Evolving role of molecular imaging with PET in detecting and characterizing heterogeneity of cancer tissue at the primary and metastatic sites, a plausible explanation for failed attempts to cure malignant disorders

Models using comprehensive, lesion-level, longitudinal [68Ga]Ga-DOTA-TATE PET-derived features lead to superior outcome prediction in neuroendocrine tumor patients treated with [177Lu]Lu-DOTA-TATE

PURPOSE

Somatostatin receptor (SSTR) imaging features are predictive of treatment outcome for neuroendocrine tumor (NET) patients receiving peptide receptor radionuclide therapy (PRRT). However, comprehensive (all metastatic lesions), longitudinal (temporal variation), and lesion-level measured features have never been explored. Such features allow for capturing the heterogeneity in disease response to treatment. Furthermore, models combining these features are lacking. In this work we evaluated the predictive power of comprehensive, longitudinal, lesion-level 68GA-SSTR-PET features combined with a multivariate linear regression (MLR) model.

METHODS

This retrospective study enrolled NET patients treated with [177Lu]Lu-DOTA-TATE and imaged with [68Ga]Ga-DOTA-TATE at baseline and post-therapy. All lesions were segmented, anatomically labeled, and longitudinally matched. Lesion-level uptake and variation in uptake were measured. Patient-level features were engineered and selected for modeling of progression-free survival (PFS). The model was validated via concordance index, patient classification (ROC analysis), and survival analysis (Kaplan-Meier and Cox proportional hazards). The MLR was benchmarked against single feature predictions.

RESULTS

Thirty-six NET patients were enrolled and stratified into poor and good responders (PFS ≥ 25 months). Four patient-level features were selected, the MLR concordance index was 0.826, and the AUC was 0.88 (0.85 specificity, 0.81 sensitivity). Survival analysis led to significant patient stratification (p<.001) and hazard ratio (3⨯10-5). Lastly, in a benchmark study, the MLR modeling approach outperformed all the single feature predictors.

CONCLUSION

Comprehensive, lesion-level, longitudinal 68GA-SSTR-PET analysis, combined with MLR modeling, leads to excellent predictions of PRRT outcome in NET patients, outperforming non-comprehensive, patient-level, and single time-point feature predictions.

MESSAGE

Neuroendocrine tumor, peptide receptor radionuclide therapy, Somatostatin Receptor Imaging, Outcome Prediction, Treatment Response Assessment.

Role of Textural Analysis of Pretreatment 18F Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Response Prediction in Esophageal Carcinoma Patients

Introduction

Positron emission tomography/computed tomography (PET/CT) is routinely used for staging, response assessment, and surveillance in esophageal carcinoma patients. The aim of this study was to investigate whether textural features of pretreatment 18F-fluorodeoxyglucose (18F-FDG) PET/CT images can contribute to prognosis prediction in carcinoma oesophagus patients.

Materials and Methods

This is a retrospective study of 30 diagnosed carcinoma esophagus patients. These patients underwent pretreatment 18F-FDG PET/CT for staging. The images were processed in a commercially available textural analysis software. Region of interest was drawn over primary tumor with a 40% threshold and was processed further to derive 92 textural and radiomic parameters. These parameters were then compared between progression group and nonprogression group. The original dataset was subject separately to receiver operating curve analysis. Receiver operating characteristic (ROC) curves were used to identify the cutoff values for textural features with a P < 0.05 for statistical significance. Feature selection was done with principal component analysis. The selected features of each evaluator were subject to 4 machine-learning algorithms. The highest area under the curve (AUC) values was selected for 10 features.

Results

A retrospective study of 30 primary carcinoma esophagus patients was done. Patients were followed up after chemo-radiotherapy and they underwent follow-up PET/CT. On the basis of their response, patients were divided into progression group and nonprogression group. Among them, 15 patients showed disease progression and 15 patients were in the nonprogression group. Ten textural analysis parameters turned out to be significant in the prediction of disease progression. Cutoff values were calculated for these parameters according to the ROC curves, GLZLM_long zone emphasis (Gray Level Zone Length Matrix)_long zone emphasis (44.9), GLZLM_low gray level zone emphasis (0.006), GLZLM_short zone low gray level emphasis (0.0032), GLZLM_long zone low gray level emphasis (0.185), GLRLM_long run emphasis (Gray Level Run Length Matrix) (1.31), GLRLM_low gray level run emphasis (0.0058), GLRLM_short run low gray level emphasis (0.005496), GLRLM_long run low gray level emphasis (0.00727), NGLDM_Busyness (Neighborhood Gray Level Difference Matrix) (0.75), and gray level co-occurrence matrix_homogeneity (0.37). Feature selection by principal components analysis and feature classification by the K-nearest neighbor machine-learning model using independent training and test samples yielded the overall highest AUC.

