Comparison of PET metabolic indices for the early assessment of tumour response in metastatic colorectal cancer patients treated by polychemotherapy

Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [18F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) in Patients with Head and Neck Cancer

Background. Head and neck cancer (HNC) is the seventh most common neoplastic disorder at the global level. Contouring HNC lesions on [18F] Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) scans plays a fundamental role for diagnosis, risk assessment, radiotherapy planning and post-treatment evaluation. However, manual contouring is a lengthy and tedious procedure which requires significant effort from the clinician. Methods. We evaluated the performance of six hand-crafted, training-free methods (four threshold-based, two algorithm-based) for the semi-automated delineation of HNC lesions on FDG PET/CT. This study was carried out on a single-centre population of n=103 subjects, and the standard of reference was manual segmentation generated by nuclear medicine specialists. Figures of merit were the Sørensen-Dice coefficient (DSC) and relative volume difference (RVD). Results. Median DSC ranged between 0.595 and 0.792, median RVD between -22.0% and 87.4%. Click and draw and Nestle's methods achieved the best segmentation accuracy (median DSC, respectively, 0.792 ± 0.178 and 0.762 ± 0.107; median RVD, respectively, -21.6% ± 1270.8% and -32.7% ± 40.0%) and outperformed the other methods by a significant margin. Nestle's method also resulted in a lower dispersion of the data, hence showing stronger inter-patient stability. The accuracy of the two best methods was in agreement with the most recent state-of-the art results. Conclusions. Semi-automated PET delineation methods show potential to assist clinicians in the segmentation of HNC lesions on FDG PET/CT images, although manual refinement may sometimes be needed to obtain clinically acceptable ROIs.

Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features

BACKGROUND

Texture features reflecting tumour heterogeneity enable us to investigate prognostic factors. The R package ComBat can harmonize the quantitative texture features among several positron emission tomography (PET) scanners. We aimed to identify prognostic factors among harmonized PET radiomic features and clinical information from pancreatic cancer patients who underwent curative surgery.

METHODS

Fifty-eight patients underwent preoperative enhanced dynamic computed tomography (CT) scanning and fluorodeoxyglucose PET/CT using four PET scanners. Using LIFEx software, we measured PET radiomic parameters including texture features with higher order and harmonized these PET parameters. For progression-free survival (PFS) and overall survival (OS), we evaluated clinical information, including age, TNM stage, and neural invasion, and the harmonized PET radiomic features based on univariate Cox proportional hazard regression. Next, we analysed the prognostic indices by multivariate Cox proportional hazard regression (1) by using either significant (p < 0.05) or borderline significant (p = 0.05-0.10) indices in the univariate analysis (first multivariate analysis) or (2) by using the selected features with random forest algorithms (second multivariate analysis). Finally, we checked these multivariate results by log-rank test.

RESULTS

Regarding the first multivariate analysis for PFS after univariate analysis, age was the significant prognostic factor (p = 0.020), and MTV and GLCM contrast were borderline significant (p = 0.051 and 0.075, respectively). Regarding the first multivariate analysis of OS, neural invasion, Shape sphericity and GLZLM LZLGE were significant (p = 0.019, 0.042 and 0.0076). In the second multivariate analysis, only MTV was significant (p = 0.046) for PFS, whereas GLZLM LZLGE was significant (p = 0.047), and Shape sphericity was borderline significant (p = 0.088) for OS. In the log-rank test, age, MTV and GLCM contrast were borderline significant for PFS (p = 0.08, 0.06 and 0.07, respectively), whereas neural invasion and Shape sphericity were significant (p = 0.03 and 0.04, respectively), and GLZLM LZLGE was borderline significant for OS (p = 0.08).

CONCLUSIONS

Other than the clinical factors, MTV and GLCM contrast for PFS and Shape sphericity and GLZLM LZLGE for OS may be prognostic PET parameters. A prospective multicentre study with a larger sample size may be warranted.

