Dataset Information

Prognostic modeling for patients with colorectal liver metastases incorporating FDG PET radiomic features.

ABSTRACT: OBJECTIVE:We aimed to improve prediction of outcome for patients with colorectal liver metastases, via prognostic models incorporating PET-derived measures, including radiomic features that move beyond conventional standard uptake value (SUV) measures. PATIENTS AND METHODS:A range of parameters including volumetric and heterogeneity measures were derived from FDG PET images of 52 patients with colorectal intrahepatic-only metastases (29 males and 23 females; mean age 62.9 years [SD 9.8; range 32-82]). The patients underwent PET/CT imaging as part of the clinical workup prior to final decision on treatment. Univariate and multivariate models were implemented, which included statistical considerations (to discourage false discovery and overfitting), to predict overall survival (OS), progression-free survival (PFS) and event-free survival (EFS). Kaplan-Meier survival analyses were performed, where the subjects were divided into high-risk and low-risk groups, from which the hazard ratios (HR) were computed via Cox proportional hazards regression. RESULTS:Commonly-invoked SUV metrics performed relatively poorly for different prediction tasks (SUVmax HR?=?1.48, 0.83 and 1.16; SUVpeak HR?=?2.05, 1.93, and 1.64, for OS, PFS and EFS, respectively). By contrast, the number of liver metastases and metabolic tumor volume (MTV) each performed well (with respective HR values of 2.71, 2.61 and 2.42, and 2.62, 1.96 and 2.29, for OS, PFS and EFS). Total lesion glycolysis (TLG) also resulted in similar performance as MTV. Multivariate prognostic modeling incorporating different features (including those quantifying intra-tumor heterogeneity) resulted in further enhanced prediction. Specifically, HR values of 4.29, 4.02 and 3.20 (p-values?=?0.00004, 0.0019 and 0.0002) were obtained for OS, PFS and EFS, respectively. CONCLUSIONS:PET-derived measures beyond commonly invoked SUV parameters hold significant potential towards improved prediction of clinical outcome in patients with liver metastases, especially when utilizing multivariate models.

SUBMITTER: Rahmim A

PROVIDER: S-EPMC7507885 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Prognostic modeling for patients with colorectal liver metastases incorporating FDG PET radiomic features.

Rahmim Arman A Bak-Fredslund Kirstine P KP Ashrafinia Saeed S Lu Lijun L Schmidtlein C Ross CR Subramaniam Rathan M RM Morsing Anni A Keiding Susanne S Horsager Jacob J Munk Ole L OL

European journal of radiology 20190208

<h4>Objective</h4>We aimed to improve prediction of outcome for patients with colorectal liver metastases, via prognostic models incorporating PET-derived measures, including radiomic features that move beyond conventional standard uptake value (SUV) measures.<h4>Patients and methods</h4>A range of parameters including volumetric and heterogeneity measures were derived from FDG PET images of 52 patients with colorectal intrahepatic-only metastases (29 males and 23 females; mean age 62.9 years [S ...[more]

PMID: 30927933

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Project description:Knowledge of the intrinsic variability of radiomic features is essential to the proper interpretation of changes in these features over time. The primary aim of this study was to assess the test-retest repeatability of radiomic features extracted from 18F-FDG PET images of cervical tumors. The impact of different image preprocessing methods was also explored. Methods: Patients with cervical cancer underwent baseline and repeat 18F-FDG PET/CT imaging within 7 d. PET images were reconstructed using 2 methods: ordered-subset expectation maximization (PETOSEM) or ordered-subset expectation maximization with point-spread function (PETPSF). Tumors were segmented to produce whole-tumor volumes of interest (VOIWT) and 40% isocontours (VOI40). Voxels were either left at the default size or resampled to 3-mm isotropic voxels. SUV was discretized to a fixed number of bins (32, 64, or 128). Radiomic features were extracted from both VOIs, and repeatability was then assessed using the Lin concordance correlation coefficient (CCC). Results: Eleven patients were enrolled and completed the test-retest PET/CT imaging protocol. Shape, neighborhood gray-level difference matrix, and gray-level cooccurrence matrix features were repeatable, with a mean CCC value of 0.81. Radiomic features extracted from PETOSEM images showed significantly better repeatability than features extracted from PETPSF images (P < 0.001). Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT (P < 0.001). For most features (78.4%), a change in bin number or voxel size resulted in less than a 10% change in feature value. All gray-level emphasis and gray-level run emphasis features showed poor repeatability (CCC values < 0.52) when extracted from VOIWT but were highly repeatable (mean CCC values > 0.96) when extracted from VOI40 Conclusion: Shape, gray-level cooccurrence matrix, and neighborhood gray-level difference matrix radiomic features were consistently repeatable, whereas gray-level run length matrix and gray-level zone length matrix features were highly variable. Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT Changes in voxel size or SUV discretization parameters typically resulted in relatively small differences in feature value, though several features were highly sensitive to these changes.