Conclusions

Textural analysis parameters could provide prognostic information in carcinoma esophagus patients. Larger multicenter studies are needed for better clinical prognostication of these parameters.

Spatial and temporal heterogeneity of digestive neuroendocrine neoplasms

Neuroendocrine neoplasms (NENs) are initially monoclonal neoplasms that progressively become polyclonal, with very different genotypic and phenotypic characteristics leading to biological differences, including the Ki-67 proliferation index, morphology, or sensitivity to treatments. Whereas inter-patient heterogeneity has been well described, intra-tumor heterogeneity has been little studied. However, NENs present a high degree of heterogeneity, both spatially within the same location or between different lesions, and through time. This can be explained by the emergence of tumor subclones with different behaviors. These subpopulations can be distinguished by the Ki-67 index, but also by the expression of hormonal markers or by differences in the intensity of uptake on metabolic imaging, such as ⁶⁸Ga-somatostatin receptor and Fluorine-18 fluorodeoxyglucose positron emission tomography. As these features are directly related to prognosis, it seems mandatory to move toward a standardized, improved selection of the tumor areas to be studied to be as predictive as possible. The temporal evolution of NENs frequently leads to changes in tumor grade over time, with impact on prognosis and therapeutic decision-making. However, there is no recommendation regarding systematic biopsy of NEN recurrence or progression, and which lesion to sample. This review aims to summarize the current state of knowledge, the main hypotheses, and the main implications regarding intra-tumor spatial and temporal heterogeneity in digestive NENs.

Utility of pre-treatment 18 F-fluorodeoxyglucose PET radiomic analysis in assessing nodal involvement in cervical cancer

OBJECTIVE

Intratumor heterogeneity has prognostic value in cervical cancer, which can be depicted on 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (PET/CT) and then quantitatively characterized by texture features. This study aimed to evaluate the discriminative performance and predictive ability of the texture features in determining lymph node involvement in cervical cancer.

METHODS

A total of 101 patients with newly diagnosed cervical cancer, who underwent pre-treatment whole-body 18 F-FDG PET/CT imaging were retrospectively recruited. Patients were categorized based on their nodal status. Thirty-five radiomic features together with the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary cervical tumors were extracted. Conventional indices were used to build logistic regression model and texture features were used to build random forest model. The performances for differentiating nodal status were assessed by receiver operating characteristic analysis.

RESULTS

Conventional PET indices were significantly higher in patients with nodal involvement compared to those without: SUVmax = 14.22 vs. 10.05; MTV = 57.02 vs. 28.73; TLG = 492.8 vs. 188.8 ( P  < 0.05). Nineteen radiomic features describing regional heterogeneity were significantly different between nodal involvements. Area under the curves of the models with conventional indices and PET texture features for discriminating nodal status were 0.72 and 0.76, respectively.

CONCLUSION

PET-derived radiomic features had moderate performance in discriminating nodal involvement in cervical cancer; and they did not outperform model based on conventional indices.

Rare Case of Neuroendocrine Tumor of Common Bile Duct Identified With Somatostatin Receptor But Not With Glucose Transporter Imaging

ABSTRACT

Neuroendocrine tumors (NETs) are heterogeneous group of tumors arising from enterochromaffin cells. Neuroendocrine tumors are most commonly found in bowel and pancreatic tissue. Because of paucity of enterochromaffin cells in biliary tract, NETs of bile duct are very rare. Most of the neoplasms in the extrahepatic bile duct are adenocarcinomas; only 0.2% to 0.3% of NETs arise from the bile duct. Cases reported in the literature of biliary carcinoid are diagnosed postoperatively on histopathologic evaluation. We hereby demonstrate a rare presentation of CBD NET identified preoperatively on somatostatin receptor but not on glucose transporter imaging, confirmed by histopathology and immunohistochemistry to be grade 2 NET (Ki-67, 20%).