Relationship of FDG PET/CT Textural Features with the Tumor Microenvironment and Recurrence Risks in Patients with Advanced Gastric Cancers

The relationship between 2-deoxy-2-[18F]fluoro-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) textural features and histopathological findings in gastric cancer has not been fully evaluated. We investigated the relationship between the textural features of primary tumors on FDG PET/CT with histopathological findings and recurrence-free survival (RFS) in patients with advanced gastric cancer (AGC). Fifty-six patients with AGC who underwent FDG PET/CT for staging work-ups were retrospectively enrolled. Conventional parameters and the first- and second-order textural features of AGC were extracted using PET textural analysis. Upon histopathological analysis, along with histopathological classification and staging, the degree of CD4, CD8, and CD163 cell infiltrations and expressions of interleukin-6 and matrix-metalloproteinase-11 (MMP-11) in the primary tumor were assessed. The histopathological classification, Lauren classification, lymph node metastasis, CD8 T lymphocyte and CD163 macrophage infiltrations, and MMP-11 expression were significantly associated with the textural features of AGC. The multivariate survival analysis showed that increased FDG uptake and intra-tumoral metabolic heterogeneity were significantly associated with an increased risk of recurrence after curative surgery. Textural features of AGC on FDG PET/CT showed significant correlations with the inflammatory response in the tumor microenvironment and histopathological features of AGC, and they showed significant prognostic values for predicting RFS.

Different Prognostic Values of Dual-Time-Point FDG PET/CT Imaging Features According to Treatment Modality in Patients with Non-Small Cell Lung Cancer

This study was aimed to investigate whether dual-time-point F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) imaging features had different prognostic values according to the treatment modality in patients with non-small cell lung cancer (NSCLC). We retrospectively reviewed 121 NSCLC patients with surgical resection (surgery group) and 69 NSCLC patients with chemotherapy and/or radiotherapy (CRT group), who underwent pretreatment dual-time-point FDG PET/CT. The maximum standardized uptake value (SUV), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV histogram entropy of primary cancer, and the percent changes in these parameters (Δparameters) were measured. In multivariate analysis, MTV, TLG, and entropy on both early and delayed PET/CT scans were significantly associated with progression-free survival (PFS) in the surgery group, but all Δparameters failed to show a significant association. In the CRT group, TLG on the early PET, maximum SUV on the delayed PET, ΔMTV, and ΔTLG were significant independent predictors for PFS. In the surgery group, patients with high values of MTV, TLG, and entropy had worse survival, whereas, in the CRT group, patients with high values of ΔMTV and ΔTLG had better survival. Dual-time-point FDG PET/CT parameters showed different prognostic values between the surgery and CRT groups of NSCLC patients.

Predicting Survival in Patients with Pancreatic Cancer by Integrating Bone Marrow FDG Uptake and Radiomic Features of Primary Tumor in PET/CT

Simple Summary

FDG uptake of bone marrow (BM) is known to reflect the degree of host inflammatory response to cancer cells and showed significant association with survival in diverse kinds of cancers. The aim of this retrospective study was to evaluate the prognostic significance of FDG uptake of BM and to investigate whether integrating FDG uptake of BM and radiomic features of primary tumors could improve the prediction of overall survival (OS) in patients with pancreatic cancer. In multivariable survival analysis, along with total lesion glycolysis (TLG) and first-order entropy of primary tumor lesions, FDG uptake of BM was an independent predictor of OS. We designed a PET/CT scoring system based on the cumulative scores of tumor factors (TLG and first-order entropy) and host factors (FDG uptake of BM). This scoring system was able to stratify the patients with three distinct prognostic groups independent of clinical stage and treatment modality.

Abstract

The purpose of this study was to evaluate the prognostic significance of FDG uptake of bone marrow (BM SUV) and to investigate its role combined with radiomic features of primary tumors in improving the prediction of overall survival (OS) in patients with pancreatic cancer. We retrospectively enrolled 65 pancreatic cancer patients with staging FDG PET/CT. BM SUV and conventional imaging parameters of primary tumors including total lesion glycolysis (TLG) were measured. First-order and higher-order textural features of primary cancer were extracted using PET textural analysis. Associations of PET/CT parameters of bone marrow (BM) and primary cancer with OS were assessed. BM SUV as well as TLG and first-order entropy of pancreatic cancer were significant independent predictors of OS in multivariable analysis. A PET/CT scoring system based on the cumulative scores of these three independent predictors enabled patient stratification into three distinct prognostic groups. The scoring system yielded a good prognostic stratification based on subgroup analysis irrespective of tumor stage and treatment modality. BM SUV was an independent predictor of OS in pancreatic cancer patients. The PET/CT scoring system that integrated PET/CT parameters of primary tumors and BM can provide prognostic information in pancreatic cancer independent of tumor stage and treatment.

