Dataset Information

Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation.

ABSTRACT:

Purpose

Mathematical models combined with new imaging technologies could improve clinical oncology studies. To improve detection of therapeutic effect in patients with cancer, we assessed volumetric measurement of target lesions to estimate the rates of exponential tumor growth and regression as treatment is administered.

Experimental design

Two completed phase III trials were studied (988 patients) of aflibercept or panitumumab added to standard chemotherapy for advanced colorectal cancer. Retrospectively, radiologists performed semiautomated measurements of all metastatic lesions on CT images. Using exponential growth modeling, tumor regression (d) and growth (g) rates were estimated for each patient's unidimensional and volumetric measurements.

Results

Exponential growth modeling of volumetric measurements detected different empiric mechanisms of effect for each drug: panitumumab marginally augmented the decay rate [tumor half-life; d [IQR]: 36.5 days (56.3, 29.0)] of chemotherapy [d: 44.5 days (67.2, 32.1), two-sided Wilcoxon P = 0.016], whereas aflibercept more significantly slowed the growth rate [doubling time; g = 300.8 days (154.0, 572.3)] compared with chemotherapy alone [g = 155.9 days (82.2, 347.0), P ≤ 0.0001]. An association of g with overall survival (OS) was observed. Simulating clinical trials using volumetric or unidimensional tumor measurements, fewer patients were required to detect a treatment effect using a volumetric measurement-based strategy (32-60 patients) than for unidimensional measurement-based strategies (124-184 patients).

Conclusions

Combined tumor volume measurement and estimation of tumor regression and growth rate has potential to enhance assessment of treatment effects in clinical studies of colorectal cancer that would not be achieved with conventional, RECIST-based unidimensional measurements.

SUBMITTER: Maitland ML

PROVIDER: S-EPMC8170504 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesLate contrast enhancement CT (LCE-CT) visualizes the presence of myocardial infarcts. Differentiation of the contrast-enhanced infarct from blood pool is challenging. We developed a novel method using data from first pass CT angiography (CTA) imaging to enable automatic infarct detection.Materials and methodsA canine model of myocardial infarction was produced in 11 animals. Two months later, first pass CTA (90 kVp) and LCE-CT (dual energy 90 kVp/150 kVp tin filtered) were performed. Late gadolinium enhancement MRI was used as reference standard. The CTA and LCE-CT were co-registered using a fully automatic non-rigid method based on curved B-splines. The method allowed for limited elastic deformation and the considerable differences in attenuation between first-pass and delayed image. The blood pool was easily identified on the CTA image by high attenuation. Because CTA and LCE-CT were registered, the blood pool segmentation can be directly transferred to the LCE-CT - thereby solving the key problem of infarct/blood pool differentiation. The remaining segmentation of infarcted vs. noninfarcted myocardium was performed using a threshold. Automatic and MRI-guided expert segmentations of LCE-CT infarcts were compared to each other on volume and area basis (intraclass correlation coefficient, ICC) and on voxel basis (dice similarity coefficient, DSC between automatic and expert CT segmentation). CT infarct volumes were compared with the reference standard MRI.ResultsThe infarcts were mainly subendocardial (81%) and relatively small (median MRI infarct mass 7.4 g). The automatic segmentation showed excellent agreement with expert segmentation on volume and area measurements (ICC = 0.96 and 0.87, respectively). DSC showed moderately good agreement (DSC = 0.47). Compared to MRI there was modest agreement (ICC = 0.62) and excellent correlation (R = 0.9). Manual interaction was less than 1 min per exam.ConclusionWe propose an automatic method for infarct segmentation on LCE-CT using multiphase CT information, which showed excellent agreement with expert readers and favorable correlation with MRI.

Project description:PurposeMedical oncology needs early identification of patients that are not responding to systemic therapy. (18)F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) performed before and early during treatment has been proposed for this purpose. However, the best way to assess the change in FDG uptake between two scans has not been identified. We studied cutoff thresholds to identify responding tumours as a function of the method used to measure tumour uptake.MethodsThe study included 28 metastatic colorectal cancer (mCRC) patients who underwent 2 FDG PET/CT scans (baseline and at day 14 of the first course of polychemotherapy). For 78 tumour lesions, 4 standardized uptake value (SUV) indices were measured: maximum SUV (SUV(max)) and mean SUV in a region obtained using an isocontour (SUV(40 %)), with each of these SUV normalized either by the patient body weight (BW) or body surface area (BSA). The per cent change and absolute change in tumour uptake between the baseline and the early PET scans were measured based on these four indices. These changes were correlated to the RECIST 1.0-based response using contrast-enhanced CT at baseline and at 6-8 weeks on treatment.ResultsThe 78 tumours were classified as non-responding (NRL, n = 58) and responding lesions (RL, n = 20). Receiver-operating characteristic (ROC) curves characterizing the performance in NRL/RL classification using early FDG PET uptake had areas under the curve between 0.75 and 0.84, without significant difference between the indices. The cutoff threshold in FDG uptake per cent change to get a 95 % sensitivity of RL detection depended on the way uptake was measured: -14 % (specificity of 53 %) and -22 % (specificity of 64 %) for SUV(max) and SUV(40 %), respectively. Thresholds expressed as absolute SUV decrease instead of per cent change were less sensitive to the SUV definition: an SUV decline by 1.2 yielded a sensitivity of RL detection of 95 % for SUV(max) and SUV(40 %). For a given cutoff threshold, the sensitivity was the same whatever the normalization (by BSA or BW).ConclusionA 14 % drop of tumour FDG SUV(max), 22 % drop of SUV(40 %) or 1.2 drop of SUV(max) or SUV(mean) after one single course of polychemotherapy predicts objective response in mCRC lesions with a high sensitivity, potentially allowing the early identification of non-responding patients.

Project description:PurposeTo evaluate the feasibility of using contrast material-enhanced computed tomographic (CT) measurements of hepatic fractional extracellular space (fECS) and macromolecular contrast material (MMCM) uptake to measure severity of liver fibrosis.Materials and methodsAll procedures were approved by and executed in accordance with University of California, San Francisco, institutional animal care and use committee regulations. Twenty-one rats that received intragastric CCl(4) for 0-12 weeks were imaged with respiratory-gated micro-CT by using both a conventional contrast material and a novel iodinated MMCM. Histopathologic hepatic fibrosis was graded qualitatively by using the Ishak fibrosis score and quantitatively by using morphometry of the fibrosis area. Hepatic fECS and MMCM uptake were calculated for each examination and correlated with histopathologic findings by using uni- and multivariate linear regressions.ResultsIshak fibrosis scores ranged from a baseline of 0 in untreated animals to a maximum of 5. Histopathologic liver fibrosis area increased from 0.46% to 3.5% over the same interval. Strong correlations were seen between conventional contrast-enhanced CT measurements of fECS and both the Ishak fibrosis scores (R(2) = 0.751, P < .001) and the fibrosis area (R(2) = 0.801, P < .001). Strong negative correlations were observed between uptake of MMCM in the liver and Ishak fibrosis scores (R(2) = 0.827, P < .001), as well as between uptake of MMCM in the liver and fibrosis area (R(2) = 0.643, P = .001). Multivariate linear regression analysis showed a trend toward independence for fECS and MMCM uptake in the prediction of Ishak fibrosis scores, with an R(2) value of 0.86 (P = .081 and P = .033, respectively).ConclusionContrast-enhanced CT measurements of fECS and MMCM uptake are individually capable of being used to estimate the degree of early hepatic fibrosis in a rat model.Supplemental materialhttp://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112452/-/DC1.