Impact of Interobserver Variability in Manual Segmentation of Non-Small Cell Lung Cancer (NSCLC) Applying Low-Rank Radiomic Representation on Computed Tomography

Simple Summary

Discovery of predictive and prognostic radiomic features in cancer is currently of great interest to the radiologic and oncologic community. Tumor phenotypic and prognostic information can be obtained by extracting features on tumor segmentations, and it is typically imaging analysts, physician trainees, and attending physicians who provide these labeled datasets for analysis. The potential impact of level and type of specialty training on interobserver variability in manual segmentation of NSCLC was examined. Although there was some variability in segmentation between readers, the subsequently extracted radiomic features were overall well correlated. High fidelity radiomic feature extraction relies on accurate feature extraction from imaging that produce robust prognostic and predictive radiomic NSCLC biomarkers. This study concludes that this goal can be obtained using segmenters of different levels of training and clinical experience.

Abstract

This study tackles interobserver variability with respect to specialty training in manual segmentation of non-small cell lung cancer (NSCLC). Four readers included for segmentation are: a data scientist (BY), a medical student (LS), a radiology trainee (MH), and a specialty-trained radiologist (SK) for a total of 293 patients from two publicly available databases. Sørensen–Dice (SD) coefficients and low rank Pearson correlation coefficients (CC) of 429 radiomics were calculated to assess interobserver variability. Cox proportional hazard (CPH) models and Kaplan-Meier (KM) curves of overall survival (OS) prediction for each dataset were also generated. SD and CC for segmentations demonstrated high similarities, yielding, SD: 0.79 and CC: 0.92 (BY-SK), SD: 0.81 and CC: 0.83 (LS-SK), and SD: 0.84 and CC: 0.91 (MH-SK) in average for both databases, respectively. OS through the maximal CPH model for the two datasets yielded c-statistics of 0.7 (95% CI) and 0.69 (95% CI), while adding radiomic and clinical variables (sex, stage/morphological status, and histology) together. KM curves also showed significant discrimination between high- and low-risk patients (p-value < 0.005). This supports that readers’ level of training and clinical experience may not significantly influence the ability to extract accurate radiomic features for NSCLC on CT. This potentially allows flexibility in the training required to produce robust prognostic imaging biomarkers for potential clinical translation.

The exploration of quantitative intra-tumoral metabolic heterogeneity in dual-time 18F-FDG PET/CT of pancreatic cancer

PURPOSE

We aimed to analyze the change of quantitative intra-tumoral metabolic heterogeneity consisting of texture features and conventional metabolic parameters of pancreatic cancer (PC) in dual-time 2-deoxy-2(¹⁸F) fluoro-D-glucose (¹⁸F-FDG) positron emission tomography-computed tomography (PET/CT).

METHODS

A retrospective analysis was conducted considering the texture features and conventional metabolic parameters in dual-time ¹⁸F-FDG PET/CT scans of PC patients. Features were extracted based on spatial distribution of ¹⁸F-FDG uptake in image. Firstly, the texture features and the conventional metabolic parameters of the delayed scan were both compared with that of the early scan. Statistically different data was defined among them. Secondly, the study evaluated the correlations between retention index (RI) of the texture features and the conventional metabolic parameters. Finally, the variation of texture features in dual-time PET/CT of resectable PC patients and unresectable PC patients was calculated separately.

RESULTS

In total, 183 PC patients were analyzed retrospectively in this research. The conventional metabolic parameters were all statistically different between the early and delayed scans except for metabolic tumor volume (MTV). In the radiomics, there were 59 textural features. Nineteen of 59 texture features were statistically different between the early and delayed scans. Features that were more than 10% different during two scans were observed in a substantial percentage of patients. Weak correlations were only found between MTV, TLG (Total lesion glycolysis), SUVpeak and the RI of some texture features in early or delayed scans. There were obviously fewer features with significant difference in resectable PC group than in unresectable PC group. Most features showing the difference in unresectable group while no significant difference in resectable group.