Prognostic value of tumor metabolic imaging phenotype by FDG PET radiomics in HNSCC

OBJECTIVE

Tumor metabolic phenotype can be assessed with integrated image pattern analysis of ¹⁸F-fluoro-deoxy-glucose (FDG) Positron Emission Tomography/Computed Tomography (PET/CT), called radiomics. This study was performed to assess the prognostic value of radiomics PET parameters in head and neck squamous cell carcinoma (HNSCC) patients.

METHODS

¹⁸F-fluoro-deoxy-glucose (FDG) PET/CT data of 215 patients from HNSCC collection free database in The Cancer Imaging Archive (TCIA), and 122 patients in Seoul St. Mary's Hospital with baseline FDG PET/CT for locally advanced HNSCC were reviewed. Data from TCIA database were used as a training cohort, and data from Seoul St. Mary's Hospital as a validation cohort. With the training cohort, primary tumors were segmented by Nestles' adaptive thresholding method. Segmental tumors in PET images were preprocessed using relative resampling of 64 bins. Forty-two PET parameters, including conventional parameters and texture parameters, were measured. Binary groups of homogeneous imaging phenotypes, clustered by K-means method, were compared for overall survival (OS) and disease-free survival (DFS) by log-rank test. Selected individual radiomics parameters were tested along with clinical factors, including age and sex, by Cox-regression test for OS and DFS, and the significant parameters were tested with multivariate analysis. Significant parameters on multivariate analysis were again tested with multivariate analysis in the validation cohort.

RESULTS

A total of 119 patients, 70 from training, and 49 from validation cohort, were included in the study. The median follow-up period was 62 and 52 months for the training and the validation cohort, respectively. In the training cohort. binary groups with different metabolic radiomics phenotypes showed significant difference in OS (p = 0.036), and borderline difference in DFS (p = 0.086). Gray-Level Non-Uniformity for zone (GLNU_GLZLM) was the most significant prognostic factor for both OS (hazard ratio [HR] 3.1, 95% confidence interval [CI] 1.4-7.3, p = 0.008) and DFS (HR 4.5, CI 1.3-16, p = 0.020). Multivariate analysis revealed GLNU_GLZLM as an independent prognostic factor for OS (HR 3.7, 95% CI 1.1-7.5, p = 0.032). GLNU_GLZLM remained as an independent prognostic factor in the validation cohort (HR 14.8. 95% CI 3.3-66, p < 0.001).

CONCLUSIONS

Baseline FDG PET radiomics contain risk information for survival prognosis in HNSCC patients. The metabolic heterogeneity parameter, GLNU_GLZLM, may assist clinicians in patient risk assessment as a feasible prognostic factor.

Metabolic Parameters as Predictors for Progression Free and Overall Survival of Patients with Metastatic Colorectal Cancer

We tested the prognostic relevance of metabolic parameters and their relative changes in patients with metastatic colorectal cancer (mCRC) treated with monoclonal antibody and chemotherapy. SUVmax (standardized uptake volume), SAM (standardized added metabolic activity) and TLG (total lesion glycolysis) are assessed with 18F-fluorodeoxyglucosepositron emission tomography and computed tomography (FDG-PET/CT) to evaluate total metabolic activity of malignant processes. Our purpose was to investigate the change of glucose metabolism in relation to PFS (progression free survival) and OS (overall survival). Fifty-three patients with mCRC with at least one measurable liver metastasis were included in this prospective, multi-center, early exploratory study. All patients were treated with first-line chemotherapy and targeted therapy. Metabolic parameters, like SUVmax, SAM, normalized SAM (NSAM) and TLG were assessed by FDG-PET/CT, carried out at baseline (scan-1) and after two therapeutic cycle (scan-2). Our results suggested neither SUVmax nor TLG have such prognostic value as NSAM in liver metastases of colorectal cancer. The parameters after the two cycles of chemotherapy proved to be better predictors of the clinical outcome. NSAM after two cycles of treatment has a statistically significant predictive value on OS, while SAM was predictive to the PFS. The follow up normalized SAM after 2 cycles of first line oncotherapy was demonstrated to be useful as prognostic biomarkers for OS in metastatic colorectal cancer. We should introduce this measurement in metastatic colorectal cancer if there is at least one metastasis in the liver.

