Predicting survival for hepatic arterial infusion chemotherapy of unresectable colorectal liver metastases: Radiomics analysis of pretreatment computed tomography

Liu, Peng; Zhu, Hai‐Tao; Zhu, Honglin; Zhang, Xiaoyan; Feng, Aiwei; Zhu, Xu; Sun, Ying‐Shi

doi:10.2478/jtim-2022-0004

Cited by 22 publications

(11 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Imaging, including EUS, CT and MRI, which can provide a convenient and noninvasive diagnosis, remains the first-line diagnostic modality for pancreatic cancer and is used to evaluate therapeutic efficacy in many organs[ 25 - 28 ]. However, cross-sectional imaging is limited in the visualization of small and metastatic tumors, which can frequently result in underestimation of the pancreatic cancer stage[ 29 ].…”

Section: Discussionmentioning

confidence: 99%

Circulating tumor cells as potential prognostic biomarkers for early-stage pancreatic cancer: A systematic review and meta-analysis

Zhang,

Bao,

Zhao

et al. 2023

World J Clin Oncol

View full text Add to dashboard Cite

BACKGROUND Pancreatic cancer is difficult to be diagnosed early clinically, while often leads to poor prognosis. If optimal personalized treatment plan can be provided to pancreatic cancer patient at an earlier stage, this can greatly improve overall survival (OS). Circulating tumor cells (CTCs) are a collective term for various types of tumor cells present in the peripheral blood (PB), which are formed by detachment during the development of solid tumor lesions. Most CTCs undergo apoptosis or are phagocytosed after entering the PB, whereas a few can escape and anchor at distal sites to develop metastasis, increasing the risk of death for patients with malignant tumors. AIM To investigate the significance of CTCs in predicting the prognosis of early pancreatic cancer patients. METHODS The PubMed, EMBASE, Web of Science, Cochrane Library, China National Knowledge Infrastructure, China Biology Medicine, and ChinaInfo databases were searched for articles published through December 2022. Studies were considered qualified if they included patients with early pancreatic cancer, analyzed the prognostic value of CTCs, and were full papers reported in English or Chinese. Researches were selected and assessed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol and the Newcastle-Ottawa Scale criteria. We used a funnel plot to assess publication bias. RESULTS From 1595 publications, we identified eight eligible studies that collectively enrolled 355 patients with pancreatic cancer. Among these original studies, two were carried out in China; three in the United States; and one each in Italy, Spain, and Norway. All eight studies analyzed the relevance between CTCs and the prognosis of patients with early-stage pancreatic cancer after surgery. A meta-analysis showed that the patients that were positive pre-treatment or post-treatment for CTCs were associated with decreased OS [hazard ratio (HR) = 1.93, 95% confidence interval (CI): 1.197-3.126, P = 0.007] and decreased relapse-free/disease-free/progression-free survival (HR = 1.27, 95%CI: 1.137-1.419, P < 0.001) in early-stage pancreatic cancer. Additionally, the results suggest no statistically noticeable publication bias for overall, disease-free, progression-free, and recurrence-free survival. CONCLUSION This pooled meta-analysis shows that CTCs, as biomarkers, can afford reliable prognostic information for patients with early-stage pancreatic cancer and help develop individualized treatment plans.

show abstract

Section: Discussionmentioning

confidence: 99%

Circulating tumor cells as potential prognostic biomarkers for early-stage pancreatic cancer: A systematic review and meta-analysis

Zhang,

Bao,

Zhao

et al. 2023

World J Clin Oncol

View full text Add to dashboard Cite

show abstract

“…Compared to single biomarkers, multiple biomarkers might considerably increase the prediction strength of predictive models. A nomogram, a statistical modelling method that comprehensively incorporates the impact of diverse clinical variables, 29 has been used for the prediction of low muscle mass or sarcopenia in patients with cirrhosis 30 and gastric cancer. 31 However, there is currently no nomogram for predicting sarcopenia in COPD patients.…”

Section: Discussionmentioning

confidence: 99%

Ultrasound Assessment of the Rectus Femoris in Patients with Chronic Obstructive Pulmonary Disease Predicts Sarcopenia