CONCLUSIONS

This study investigated the change and inner correlations of quantitative tumoral metabolic heterogeneity in the dual-time ¹⁸F-FDG-PET/CT scan of PC patients. Some features displayed the difference between dual-time scans. Conventional metabolic parameters were weakly related to the change of texture feature. The change of texture feature in resectable PC group was different from that in unresectable PC group. This result is potential to provide more information for the image evaluation of PC.

The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer

Evolutionary game theory mathematically conceptualizes and analyzes biological interactions where one's fitness not only depends on one's own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer's eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. Moreover, we discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with evolutionary game theory has medically useful implications that can inform and create a lockstep between empirical findings and mathematical modeling. We suggest that cancer progression is an evolutionary competition between different cell types and therefore needs to be viewed as an evolutionary game.

CT-Based Hand-crafted Radiomic Signatures Can Predict PD-L1 Expression Levels in Non-small Cell Lung Cancer: a Two-Center Study

Here, we used pre-treatment CT images to develop and evaluate a radiomic signature that can predict the expression of programmed death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC). We then verified its predictive performance by cross-referencing its results with clinical characteristics. This two-center retrospective analysis included 125 patients with histologically confirmed NSCLC. A total of 1287 hand-crafted radiomic features were observed from manually determined tumor regions. Valuable features were then selected with a ridge regression-based recursive feature elimination approach. Machine learning-based prediction models were then built from this and compared each other. The final radiomic signature was built using logistic regression in the primary cohort, and then tested in a validation cohort. Finally, we compared the efficacy of the radiomic signature to the clinical model and the radiomic-clinical nomogram. Among the 125 patients, 89 were classified as having PD-L1 positive expression. However, there was no significant difference in PD-L1 expression levels determined by clinical characteristics (P = 0.109-0.955). Upon selecting 9 radiomic features, we found that the logistic regression-based prediction model performed the best (AUC = 0.96, P < 0.001). In the external cohort, our radiomic signature showed an AUC of 0.85, which outperformed both the clinical model (AUC = 0.38, P < 0.001) and the radiomics-nomogram model (AUC = 0.61, P < 0.001). Our CT-based hand-crafted radiomic signature model can effectively predict PD-L1 expression levels, providing a noninvasive means of better understanding PD-L1 expression in patients with NSCLC.

Preoperative prediction of regional lymph node metastasis of colorectal cancer based on 18F-FDG PET/CT and machine learning

PURPOSE

To establish and validate a regional lymph node (LN) metastasis prediction model of colorectal cancer (CRC) based on 18F-FDG PET/CT and radiomic features using machine-learning methods.

METHODS

A total of 199 colorectal cancer patients underwent pre-therapy diagnostic 18F-FDG PET/CT scans and CRC radical surgery. The Chang-Gung Image Texture Analysis toolbox (CGITA) was used to extract 70 PET radiomic features reflecting 18F-FDG uptake heterogeneity of tumors. The least absolute shrinkage and selection operator (LASSO) algorithm was used to select radiomic features and develop a radiomic signature score (Rad-score). The training set was used to establish five machine-learning prediction models and the test set was used to test the efficacy of the models. The effectiveness of the models was compared by ROC analysis.

RESULTS

The CRC patients were divided into a training set (n = 144) and a test set (n = 55). Two radiomic features were selected to build the Rad-score. Five machine-learning algorithms including logistic regression, support vector machine (SVM), random forest, neural network and eXtreme gradient boosting (XGBoost) were used to established models. Among the five machine-learning models, logistic regression (AUC 0.866, 95% CI 0.808-0.925) and XGBoost (AUC 0.903, 95% CI 0.855-0.951) models performed the best. In the training set, the AUC of these two models were significantly higher than that of the LN metastasis status reported by 18F-FDG PET/CT for differentiating positive and negative regional LN metastases in CRC (all p < 0.05). Good efficacy of the above two models was also achieved in the test set. We created a nomogram based on the logistic regression model that visualized the results and provided an easy-to-use method for predicting regional LN metastasis in patients with CRC.

CONCLUSION

In this study, five machine-learning models for preoperative prediction of regional LN metastasis of CRC based on 18F-FDG PET/CT and PET-based radiomic features were successfully developed and validated. Among them, the logistic regression and XGBoost models performed the best, with higher efficacy than 18F-FDG PET/CT in both the training and test sets.