Tumor immune profiles noninvasively estimated by FDG PET with deep learning correlate with immunotherapy response in lung adenocarcinoma

Rationale: The clinical application of biomarkers reflecting tumor immune microenvironment is hurdled by the invasiveness of obtaining tissues despite its importance in immunotherapy. We developed a deep learning-based biomarker which noninvasively estimates a tumor immune profile with fluorodeoxyglucose positron emission tomography (FDG-PET) in lung adenocarcinoma (LUAD).

Methods: A deep learning model to predict cytolytic activity score (CytAct) using semi-automatically segmented tumors on FDG-PET trained by a publicly available dataset paired with tissue RNA sequencing (n = 93). This model was validated in two independent cohorts of LUAD: SNUH (n = 43) and The Cancer Genome Atlas (TCGA) cohort (n = 16). The model was applied to the immune checkpoint blockade (ICB) cohort, which consists of patients with metastatic LUAD who underwent ICB treatment (n = 29).

Results: The predicted CytAct showed a positive correlation with CytAct of RNA sequencing in validation cohorts (Spearman rho = 0.32, p = 0.04 in SNUH cohort; spearman rho = 0.47, p = 0.07 in TCGA cohort). In ICB cohort, the higher predicted CytAct of individual lesion was associated with more decrement in tumor size after ICB treatment (Spearman rho = -0.54, p < 0.001). Higher minimum predicted CytAct in each patient associated with significantly prolonged progression free survival and overall survival (Hazard ratio 0.25, p = 0.001 and 0.18, p = 0.004, respectively). In patients with multiple lesions, ICB responders had significantly lower variance of predicted CytActs (p = 0.005).

Conclusion: The deep learning model that predicts CytAct using FDG-PET of LUAD was validated in independent cohorts. Our approach may be used to noninvasively assess an immune profile and predict outcomes of LUAD patients treated with ICB.

Selected PET radiomic features remain the same

Purpose

We investigated whether PET radiomic features are affected by differences in the scanner, scan protocol, and lesion location using ¹⁸F-FDG PET/CT and PET/MR scans.

Results

SUV, TMR, skewness, kurtosis, entropy, and homogeneity strongly correlated between PET/CT and PET/MR images. SUVs were significantly higher on PET/MR_{0-2 min} and PET/MR_{0-10 min} than on PET/CT in gynecological cancer (p = 0.008 and 0.008, respectively), whereas no significant difference was observed between PET/CT, PET/MR_{0–2 min}, and PET/MR_{0–10 min} images in oral cavity/oropharyngeal cancer. TMRs on PET/CT, PET/MR_{0–2 min}, and PET/MR_{0–10 min} increased in this order in gynecological cancer and oral cavity/oropharyngeal cancer. In contrast to conventional and histogram indices, 4 textural features (entropy, homogeneity, SRE, and LRE) were not significantly different between PET/CT, PET/MR_{0–2 min}, and PET/MR_{0–10 min} images.

Conclusions

¹⁸F-FDG PET radiomic features strongly correlated between PET/CT and PET/MR images. Dixon-based attenuation correction on PET/MR images underestimated tumor tracer uptake more significantly in oral cavity/oropharyngeal cancer than in gynecological cancer. ¹⁸F-FDG PET textural features were affected less by differences in the scanner and scan protocol than conventional and histogram features, possibly due to the resampling process using a medium bin width.

Methods

Eight patients with gynecological cancer and 7 with oral cavity/oropharyngeal cancer underwent a whole-body ¹⁸F-FDG PET/CT scan and regional PET/MR scan in one day. PET/MR scans were performed for 10 minutes in the list mode, and PET/CT and 0–2 min and 0–10 min PET/MR images were reconstructed. The standardized uptake value (SUV), tumor-to-muscle SUV ratio (TMR), skewness, kurtosis, entropy, homogeneity, short-run emphasis (SRE), and long-run emphasis (LRE) were compared between PET/CT, PET/MR_{0-2 min}, and PET/MR_{0-10 min} images.

Advanced imaging to predict response to chemotherapy in colorectal liver metastases - a systematic review

BACKGROUND

The assessment of colorectal liver metastases (CRLM) after treatment with chemotherapy is challenging due to morphological and/or functional change without changes in size. The aim of this review was to assess the value of FDG-PET, FDG-PET-CT, CT and MRI in predicting response to chemotherapy in CRLM.

METHODS

A systematic review was undertaken based on PRISMA statement. PubMed and Embase were searched up to October 2016 for studies on the accuracy of PET, PET-CT, CT and MRI in predicting RECIST or metabolic response to chemotherapy and/or survival in patients with CRLM. Articles evaluating the assessment of response after chemotherapy were excluded.

