Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling.
Ontology highlight
ABSTRACT:
SUBMITTER: Li CH
PROVIDER: S-EPMC4760886 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:PURPOSE:To examine the correlations between uni-dimensional RECIST and volumetric measurements in patients with lung adenocarcinoma and to assess their association with overall survival (OS) and progression-free survival (PFS). MATERIALS AND METHODS:In this study of patients receiving chemotherapy for lung cancer in the setting of a clinical trial, response was prospectively evaluated using RECIST 1.0. Retrospectively, volumetric measurements were recorded and response was assessed by two different volumetric methods at each followup CT scan using a semi-automated segmentation algorithm. We subsequently evaluated the correlation between the uni-dimensional RECIST measurements and the volumetric measurements and performed landmark analyses for OS and PFS at the completion of the first and second follow-ups. Kaplan-Meier curves together with log-rank tests were used to evaluate the association between the different response criteria and patient outcome. RESULTS:Forty-two patients had CT scans at baseline, after the first follow up scan and second followup scan, and then every 8 weeks. The uni-dimensional RECIST measurements and volumetric measurements were strongly correlated, with a Spearman correlation coefficient (?) of 0.853 at baseline, ?=0.861 at the first followup, ?=0.843 at the 2nd followup, and ?=0.887 overall between-subject. On first follow-up CT, partial responders and non responders as assessed by an "ellipsoid" volumetric criteria showed a significant difference in OS (p=0.008, 1-year OS of 70% for partial responders and 46% for non responders). There was no difference between the groups when assessed by RECIST criteria on first follow-up CT (p=0.841, 1-year OS rate of 64% for partial responders and 64% for non responders). CONCLUSION:Volumetric response on first follow-up CT may better predict OS than RECIST response. CLINICAL RELEVANCE STATEMENT:Assessment of tumor size and response is of utmost importance in clinical trials. Volumetric measurements may help to better predict OS than uni-dimensional RECIST criteria.
| S-EPMC4750046 | biostudies-literature
Project description:Response Evaluation Criteria in Solid Tumors (RECIST) is the gold standard for assessment of treatment response in solid tumors. Morphologic change of tumor size evaluated by RECIST is often correlated with survival length and has been considered as a surrogate endpoint of therapeutic efficacy. However, the detection of morphologic change alone may not be sufficient for assessing response to new anti-cancer medication in all solid tumors. During the past fifteen years, several molecular-targeted therapies and immunotherapies have emerged in cancer treatment which work by disrupting signaling pathways and inhibited cell growth. Tumor necrosis or lack of tumor progression is associated with a good therapeutic response even in the absence of tumor shrinkage. Therefore, the use of unmodified RECIST criteria to estimate morphological changes of tumor alone may not be sufficient to estimate tumor response for these new anti-cancer drugs. Several studies have reported the low reliability of RECIST in evaluating treatment response in different tumors such as hepatocellular carcinoma, lung cancer, prostate cancer, brain glioma, bone metastasis, and lymphoma. There is an increased need for new medical imaging biomarkers, considering the changes in tumor viability, metabolic activity, and attenuation, which are related to early tumor response. Promising imaging techniques, beyond RECIST, include dynamic contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI), diffusion-weight imaging (DWI), magnetic resonance spectroscopy (MRS), and 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET). This review outlines the current RECIST with their limitations and the new emerging concepts of imaging biomarkers in oncology.
| S-EPMC8252278 | biostudies-literature
Project description:Large-molecule tracers, such as labeled antibodies, have shown success in immuno-PET for imaging of specific cell surface biomarkers. However, previous work has shown that localization of such tracers shows high levels of heterogeneity in target tissues, due to both the slow diffusion and the high affinity of these compounds. In this work, we investigate the effects of subvoxel spatial heterogeneity on measured time-activity curves in PET imaging and the effects of ignoring diffusion limitation on parameter estimates from kinetic modeling.Partial differential equations (PDE) were built to model a radially symmetric reaction-diffusion equation describing the activity of immuno-PET tracers. The effects of slower diffusion on measured time-activity curves and parameter estimates were measured in silico, and a modified Levenberg-Marquardt algorithm with Bayesian priors was developed to accurately estimate parameters from diffusion-limited data. This algorithm was applied to immuno-PET data of mice implanted with prostate stem cell antigen-overexpressing tumors and injected with (124)I-labeled A11 anti-prostate stem cell antigen minibody.Slow diffusion of tracers in linear binding models resulted in heterogeneous localization in silico but no measurable differences in time-activity curves. For more realistic saturable binding models, measured time-activity curves were strongly dependent on diffusion rates of the tracers. Fitting diffusion-limited data with regular compartmental models led to parameter estimate bias in an excess of 1,000% of true values, while the new model and fitting protocol could accurately measure kinetics in silico. In vivo imaging data were also fit well by the new PDE model, with estimates of the dissociation constant (Kd) and receptor density close to in vitro measurements and with order of magnitude differences from a regular compartmental model ignoring tracer diffusion limitation.Heterogeneous localization of large, high-affinity compounds can lead to large differences in measured time-activity curves in immuno-PET imaging, and ignoring diffusion limitations can lead to large errors in kinetic parameter estimates. Modeling of these systems with PDE models with Bayesian priors is necessary for quantitative in vivo measurements of kinetics of slow-diffusion tracers.
