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Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm.

ABSTRACT: PURPOSE:New 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). METHODS:Pretreatment 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. RESULTS:Contrast-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). CONCLUSION:Nonoptimal 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.

SUBMITTER: Dercle L

PROVIDER: S-EPMC6874047 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm.

Dercle Laurent L Lu Lin L Lichtenstein Philip P Yang Hao H Wang Deling D Zhu Jianguo J Wu Feiyun F Piessevaux Hubert H Schwartz Lawrence H LH Zhao Binsheng B

JCO clinical cancer informatics 20171101

<h4>Purpose</h4>New 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).<h4>Methods</h4>Pretreatment PVP computed tomography images from 291 patients with ...[more]

PMID: 30657405

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Project description:Tumor cells circulate in low numbers in peripheral blood; their detection is used predominantly in metastatic disease. We evaluated the feasibility and safety of sampling portal venous blood via endoscopic ultrasound (EUS) to count portal venous circulating tumor cells (CTCs), compared with paired peripheral CTCs, in patients with pancreaticobiliary cancers (PBCs).In a single-center cohort study, we evaluated 18 patients with suspected PBCs. Under EUS guidance, a 19-gauge EUS fine needle was advanced transhepatically into the portal vein and as many as four 7.5-mL aliquots of blood were aspirated. Paired peripheral blood samples were obtained. Epithelial-derived CTCs were sorted magnetically based on expression of epithelial cell adhesion molecules; only those with a proper morphology and found to be CD45 negative and positive for cytokeratins 8, 18, and/or 19 and 4',6-diamidino-2-phenylindole were considered to be CTCs. For 5 samples, CTCs also were isolated by flow cytometry and based on CD45 depletion. ImageStream was used to determine the relative protein levels of P16, SMAD4, and P53. DNA was extracted from CTCs for sequencing of select KRAS codons.There were no complications from portal vein blood acquisition. We detected CTCs in portal vein samples from all 18 patients (100%) vs peripheral blood samples from only 4 patients (22.2%). Patients with confirmed PBCs had a mean of 118.4 ± 36.8 CTCs/7.5 mL portal vein blood, compared with a mean of 0.8 ± 0.4 CTCs/7.5 mL peripheral blood (P < .01). The 9 patients with nonmetastatic, resectable, or borderline-resectable PBCs had a mean of 83.2 CTCs/7.5 mL portal vein blood (median, 62.0 CTCs/7.5 mL portal vein blood). In a selected patient, portal vein CTCs were found to carry the same mutations as those detected in a metastatic lymph node and expressed similar levels of P16, SMAD4, and P53 proteins.It is feasible and safe to collect portal venous blood from patients undergoing EUS. We identified CTCs in all portal vein blood samples from patients with PBCs, but less than 25% of peripheral blood samples. Portal vein CTCs can be used for molecular characterization of PBCs and share features of metastatic tissue. This technique might be used to study the pathogenesis and progression of PBCs, as well as a diagnostic or prognostic tool to stratify risk of cancer recurrence or developing metastases.

Project description:ObjectiveMeasurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT) volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limited application in clinical practice due to its time-consuming segmentation process. We aimed to develop and validate a deep learning algorithm (DLA) for fully automated liver and spleen segmentation using portal venous phase CT images in various liver conditions.Materials and methodsA DLA for liver and spleen segmentation was trained using a development dataset of portal venous CT images from 813 patients. Performance of the DLA was evaluated in two separate test datasets: dataset-1 which included 150 CT examinations in patients with various liver conditions (i.e., healthy liver, fatty liver, chronic liver disease, cirrhosis, and post-hepatectomy) and dataset-2 which included 50 pairs of CT examinations performed at ours and other institutions. The performance of the DLA was evaluated using the dice similarity score (DSS) for segmentation and Bland-Altman 95% limits of agreement (LOA) for measurement of the volumetric indices, which was compared with that of ground truth manual segmentation.ResultsIn test dataset-1, the DLA achieved a mean DSS of 0.973 and 0.974 for liver and spleen segmentation, respectively, with no significant difference in DSS across different liver conditions (p = 0.60 and 0.26 for the liver and spleen, respectively). For the measurement of volumetric indices, the Bland-Altman 95% LOA was -0.17 ± 3.07% for liver volume and -0.56 ± 3.78% for spleen volume. In test dataset-2, DLA performance using CT images obtained at outside institutions and our institution was comparable for liver (DSS, 0.982 vs. 0.983; p = 0.28) and spleen (DSS, 0.969 vs. 0.968; p = 0.41) segmentation.ConclusionThe DLA enabled highly accurate segmentation and volume measurement of the liver and spleen using portal venous phase CT images of patients with various liver conditions.

Dataset Information

Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm.

Publications

Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm.

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