RESULTS

Sixteen studies met the inclusion criteria and were included for further analysis. Study results were available for 6 studies for FDG-PET(-CT), 6 studies for CT and 9 studies for MRI. Generally, features predicting RECIST or metabolic response often predicted shorter survival. The ADC (apparent diffusion coefficient, on MRI) seems to be the most promising predictor of response and survival. In CT-related studies, few attenuation-related parameters and texture features show promising results. In FDG-PET(-CT), findings were ambiguous.

CONCLUSION

Radiological data on the prediction of response to chemotherapy for CRLM is relatively sparse and heterogeneous. Despite that, a promising parameter might be ADC. Second, there seems to be a seemingly counterintuitive correlation between parameters that predict a good response and also predict poor survival.

Quantification and reduction of respiratory induced artifacts in positron emission tomography/computed tomography using the time-of-flight technique

OBJECTIVE

The aim of this study was to investigate the impact of time-of-flight (TOF) on quantification and reduction of respiratory artifacts.

PATIENTS AND METHODS

The National Electrical Manufacturers Association phantom was used for optimization of reconstruction parameters. Twenty seven patients with lesions located in the diaphragmatic region were evaluated. The PET images were retrospectively reconstructed using non-TOF (routine protocol in our department) and TOF algorithms with different reconstruction parameters. Maximum standardized uptake value, estimated maximum tumor diameter, coefficient of variation, signal-to-noise ratio, and lesion-to-background-ratio were also evaluated.

RESULTS

On the basis of phantom experiments, TOF algorithms with two iterations, 18 subsets, and 5.4 mm and 6.4 mm postsmoothing filter reduced the noise by 3.1 and 12.6% in phantom with 2 : 1 activity ratio, and 3.0 and 13.1% in phantom with 4 : 1 activity ratio. The TOF algorithm with two iterations, 18 subsets, and 6.4 mm postsmoothing filter had the highest signal-to-noise value, and was selected as the optimal TOF reconstruction. Mean relative difference for signal-to-noise between non-TOF and optimal TOF in phantom with 2 : 1 and 4 : 1 activity ratio were 11.6 and 18.7%, respectively. In clinical data, the mean relative difference for estimated maximum tumor diameter and maximum standardized uptake value between routine protocol and optimal TOF algorithm were -6.3% (range: -20.4 to -0.6%) and 13.2% (range: 0.3-57.6%), respectively.

CONCLUSION

Integration of TOF in reconstruction algorithm remarkably improved the white band artifact in the diaphragmatic region. This technique affected the quantification accuracy and resulted in smaller tumor size and higher standardized uptake value in tumors located in/near the diaphragmatic region.

Impact of partial-volume correction in oncological PET studies: a systematic review and meta-analysis

Purpose

Positron-emission tomography can be useful in oncology for diagnosis, (re)staging, determining prognosis, and response assessment. However, partial-volume effects hamper accurate quantification of lesions <2–3× the PET system’s spatial resolution, and the clinical impact of this is not evident. This systematic review provides an up-to-date overview of studies investigating the impact of partial-volume correction (PVC) in oncological PET studies.

Methods

We searched in PubMed and Embase databases according to the PRISMA statement, including studies from inception till May 9, 2016. Two reviewers independently screened all abstracts and eligible full-text articles and performed quality assessment according to QUADAS-2 and QUIPS criteria. For a set of similar diagnostic studies, we statistically pooled the results using bivariate meta-regression.

Results

Thirty-one studies were eligible for inclusion. Overall, study quality was good. For diagnosis and nodal staging, PVC yielded a strong trend of increased sensitivity at expense of specificity. Meta-analysis of six studies investigating diagnosis of pulmonary nodules (679 lesions) showed no significant change in diagnostic accuracy after PVC (p = 0.222). Prognostication was not improved for non-small cell lung cancer and esophageal cancer, whereas it did improve for head and neck cancer. Response assessment was not improved by PVC for (locally advanced) breast cancer or rectal cancer, and it worsened in metastatic colorectal cancer.

Conclusions

The accumulated evidence to date does not support routine application of PVC in standard clinical PET practice. Consensus on the preferred PVC methodology in oncological PET should be reached. Partial-volume-corrected data should be used as adjuncts to, but not yet replacement for, uncorrected data.

