FDG PET/CT as a Prognostic Test After 90Y Radioembolization in Patients With Metastatic Hepatic Disease

Zalom, Martina; Yu, Run; Friedman, Marc L.; Bresee, Catherine; Waxman, Alan

doi:10.1097/rlu.0b013e318262af7f

Cited by 11 publications

(3 citation statements)

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“…Recently, the degree of tumor uptake of 18 FDG on PET as assessed by the SUV was shown to be an independent prognostic factor in liver metastases [ 26 , 27 ], but some studies have not found a significant association between SUV and prognosis [ 28 – 30 ]. Apparently, there have been controversial results.…”

Section: Discussionmentioning

confidence: 99%

Prognostic significance of 18FDG PET/CT in colorectal cancer patients with liver metastases: a meta-analysis

Xin

et al. 2015

cancer imaging

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BackgroundThe role of 18-fluorodeoxyglucose positron emission tomography CT (18FDG PET/CT), as a prognostic factor for survival in colorectal cancer patients with liver metastases, is still controversial. We sought to perform a meta-analysis of the literature to address this issue.MethodsA systematic literature search was performed to identify the studies that associated 18FDG PET/CT to clinical survival outcomes of patients with liver metastases. Methodological qualities of the included studies were also assessed. The summarized hazard ratio (HR) was estimated by using fixed- or random-effect model according to heterogeneity between trails.ResultsBy analyzing a total of 867 patients from 15 studies, we found that PET/CT for metabolic response to the therapy was capable of predicting event-free survival (EFS) and overall survival (OS) with statistical significance, and the HR was 0.45 (95 % confidence interval [CI], 0.26–0.78) and 0.36 (95 % CI, 0.18–0.71), respectively. Furthermore, pre-treatment 18FDG PET/CT with high standardized uptake value (SUV) was also significantly associated with poorer OS HR, 1.24; (95 % CI, 1.06–1.45). However, we did not find a statistically significant effect of post-treatment SUV for predicting OS HR, 1.68; (95 % CI, 0.63–4.52).ConclusionsThe present meta-analysis confirms that 18FDG PET/CT is a useful tool to help predict survival outcomes in patients with liver metastases.Electronic supplementary materialThe online version of this article (doi:10.1186/s40644-015-0055-z) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Prognostic significance of 18FDG PET/CT in colorectal cancer patients with liver metastases: a meta-analysis

Xin

et al. 2015

cancer imaging

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“…7 Computed tomography assessments use size-based revised Response Evaluation Criteria in Solid Tumors (RECIST 1.1) 8 or tumor necrosis-based Choi criteria. 9 Recent reports have shown that FDG PET/CT was useful in predicting the overall survival after Y90-RE in patients with FDG-avid liver metastases 10,11 or primary liver cancers, 12 especially cholangiocarcinomas. 13 The objective of this study is to create a model that predicts patient treatment response from the pretherapy FDG PET/CT scan alone.…”

Section: Introductionmentioning

confidence: 99%

A Lesion-Based Response Prediction Model Using Pretherapy PET/CT Image Features for Y90 Radioembolization to Hepatic Malignancies

Mehta

Cai

Kumar

et al. 2016

Technol Cancer Res Treat

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We present a probabilistic approach to identify patients with primary and secondary hepatic malignancies as responders or nonresponders to yttrium-90 radioembolization therapy. Recent advances in computer-aided detection have decreased false-negative and false-positive rates of perceived abnormalities; however, there is limited research in using similar concepts to predict treatment response. Our approach is driven by the goal of precision medicine to determine pretherapy fluorine-18-2-fluoro-2-deoxy-d-glucose positron emission tomography and computed tomography imaging parameters to facilitate the identification of patients who would benefit most from yttrium-90 radioembolization therapy, while avoiding complex and costly procedures for those who would not. Our algorithm seeks to predict a patient's response by discovering common co-occurring image patterns in the lesions of baseline fluorine-18-2-fluoro-2-deoxy-d-glucose positron emission tomography and computed tomography scans by extracting invariant shape and texture features. The extracted imaging features were represented as a distribution of each subject based on the bag-of-feature paradigm. The distribution was applied in a multinomial naive Bayes classifier to predict whether a patient would be a responder or nonresponder to yttrium-90 radioembolization therapy based on the imaging features of a pretherapy fluorine-18-2-fluoro-2-deoxy-d-glucose positron emission tomography and computed tomography scan. Comprehensive published criteria were used to determine lesion-based clinical treatment response based on fluorine-18-2-fluoro-2-deoxy-d-glucose positron emission tomography and computed tomography imaging findings. Our results show that the model is able to predict a patient with liver cancer as a responder or nonresponder to yttrium-90 radioembolization therapy with a sensitivity of 0.791 using extracted invariant imaging features from the pretherapy fluorine-18-2-fluoro-2-deoxy-d-glucose positron emission tomography and computed tomography test. The sensitivity increased to 0.821 when combining extracted invariant image features with variable features of tumor volume.

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“…The formulation of the dose calculation is given in the Equation where BSA is body surface area. The role of PET in the SIRT treatment has been steadily increasing, not just for treatment planning, but also for prognostic evaluation [25][26][27]. Both tumor volume and standard uptake value are used for prognostic evaluation [22,25,26].…”

Section: Y-90 Microparticlesmentioning

confidence: 99%

Positron Emission Tomography (PET) Tumor Segmentation and Quantification: Development of New Algorithms

Bhatt¹

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Professor Anthony McGoron, Major ProfessorTumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and iv with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ~10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.

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FDG PET/CT as a Prognostic Test After 90Y Radioembolization in Patients With Metastatic Hepatic Disease

Cited by 11 publications

References 0 publications

Prognostic significance of 18FDG PET/CT in colorectal cancer patients with liver metastases: a meta-analysis

Prognostic significance of 18FDG PET/CT in colorectal cancer patients with liver metastases: a meta-analysis

A Lesion-Based Response Prediction Model Using Pretherapy PET/CT Image Features for Y90 Radioembolization to Hepatic Malignancies

Positron Emission Tomography (PET) Tumor Segmentation and Quantification: Development of New Algorithms

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