Deng¹,

Yan²,

Tong³

et al. 2022

COPD

View full text Add to dashboard Cite

Purpose Sarcopenia, an age-related loss of skeletal muscle mass and function, is frequent in patients with chronic obstructive pulmonary disease (COPD) and is linked to a poor prognosis. The diagnosis of sarcopenia requires specific equipment and is inconvenient to introduce into clinical practice. Ultrasound is an innovative method to assess muscle quantity. The objective of this research was to evaluate the use of ultrasound for prospectively screening for sarcopenia in COPD patients. Patients and Methods A total of 235 stable patients with COPD were included in this observational study and divided into development and validation sets. The Asian Working Group for Sarcopenia standards were used to define sarcopenia. The thickness (RF thick ) and cross-sectional area (RF csa ) of the rectus femoris were measured using ultrasound. Receiver operating characteristic curve analysis of RF thick and RF csa was used to predict sarcopenia. Nomogram models were constructed based on RF thick , RF csa , age and body mass index to identify sarcopenia. Results Sarcopenia was present in 83 (35.32%) patients. Patients with sarcopenia had advanced age, decreased pulmonary function, decreased physical function and poor clinical outcomes. RF thick and RF csa showed good predictive ability for sarcopenia in the development and validation sets. The nomogram based on RF thick and RF csa could detect sarcopenia in COPD patients, and all had significant predictive performance in the development and validation sets. The calibration plot showed good agreement between the nomogram predictions and actual observations. Conclusion The ultrasound measurement of the rectus femoris has potential for the clinical assessment of sarcopenia in patients with COPD.

show abstract

“…Jain et al predicted the overall survival (OS) and response to chemotherapy of small cell lung cancer (SCLC) patients based on the radiomic features within and around lung tumors extracted from CT images (18). In predicting the efficacy and prognosis of CRLM after treatment, Wei et al constructed a deep learning-based radiomics model using CT images to predict the response of CRLM to advanced first-line chemotherapy, with an AUC of 0.935 in the validation cohort (19); Liu et al constructed a CT-based radiomics model to predict the survival of unresectable colorectal liver metastases treated with hepatic arterial infusion chemotherapy, and the c-index of the test group reached 0.743 (20).…”

Section: Introductionmentioning

confidence: 99%

“…constructed a deep learning-based radiomics model using CT images to predict the response of CRLM to advanced first-line chemotherapy, with an AUC of 0.935 in the validation cohort ( 19 ); Liu et al. constructed a CT-based radiomics model to predict the survival of unresectable colorectal liver metastases treated with hepatic arterial infusion chemotherapy, and the c-index of the test group reached 0.743 ( 20 ).…”

Section: Introductionmentioning

confidence: 99%

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases

Zhai

Zhang

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

Background and objectiveFor patients with advanced colorectal liver metastases (CRLMs) receiving first-line anti-angiogenic therapy, an accurate, rapid and noninvasive indicator is urgently needed to predict its efficacy. In previous studies, dynamic radiomics predicted more accurately than conventional radiomics. Therefore, it is necessary to establish a dynamic radiomics efficacy prediction model for antiangiogenic therapy to provide more accurate guidance for clinical diagnosis and treatment decisions.MethodsIn this study, we use dynamic radiomics feature extraction method that extracts static features using tomographic images of different sequences of the same patient and then quantifies them into new dynamic features for the prediction of treatmentefficacy. In this retrospective study, we collected 76 patients who were diagnosed with unresectable CRLM between June 2016 and June 2021 in the First Hospital of China Medical University. All patients received standard treatment regimen of bevacizumab combined with chemotherapy in the first-line treatment, and contrast-enhanced abdominal CT (CECT) scans were performed before treatment. Patients with multiple primary lesions as well as missing clinical or imaging information were excluded. Area Under Curve (AUC) and accuracy were used to evaluate model performance. Regions of interest (ROIs) were independently delineated by two radiologists to extract radiomics features. Three machine learning algorithms were used to construct two scores based on the best response and progression-free survival (PFS).ResultsFor the task that predict the best response patients will achieve after treatment, by using ROC curve analysis, it can be seen that the relative change rate (RCR) feature performed best among all features and best in linear discriminantanalysis (AUC: 0.945 and accuracy: 0.855). In terms of predicting PFS, the Kaplan–Meier plots suggested that the score constructed using the RCR features could significantly distinguish patients with good response from those with poor response (Two-sided P<0.0001 for survival analysis).ConclusionsThis study demonstrates that the application of dynamic radiomics features can better predict the efficacy of CRLM patients receiving antiangiogenic therapy compared with conventional radiomics features. It allows patients to have a more accurate assessment of the effect of medical treatment before receiving treatment, and this assessment method is noninvasive, rapid, and less expensive. Dynamic radiomics model provides stronger guidance for the selection of treatment options and precision medicine.

show abstract

Predicting survival for hepatic arterial infusion chemotherapy of unresectable colorectal liver metastases: Radiomics analysis of pretreatment computed tomography

Cited by 22 publications

References 31 publications

Circulating tumor cells as potential prognostic biomarkers for early-stage pancreatic cancer: A systematic review and meta-analysis

Circulating tumor cells as potential prognostic biomarkers for early-stage pancreatic cancer: A systematic review and meta-analysis

Ultrasound Assessment of the Rectus Femoris in Patients with Chronic Obstructive Pulmonary Disease Predicts Sarcopenia

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases

Contact Info

Product

Resources

About