Electronic supplementary material

The online version of this article (doi:10.1007/s00259-017-3775-4) contains supplementary material, which is available to authorized users.

Antiangiogenic therapy for refractory colorectal cancer: current options and future strategies

Even though significant improvements in the treatment of colorectal cancer (CRC) have been made in recent years, survival rates for metastatic colorectal cancer (mCRC) are poor. Effective treatment options for metastatic colorectal cancer remain limited, and new therapeutic strategies are desperately needed. Several tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) that target angiogenesis, a critical process for facilitating tumor cell growth, invasion, and metastasis, are either approved or in clinical development for the treatment of mCRC. Many of these agents have shown efficacy in mCRC, both as single agents and in combination with standard chemotherapy regimens. However, there is a need for predictive markers of response to identify those patients most likely to benefit from antiangiogenic therapy, and, to date, no markers of this type have been validated in patients. Additionally, because antiangiogenic agents typically cause cytostatic as opposed to cytotoxic antitumor effects, it is important to determine the best strategies for evaluating therapeutic response in mCRC to ensure maximum clinical benefit. In this review, we summarize the efficacy and tolerability of approved and investigational antiangiogenic agents for the treatment of mCRC. We also discuss potential markers of response to antiangiogenic agents and how these markers, along with appropriate endpoint selection, can improve clinical trial design.

Monitoring metabolic response using FDG PET-CT during targeted therapy for metastatic colorectal cancer

Introduction

The introduction of targeted drugs has had a significant impact on the approach to assessing tumour response. These drugs often induce a rapid cytostatic effect associated with a less pronounced and slower tumoural volume reduction, thereby impairing the correlation between the absence of tumour shrinkage and the patient’s unlikelihood of benefit. The aim of the study was to assess the predictive value of early metabolic response (mR) evaluation after one cycle, and its interlesional heterogeneity to a later metabolic and morphological response assessment performed after three cycles in metastatic colorectal cancer (mCRC) patients treated with combined sorafenib and capecitabine.

Methods

This substudy was performed within the framework of a wider prospective multicenter study on the predictive value of early FDG PET-CT response assessment (SoMore study). A lesion-based response analysis was performed, including all measurable lesions identified on the baseline PET. On a per-patient basis, a descriptive 4-class response categorization was applied based upon the presence and proportion of non-responding lesions. For dichotomic response comparison, all patients with at least one resistant lesion were classified as non-responding.

Results

On baseline FDG PET-CT, 124 measurable “target” lesions were identified in 38 patients. Early mR assessments showed 18 patients (47 %) without treatment resistant lesions and 12 patients (32 %) with interlesional response heterogeneity. The NPV and PPV of early mR were 85 % (35/41) and 84 % (70/83), respectively, on a per-lesion basis and 95 % (19/20) and 72 % (13/18), respectively, on a dichotomized per-patient basis.

Conclusions

Early mR assessment performed after one cycle of sorafenib-capecitabine in mCRC is highly predictive of non-response at a standard response assessment time. The high NPV (95 %) of early mR could be useful as the basis for early treatment discontinuation or adaptation to spare patients from exposure to non-effective drugs.

A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

Positron Emission Tomography for the Response Evaluation following Treatment with Chemotherapy in Patients Affected by Colorectal Liver Metastases: A Selected Review

The aim of the present paper is to review the scientific literature concerning the usefulness of (18)F-FDG PET/CT in the evaluation of response to chemotherapy in patients affected by liver metastases from colorectal cancer. Material and Methods. Studies were identified by searching PubMed electronic databases. Both prospective and retrospective studies were included. Information regarding the figure of merit of PET for the evaluation of therapy response was extracted and analyzed. Results. Existing data suggests that (18)F-FDG PET/CT may have an outstanding role in evaluating the response. The sensitivity of PET in detecting therapy response seems to be greater than conventional imaging (CT and MRI). PET/CT response is strictly related to better overall survival and progression-free survival. Conclusions. PET/CT is more than a promising technique to assess the response to chemotherapy in colorectal and liver metastases. However, to be fully validated, this examination needs further studies by recruiting more patients.