Project description:BackgroundDeriving individual tumor genomic characteristics from patient imaging analysis is desirable. We explore the predictive value of 2-[18F]FDG uptake with regard to the KRAS mutational status of colorectal adenocarcinoma liver metastases (CLM).Methods2-[18F]FDG PET/CT images, surgical pathology and molecular diagnostic reports of 37 patients who underwent PET/CT-guided biopsy of CLM were reviewed under an IRB-approved retrospective research protocol. Sixty CLM in 39 interventional PET scans of the 37 patients were segmented using two different auto-segmentation tools implemented in different commercially available software packages. PET standard uptake values (SUV) were corrected for: (1) partial volume effect (PVE) using cold wall-corrected contrast recovery coefficients derived from phantom spheres with variable diameter and (2) variability of arterial tracer supply and variability of uptake time after injection until start of PET scan derived from the tumor-to-blood standard uptake ratio (SUR) approach. The correlations between the KRAS mutational status and the mean, peak and maximum SUV were investigated using Student's t test, Wilcoxon rank sum test with continuity correction, logistic regression and receiver operation characteristic (ROC) analysis. These correlation analyses were also performed for the ratios of the mean, peak and maximum tumor uptake to the mean blood activity concentration at the time of scan: SURMEAN, SURPEAK and SURMAX, respectively.ResultsFifteen patients harbored KRAS missense mutations (KRAS+), while another 3 harbored KRAS gene amplification. For 31 lesions, the mutational status was derived from the PET/CT-guided biopsy. The Student's t test p values for separating KRAS mutant cases decreased after applying PVE correction to all uptake metrics of each lesion and when applying correction for uptake time variability to the SUR metrics. The observed correlations were strongest when both corrections were applied to SURMAX and when the patients harboring gene amplification were grouped with the wild type: p ≤ 0.001; ROC area under the curve = 0.77 and 0.75 for the two different segmentations, respectively, with a mean specificity of 0.69 and sensitivity of 0.85.ConclusionThe correlations observed after applying the described corrections show potential for assigning probabilities for the KRAS missense mutation status in CLM using 2-[18F]FDG PET images.

Project description:Purpose. To investigate the value of SUV metrics and radiomic features based on the ability of 18F-FDG PET/CT in differentiating between breast lymphoma and breast carcinoma. Methods. A total of 67 breast nodules from 44 patients who underwent 18F-FDG PET/CT pretreatment were retrospectively analyzed. Radiomic parameters and SUV metrics were extracted using the LIFEx package on PET and CT images. All texture parameters were divided into six groups: histogram (HISTO), SHAPE, gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), neighborhood gray-level different matrix (NGLDM), and gray-level zone-length matrix (GLZLM). Receiver operating characteristics (ROC) curves were generated to evaluate the discriminative ability of each parameter, and the optimal parameter in each group was selected to generate a new predictive variable by using binary logistic regression. PET predictive variable, CT predictive variable, the combination of PET and CT predictive variables, and SUVmax were compared in terms of areas under the curve (AUCs), sensitivity, specificity, and accuracy. Results. Except for SUVmin (p=0.971), the averages of FDG uptake metrics of lymphoma were significantly higher than those of carcinoma (p ≤ 0.001), with the following median values: SUVmean, 4.75 versus 2.38 g/ml (P < 0.001); SUVstd, 2.04 versus 0.88 g/ml (P=0.001); SUVmax, 10.69 versus 4.76 g/ml (P=0.001); SUVpeak, 9.15 versus 2.78 g/ml (P < 0.001); TLG, 42.24 versus 9.90 (P < 0.001). In the ROC curves analysis based on radiomic features and SUVmax, the AUC for SUVmax was 0.747, for CT texture parameters was 0.729, for PET texture parameters was 0.751, and for the combination of CT and PET texture parameters was 0.771. Conclusion. The SUV metrics in 18FDG PET/CT images showed a potential ability in the differentiation between breast lymphoma and carcinoma. The combination of SUVmax and PET/CT texture analysis may be promising to provide an effectively discriminant modality for the differential diagnosis of breast lymphoma and carcinoma, even for the differentiation of subtypes of lymphoma.

