstract readMulticenter Study
In one paragraph

Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

6 authors.

Yazheng Chen *Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, Sichuan, China.
Tao Lu *Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, Sichuan, China.
Yongchang ZhangDepartment of Radiology, Chengdu Seventh People's Hospital, Chengdu, 610213, Sichuan, China.
Hang LiDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, Sichuan, China.
Jingxu XuDepartment of Research Collaboration, R&D Center, Hangzhou Deepwise & League of PHD Technology Co., Ltd, Hangzhou, China.
Mou LiDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, Sichuan, China. 1403611035@qq.com.

Funding

Foundation of Sichuan Provincial People's Hospital 2022QN59the Natural Science Foundation of Sichuan Province from Science & Technology Department of Sichuan Province 2023NSFSC1718
6 · The paper itself

Abstract

purposeTo evaluate the performance of hepatobiliary MRI parameters as predictors of clinical response to chemotherapy in patients with initially unresectable colorectal cancer liver metastases (CRLM).

methodsEighty-five patients with initially unresectable CRLM were retrospectively enrolled from two hospitals and scanned using gadobenate dimeglumine-enhanced MRI before treatment. Therapy response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Conventional parameters (i.e., signal intensity [SI]) and radiomics features of portal venous phase (PVP) and hepatobiliary phase (HBP) images were analyzed between the responders and non-responders. Next, the combined model was constructed, and the area under the receiver operating characteristic (ROC) curve (AUC) was calculated. The relationship between the combined model and progression-free survival (PFS) was analyzed using Cox regression.

resultsOf the 85 patients from two hospitals, 42 were in the response group, and 43 were in the non-response group. Upon conducting five-fold cross-validation, the normalized relative enhancement (NRE) of CRLM during the PVP yielded an AUC of 0.625. Additionally, a radiomics feature derived from the tumor area in the HBP achieved an AUC of 0.698, while a separate feature extracted from the peritumoral region in the HBP recorded an AUC of 0.709. The model that integrated these three features outperformed the individual features, achieving an AUC of 0.818. Furthermore, the combined model exhibited a significant correlation with PFS (P < 0.001).

conclusionThe combined model, based on baseline hepatobiliary MRI, aids in predicting chemotherapeutic response and PFS in patients with initially unresectable CRLM.

Indexed as

Colorectal NeoplasmsContrast MediaLiver NeoplasmsMagnetic Resonance ImagingOrganometallic CompoundsAdultAgedAged, 80 and overFemaleHumansMaleMeglumineMiddle AgedPredictive Value of TestsPrognosisResponse Evaluation Criteria in Solid TumorsContrast Mediagadobenic acidMeglumineOrganometallic CompoundsCRLMHepatobiliary MRIPrognosisRadiomics

Identifiers

PMID39034308
PMCPMC11300495

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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.