FDG-PET Response Prediction in Pediatric Hodgkin's Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value

Background: In pediatric Hodgkin’s lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); Methods: One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; Results: All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Conclusions: Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

PET scans as a predictive marker of survival in advanced colorectal cancer

BACKGROUND

The clinical utility of fluorodeoxyglucose (FDG)-positron emission tomography (PET) scan in predicting the outcome of patients with metastatic colorectal cancer (mCRC) has not been well studied. We hypothesized that standardized uptake value (SUV) in FDG-PET scans after treatment predicts outcomes among patients with mCRC.

PATIENTS AND METHODS

We retrospectively reviewed mCRC patients who had FDG-PET scans before their treatment and measured their SUV on follow-up imaging at the Karmanos Cancer Institute. Primary end points of time to progression (TTP) and overall survival (OS) were compared in 2 groups: follow-up (posttreatment) SUV of 0 versus > 0.

RESULTS

The study population consisted of 44 patients (median age of 58.1 years). Forty (91%) of the patients were treated first-line, 34 (77%) received an oxaliplatin-based regimen, and 7 (16%) received an irinotecan-based regimen. Thirty-four (77%) patients received concurrent bevacizumab. Median pretreatment SUV was 9.2 (range, 1.7-46.3), and median posttreatment SUV (in n = 41) was 4.0 (range, 0-14). The median percent change in SUV was -68.5% (range, -9.2% to -100%). The median time interval between scans was 2.6 months. There was no statistically significant difference noted between metabolic responders and nonresponders with regard to TTP and OS. However, patients with a posttreatment SUV of 0 had significantly longer OS than those with posttreatment SUV of > 0 (median, 42 vs. 25.2 months, respectively), and slightly longer TTP (median, 8.2 vs. 6.9 months, respectively).

CONCLUSION

Systemic therapy significantly decreased SUV on follow-up PET scans in advanced colorectal cancer patients. Absence of FDG uptake on follow-up PET scans was associated with markedly longer OS and slightly longer TTP.

Role of PET quantitation in the monitoring of cancer response to treatment: Review of approaches and human clinical trials

Positron emission tomography (PET) measures of cancer metabolism and cellular proliferation are increasingly being studied as markers of cancer response to treatment, with the goal of using them as predictors of patient therapeutic outcomes - i.e., as surrogate outcome measures. The primary PET radiotracers thus far used for monitoring response of cancer to treatment are ¹⁸F-fluorodeoxyglucose (FDG) for studying abnormal energy metabolism and ¹⁸F-fluorothymidine (FLT) for examining cell proliferation. Both FDG and FLT PET quantitation of cancer response to treatment have been found to correlate with patient outcomes, mostly in single-center studies. The aim of this review is to summarize the impact of commonly selected PET quantitation methods on the ability of PET measures to quantitate cancer response to treatment. An understanding of the biochemistry and kinetics of FDG and FLT uptake and knowledge of the expected tracer uptake by cancerous processes relative to background uptake are required to select appropriate PET quantitation methods for trials testing for correlations between PET measures and patient outcome. PET measures may eventually serve as predictive biomarkers capable of guiding individualized treatment and improving patient outcomes and quality of life by early identification of ineffective therapies. PET can also potentially identify patients who would be good candidates for molecularly targeted drugs and monitor response to these personalized therapies.

Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer

Background

There is currently little support to understand which pathological factors led to differences in tumor texture as measured from FDG PET/CT images. We studied whether tumor heterogeneity measured using texture analysis in FDG-PET/CT images is correlated with pathological prognostic factors in invasive breast cancer.

Methods

Fifty-four patients with locally advanced breast cancer who had an initial FDG-PET/CT were retrospectively included. In addition to SUVmax, three robust textural indices extracted from 3D matrices: High-Gray-level Run Emphasis (HGRE), Entropy and Homogeneity were studied. Univariate and multivariate logistic regression was used to identify PET parameters associated with poor prognosis pathological factors: hormone receptor negativity, presence of HER-2 and triple negative phenotype. Receiver operating characteristic (ROC) curves and the (AUC) analysis, and reclassification measures, were performed in order to evaluate the performance of combining texture analysis and SUVmax for characterizing breast tumors.