Project description:Early detection of gastrointestinal stromal tumor (GIST) liver metastases is crucial for the management and prognosis. In our experience, GIST liver metastases can display hypermetabolism on 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and marked enhancement on magnetic resonance imaging (MRI), which are uncommon in other tumors before treatment. Most literature focus on the imaging evaluation, prognosis after treatment and less is known about imaging features on both imaging methods before treatment. This study analyzes the imaging features of newly diagnosed GIST liver metastases on 18F-FDG PET/CT and MRI, with goal of improving diagnostic accuracy. This retrospective study included 55 patients with pathological or radiographical confirmed GIST liver metastases who underwent PET/CT (n=29), MRI (n=22), or both methods (n=4). PET/CT and MRI interpretation including lesion's morphologic features, number, density or signal intensity, hemorrhage, cystic changes or necrosis, maximum standardized uptake value (SUVmax) of liver metastases and liver background on PET imaging, degree and pattern of enhancement on MRI were obtained by two experienced nuclear medicine physicians and two radiologists respectively. Data are presented as numbers, percentages, means ± standard deviations or median (interquartile range). The correlation between diameter and SUVmax of metastases, and primary tumor SUVmax and synchronous liver metastases SUVmax were analyzed by Spearman's rank test. On PET/CT visual analysis, 38.9%, 23.9%, and 37.2% of lesions showed significant hypermetabolism, slightly higher metabolism, and equal or lower metabolism than liver, respectively. There was a weak correlation between the diameter and SUVmax of liver metastases (rs =0.370, P<0.001), and a moderate correlation between SUVmax of synchronous liver metastases and the primary tumors (rs =0.492, P<0.001). On contrast-enhanced MRI, 90.8% of lesions showed heterogeneous enhancement in the arterial phase with the variable presentation, and 74.3% had different enhancement patterns between margins and intratumoral parenchyma. Liver lesions in GIST displaying significant, slight hypermetabolism on 18F-FDG PET/CT, marked or heterogeneous gradual enhancement within the intratumoral parenchyma with ring-like enhancement on MRI may denote the diagnosis of liver metastasis. However, GIST liver metastases may also display equal or lower metabolism than liver parenchyma on PET, making small lesions more difficult to diagnose.

Project description:ObjectivesThis prospective study assessed the role of F-18-FDG-PET/CT in clinical staging for patients with colorectal cancer planned for pulmonary metastasectomy by thoracotomy or video-assisted surgery.Patients and methodsIn addition to conventional imaging, we performed 86 F-18-FDG-PET/CT studies in 76 patients with potentially resectable metastatic colorectal lung metastases. We then investigated the effect that PET/CT had on further clinical management. Based on the results from the 47 thoracotomies performed, we compared the number of pulmonary metastases discovered after histologic examination with the number predicted by the conventional computed tomography (CT) as an independent part of the F-18-FDG-PET/CT examination and by the F-18-FDG-PET component.ResultsF-18-FDG-PET/CT led to changes in treatment regime and diagnostic planning in many patients. In five patients PET/CT revealed previously undetected local recurrence of the primary colorectal cancer, in four patients hepatic metastases, in three patients bone metastases, in two patients soft-tissue metastases, and in three patients histologically preoperatively proven N2 or N3 station lymph node involvement. These all constituted exclusion criteria, and consequently the previously planned pulmonary metastasectomy was not performed. The sensitivity and positive predictive value (PPV) for detection of pulmonary metastases were 84.2% and 36.4% for CT and 75.0% and 61.6% for F-18-FDG-PET study. The calculated sensitivity, specificity, PPV, and NPV of F-18-FDG-PET/CT for detecting thoracic lymph node involvement were 85.7%, 93.0%, 66.7%, and 97.5%, respectively. Furthermore, we found that F-18-FDG-PET/CT may predict thoracic lymph node involvement based on the SUV of pulmonary nodules.ConclusionsF-18-FDG-PET/CT has a clear role in the diagnostic workup for pulmonary metastatic colorectal cancer and may save patients from futile surgery. It cannot, however, be relied on to detect all possible pulmonary and nodal metastases, which surgeons must always consider when making treatment decisions.

Dataset Information

Prognostic modeling for patients with colorectal liver metastases incorporating FDG PET radiomic features.

Publications

Prognostic modeling for patients with colorectal liver metastases incorporating FDG PET radiomic features.

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