| S-EPMC4334373 | biostudies-literature
Project description:Exposure-response modeling facilitates effective dosing regimen selection in clinical drug development, where the end points are often disease scores and not physiological variables. Appropriate models need to be consistent with pharmacology and identifiable from the time courses of available data. This article describes a general framework of applying mechanism-based models to various types of clinical end points. Placebo and drug model parameterization, interpretation, and assessment are discussed with a focus on the indirect response models.
| S-EPMC4076802 | biostudies-other
Project description:BackgroundGraphical methods of radiotracer kinetic modeling in PET are ideal for parametric imaging and data quality assurance but can suffer from noise bias. This study compared the Logan and Multilinear Analysis-1 (MA1) graphical models to the standard one-tissue-compartment (1TC) model, including correction for partial-volume effects, in dynamic PET-CT studies of myocardial sympathetic innervation in the left ventricle (LV) using [11C]HED.MethodsTest and retest [11C]HED PET imaging (47 ± 22 days apart) was performed in 18 subjects with heart failure symptoms. Myocardial tissue volume of distribution (VT) was estimated using Logan and MA1 graphical methods and compared to the 1TC standard model values using intraclass correlation (ICC) and Bland-Altman analysis of the non-parametric reproducibility coefficient (NPC).ResultsA modeling start-time of t* = 5 min gave the best fit for both Logan and MA1 (R2 = 0.95) methods. Logan slightly underestimated VT relative to 1TC (p = 0.002), whereas MA1 did not (p = 0.96). Both the MA1 and Logan models exhibited good-to-excellent agreement with the 1TC (MA1-1TC ICC = 0.96; Logan-1TC ICC = 0.93) with no significant differences in NPC between the two comparisons (p = 0.92). All methods exhibited good-to-excellent test-retest repeatability with no significant differences in NPC (p = 0.57).ConclusionsLogan and MA1 models exhibited similar agreement and variability compared to the 1TC for modeling of [11C]HED kinetics. Using t* = 5 min and partial-volume correction produced accurate estimates of VT as an index of myocardial sympathetic innervation.
| S-EPMC6054601 | biostudies-literature
Project description:Etiologic studies of cancer increasingly use molecular features such as gene expression, DNA methylation and sequence mutation to subclassify the cancer type. In large population-based studies, the tumor tissues available for study are archival specimens that provide variable amounts of amplifiable DNA for molecular analysis. As molecular features measured from small amounts of tumor DNA are inherently noisy, we propose a novel approach to improve statistical efficiency when comparing groups of samples. We illustrate the phenomenon using the MethyLight technology, applying our proposed analysis to compare MLH1 DNA methylation levels in males and females studied in the Colon Cancer Family Registry.We introduce two methods for computing empirical weights to model heteroscedasticity that is caused by sampling variable quantities of DNA for molecular analysis. In a simulation study, we show that using these weights in a linear regression model is more powerful for identifying differentially methylated loci than standard regression analysis. The increase in power depends on the underlying relationship between variation in outcome measure and input DNA quantity in the study samples.Tumor characteristics measured from small amounts of tumor DNA are inherently noisy. We propose a statistical analysis that accounts for the measurement error due to sampling variation of the molecular feature and show how it can improve the power to detect differential characteristics between patient groups.
| S-EPMC3213130 | biostudies-literature
Project description:This technical note demonstrates computed tomography (CT) radiation profile measurement using computed radiography (CR) imaging plate raw data showing it is possible to perform the CT collimation width measurement using a single scan without saturating the imaging plate. Previously described methods require careful adjustments to the CR reader settings in order to avoid signal clipping in the CR processed image. CT radiation profile measurements were taken as part of routine quality control on 14 CT scanners from four vendors. CR cassettes were placed on the CT scanner bed, raised to isocenter, and leveled. Axial scans were taken at all available collimations, advancing the cassette for each scan. The CR plates were processed and raw CR data were analyzed using MATLAB scripts to measure collimation widths. The raw data approach was compared with previously established methodology. The quality control analysis scripts are released as open source using creative commons licensing. A log-linear relationship was found between raw pixel value and air kerma, and raw data collimation width measurements were in agreement with CR-processed, bit-reduced data, using previously described methodology. The raw data approach, with intrinsically wider dynamic range, allows improved measurement flexibility and precision. As a result, we demonstrate a methodology for CT collimation width measurements using a single CT scan and without the need for CR scanning parameter adjustments which is more convenient for routine quality control work.