Results

Tumor heterogeneity, measured with HGRE, was higher in negative estrogen receptor (p = 0.039) and negative progesterone receptor tumors (p = 0.036), and in Scarff-Bloom-Richardson grade 3 tumors (p = 0.047). None of the PET indices could identify HER-2 positive tumors. Only SUVmax was positively correlated with Ki-67 (p<0.0004). Triple negative breast cancer (TNBC) exhibited higher SUVmax (Odd Ratio = 1.22, 95%CI [1.06–1.39],p = 0.004), lower Homogeneity (OR = 3.57[0.98–12.5],p = 0.05) and higher HGRE (OR = 8.06[1.88–34.51],p = 0.005) than non-TNBC. Multivariate analysis showed that HGRE remained associated with TNBC (OR = 5.27[1.12–1.38],p = 0.03) after adjustment for SUVmax. Combining SUVmax and HGRE yielded in higher area under the ROC curves (AUC) than SUVmax for identifying TNBC: AUC =  0.83 and 0.77, respectively. Probability of correct classification also increased in 77% (10/13) of TNBC and 71% (29/41) of non-TNBC (p = 0.003), when combining SUVmax and HGRE.

Conclusions

Tumor heterogeneity measured on FDG-PET/CT was higher in invasive breast cancer with poor prognosis pathological factors. Texture analysis might be used, in addition to SUVmax, as a new tool to assess invasive breast cancer aggressiveness.

Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis

Texture indices are of growing interest for tumor characterization in (18)F-FDG PET. Yet, on the basis of results published in the literature so far, it is unclear which indices should be used, what they represent, and how they relate to conventional indices such as standardized uptake values (SUVs), metabolic volume (MV), and total lesion glycolysis (TLG). We investigated in detail 31 texture indices, 5 first-order statistics (histogram indices) derived from the gray-level histogram of the tumor region, and their relationship with SUV, MV, and TLG in 3 different tumor types.

METHODS

Three patient groups corresponding to 3 cancer types at baseline were studied independently: patients with metastatic colorectal cancer (72 lesions), non-small cell lung cancer (24 lesions), and breast cancer (54 lesions). Thirty-one texture indices were studied in addition to SUVs, MV, and TLG, and 5 indices extracted from histogram analysis were also investigated. The relationships between indices were studied as well as the robustness of the various texture indices with respect to the parameters involved in the calculation method (sampling schemes and tumor volume of interest).

RESULTS

Regardless of the patient group, many indices were highly correlated (Pearson correlation coefficient |r| ≥ 0.80), making it desirable to focus on only a few uncorrelated indices. Three histogram indices were highly correlated with SUVs (|r| ≥ 0.84). Four texture indices were highly correlated with MV, and none was highly correlated with SUVs (|r| ≤ 0.55). The resampling formula used to calculate texture indices had a substantial impact, and resampling using at least 32 discrete values should be used for texture indices calculation. The texture indices change as a function of the segmentation method was higher than that of peak and maximum SUVs but less than mean SUV for 5 texture indices and was larger than that of MV for 14 texture indices and for the 5 histogram indices. All these results were extremely consistent across the 3 tumor types and explained many of the observations reported in the literature so far.

CONCLUSION

None of the histogram indices and only 17 of 31 texture indices were robust with respect to the tumor-segmentation method. An appropriate resampling formula with at least 32 gray levels should be used to avoid introducing a misleading relationship between texture indices and SUV. Some texture indices are highly correlated or strongly correlate with MV whatever the tumor type. Such correlation should be accounted for when interpreting the usefulness of texture indices for tumor characterization, which might call for systematic multivariate analyses.

Effects of ROI Placement on PET-Based Assessment of Tumor Response to Therapy

Purpose. Quantitative PET response assessment during therapy requires regions of interest (ROI). Commonly, a fixed-size ROI is placed at the maximum uptake point in the pretreatment study. For intratreatment, the ROI is placed either at the maximum uptake point (ROI_peak) or at the same location as the pretreatment ROI (ROI_same). We have evaluated the effects of the ROI placement on response assessment. Methods. PET scans of 15 head and neck cancer patients were used to evaluate the effects of the two ROI methods on response assessment. Results. The average intratreatment ROI_peak uptake was 13.4% higher than the ROI_same uptake (range −14% to 38%). The average relative change in ROI_peak uptake was 7.9% lower than ROI_same uptake (range −5% to 36%), resulting in ambiguous tumour classification in 19% of the tumours. Conclusion. Quantitative PET response assessment using a fixed-size ROI is sensitive the ROI placement. The difference between ROI_peak and ROI_same could be substantial resulting in ambiguous response assessment. Although the fixed-size ROI is simple to implement, it is also prone to the limitations and should be used with caution. Clinical trial data are necessary to establish reliable thresholds for fixed-size ROI techniques and to evaluate their efficacy for response assessment.