ArticleJCO clinical cancer informatics2017
Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm.
Article in JCO clinical cancer informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00154102 (Open, Randomized, Controlled, Multicenter Phase III Study Comparing 5FU/ FA Plus Irinotecan Plus Cetuximab Versus 5FU/FA Plus Irinotecan as First-line Treatment for Epidermal Growth Factor Receptor-expressing Metastatic Colorectal Cancer), which is not on this map. Cited by 17 papers.
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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.
Open, Randomized, Controlled, Multicenter Phase III Study Comparing 5FU/ FA Plus Irinotecan Plus Cetuximab Versus 5FU/FA Plus Irinotecan as First-line Treatment for Epidermal Growth Factor Receptor-expressing Metastatic Colorectal Cancer
Who cites it
17 citing papers in PubMed, 25 citations in OpenAlex.
- Trial
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- Annotated test-retest dataset of lung cancer CT scan images reconstructed at multiple imaging parameters.Scientific data · 2024Article
- Machine learning-based identification of contrast-enhancement phase of computed tomography scans.PloS one · 2024Article
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- Contrast phase recognition in liver computer tomography using deep learning.Scientific reports · 2022Article
- Understanding Sources of Variation to Improve the Reproducibility of Radiomics.Frontiers in oncology · 2021Review
- Radiomics Response Signature for Identification of Metastatic Colorectal Cancer Sensitive to Therapies Targeting EGFR Pathway.Journal of the National Cancer Institute · 2020Article
- Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Article
- Using a single abdominal computed tomography image to differentiate five contrast-enhancement phases: A machine-learning algorithm for radiomics-based precision medicine.European journal of radiology · 2020Article
- Automated Identification of Optimal Portal Venous Phase Timing with Convolutional Neural Networks.Academic radiology · 2020Article
- Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules.European radiology · 2020Article
- Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom.Tomography (Ann Arbor, Mich.) · 2019Article
- CT Slice Thickness and Convolution Kernel Affect Performance of a Radiomic Model for Predicting EGFR Status in Non-Small Cell Lung Cancer: A Preliminary Study.Scientific reports · 2018Article
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Authors and funding
10 authors at 1 institution in 2 countries.
Funding
Abstract
purposeNew response patterns to anticancer drugs have led tumor size-based response criteria to shift to also include density measurements. Choi criteria, for instance, categorize antiangiogenic therapy response as a decrease in tumor density > 15% at the portal venous phase (PVP). We studied the effect that PVP timing has on measurement of the density of liver metastases (LM) from colorectal cancer (CRC).
methodsPretreatment PVP computed tomography images from 291 patients with LM-CRC from the CRYSTAL trial (Cetuximab Combined With Irinotecan in First-Line Therapy for Metastatic Colorectal Cancer; ClinicalTrials.gov identifier: NCT00154102) were included. Four radiologists independently scored the scans' timing according to a three-point scoring system: early, optimal, late PVP. Using this, we developed, by machine learning, a proprietary computer-aided quality-control algorithm to grade PVP timing. The reference standard was a computer-refined consensus. For each patient, we contoured target liver lesions and calculated their mean density.
resultsContrast-product administration data were not recorded in the digital imaging and communications in medicine headers for injection volume (94%), type (93%), and route (76%). The PVP timing was early, optimal, and late in 52, 194, and 45 patients, respectively. The mean (95% CI) accuracy of the radiologists for detection of optimal PVP timing was 81.7% (78.3 to 85.2) and was outperformed by the 88.6% (84.8 to 92.4) computer accuracy. The mean ± standard deviation of LM-CRC density was 68 ± 15 Hounsfield units (HU) overall and 59.5 ± 14.9 HU, 71.4 ± 14.1 HU, 62.4 ± 12.5 HU at early, optimal, and late PVP timing, respectively. LM-CRC density was thus decreased at nonoptimal PVP timing by 14.8%: 16.7% at early PVP ( P < .001) and 12.6% at late PVP ( P < .001).
conclusionNonoptimal PVP timing should be identified because it significantly decreased tumor density by 14.8%. Our computer-aided quality-control system outperformed the accuracy, reproducibility, and speed of radiologists' visual scoring. PVP-timing scoring could improve the extraction of tumor quantitative imaging biomarkers and the monitoring of anticancer therapy efficacy at the patient and clinical trial levels.
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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.