| S-EPMC5690993 | biostudies-literature
Project description:The use of stereotactic ablative radiotherapy (SABR) for the treatment of primary lung cancer and metastatic disease is rapidly increasing. However, the presence of benign fibrotic changes on CT imaging makes response assessment following SABR a challenge, as these changes develop with an appearance similar to tumour recurrence. Misclassification of benign fibrosis as local recurrence has resulted in unnecessary interventions, including biopsy and surgical resection. Response evaluation criteria in solid tumours (RECIST) are widely used as a universal set of guidelines to assess tumour response following treatment. However, in the context of non-spherical and irregular post-SABR fibrotic changes, the RECIST criteria can have several limitations. Positron emission tomography can also play a role in response assessment following SABR; however, false-positive results in regions of inflammatory lung post-SABR can be a major clinical issue and optimal standardized uptake values to distinguish fibrosis and recurrence have not been determined. Although validated CT high-risk features show a high sensitivity and specificity for predicting recurrence, most recurrences are not detected until more than 1-year post-treatment. Advanced quantitative radiomic analysis on CT imaging has demonstrated promise in distinguishing benign fibrotic changes from local recurrence at earlier time points, and more accurately, than physician assessment. Overall, the use of RECIST alone may prove inferior to novel metrics of assessing response.
| S-EPMC5124920 | biostudies-literature
Project description:Background and purposeThe ability to perform neuroimaging on the angiography suite is important in making decisions during neurointerventions. Our aim was the evaluation of ACT as a fast available diagnostic tool during and after neuroendovascular procedures and the comparison of ACT with postinterventional MDCT.Materials and methodsEighty-four peri-interventional ACT acquisitions were obtained and evaluated: 38 after coil embolization of cerebral aneurysms, 16 after intracranial angioplasty with stent placement, and 30 after endovascular mechanical thrombectomy and lysis. Interventions and ACTs were performed on a biplane angiography system equipped with flat panel detectors. Postprocessing was performed on a dedicated workstation, and multiplanar reformations were generated. Reference studies were performed on a 16- or 128-section MDCT scanner. All studies were independently evaluated by 3 blinded neuroradiologists. The Wilcoxon test was applied for the statistical analysis.ResultsACT and MDCT images were of equal diagnostic quality in most cases related to the supratentorial ventricular system and the detection of hemorrhages (subarachnoidal, intraparenchymal, and intraventricular). Regarding the supratentorial ventricular system, an adequate diagnostic quality was assigned to 94% of the ACT acquisitions. For the detection of hemorrhage, no statistically significant difference was noted between ACT and MDCT. However, for the infratentorial region, ACT performed relatively poorly compared with MDCT. The diagnostic evaluation of gray matter (basal ganglia, insular cortex, and central cortex) by ACT is not sufficient, with <20% of the acquisitions scoring a diagnostic value.ConclusionsAfter neuroendovascular procedures and within the angiography suite, ACT enables an immediate detection of peri-interventional hemorrhage or hydrocephalus. However, for the detection of cerebral infarction, ACT is not yet reliable.
| S-EPMC7965444 | biostudies-literature
Project description:PurposeTo evaluate feasibility of CT colonography (CTC) volumetry of colorectal cancer (CRC) and its correlation with disease stage and patients' survival.Materials and methodsCTC volumetry was performed for 126 patients who underwent preoperative CTC. Reproducibility of tumor volume (Tvol) between two readers was assessed. One-way ANOVA and ROC analysis evaluated correlation between Tvol and pTNM staging. ROC analysis compared diagnostic performance to predict pTNM staging between Tvol and radiologist. Kaplan-Meier test compared overall survival.ResultsReproducibility among readers was excellent (interclass correlation = 0.9829). Mean Tvol showed an incremental trend with T stage and Tvol of pT4b stage was significantly larger than other stages (P<0.0001). Az value (0.780) of Tvol to predict pT4b stage was significantly larger than that (0.591) of radiologist (P = 0.004). However, Tvol was not significantly different according to pN stage. Az values (0.723~0.857) of Tvol to predict M1 or M1b were comparable to those (0.772~0.690) of radiologist (P>0.05). Smaller tumor burden (?12.85cm3), ?T3, N0, M0 stages, and curative surgery were significantly associated with patients' longer survival (P<0.05).ConclusionCT volumetry has a limited value to predict N stage; however, it may outperform the radiologist's performance when predicting pT4b and M1b stage and can be a useful prognostic marker.
| S-EPMC5453524 | biostudies-literature