18F-FDG PET is Superior to WHO Grading as a Prognostic Tool in Neuroendocrine Neoplasms and Useful in Guiding PRRT: A Prospective 10-Year Follow-up Study

Accurate grading of patients with neuroendocrine neoplasms (NENs) is essential for risk stratification and optimal choice of therapy. Currently, grading is based on histologically assessed degree of tumor proliferation. The aim of the present study was to assess the long-term prognostic value of ¹⁸F-FDG PET imaging for risk stratification of NENs and compare it with tumor grading (World Health Organization 2010 classification). Methods: We conducted a prospective cohort study evaluating the prognostic value of ¹⁸F-FDG PET imaging and compared it with histologic grading. Enrolled were 166 patients of all grades and with histologically confirmed NENs of gastroenteropancreatic origin. The primary endpoint was overall survival (OS). Progression-free survival (PFS) was a secondary endpoint. In addition, OS in relation to peptide receptor radionuclide therapy (PRRT) was analyzed as an exploratory endpoint. The median follow-up time was 9.8 y. Results: Analysis of the whole cohort revealed that a positive ¹⁸F-FDG PET scan was associated with a shorter OS than a negative ¹⁸F-FDG PET scan (hazard ratio: 3.8; 95% CI: 2.4-5.9; P < 0.001). In G1 and G2 patients (n = 140), a positive ¹⁸F-FDG PET scan was the only identifier of high risk for death (hazard ratio: 3.6; 95% CI, 2.2-5.9; P < 0.001). In multivariate analysis, ¹⁸F-FDG PET, G3 tumor, ≥2 liver metastases, and ≥2 prior therapies were independent prognostic factors for OS, and ¹⁸F-FDG PET, G3 tumor, and ≥3 liver metastases were independent prognostic factors for PFS. For patients receiving PRRT, ¹⁸F-FDG-negative cases had a significantly longer survival than ¹⁸F-FDG-positive cases, whereas no difference was identified for tumor grading. ¹⁸F-FDG-positive patients receiving PRRT had a significantly longer median survival than patients not receiving PRRT (4.4 vs. 1.4 y, P = 0.001), whereas no difference was seen for ¹⁸F-FDG-negative patients. Conclusion: ¹⁸F-FDG PET is useful for risk stratification of all NEN grades and is superior to histologic grading. ¹⁸F-FDG PET could differentiate G1 and G2 tumors into low- and high-risk groups. In the selection of therapy and for risk stratification of NEN patients, ¹⁸F-FDG PET status should be considered.

Reinventing Molecular Imaging with Total-Body PET, Part II: Clinical Applications

Total-body PET scans will initiate a new era for the PET clinic. The benefits of 40-fold effective sensitivity improvement provide new capabilities to image with lower radiation dose, perform delayed imaging, and achieve improved temporal resolution. These technical features are detailed in the first of this 2-part series. In this part, the clinical impacts of the novel features of total-body PET scans are further explored. Applications of total-body PET scans focus on the real-time interrogation of systemic disease manifestations in a variety of practical clinical contexts. Total-body PET scans make clinical systems biology imaging a reality.

Intra-tumor metabolic heterogeneity of gastric cancer on 18F-FDG PETCT indicates patient survival outcomes

The present study aimed to investigate the prognostic value of intra-tumor metabolic heterogeneity on 2-[18F] Fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) for patients with gastric cancer. Fifty-five patients with advanced gastric cancer that had received neoadjuvant chemotherapy and radical surgery were included. Clinicopathological information, ¹⁸F-FDG PET/CT before chemotherapy, pathological response, recurrence or metastasis, progression-free survival (PFS), and overall survival (OS) of the patients were collected. The maximum, peak, and mean standardized uptake values (SUV_max, SUV_peak, and SUV_mean), tumor-to-liver ratio (TLR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on PET/CT were measured. Heterogeneity index-1 (HI-1) was calculated as SUV_mean divided by the standard deviation, and heterogeneity index-2 (HI-2) was evaluated through linear regressions of MTVs according to different SUV thresholds. Associations between these parameters and patient survival outcomes were analyzed. None of the parameters on PET were associated with tumor recurrence. Pathological responders had significantly smaller TLR, MTV and HI-2 values than non-responders (P = 0.017, 0.017 and 0.013, respectively). In multivariate analysis of PFS, only HI-2 was an independent factor (hazard ratio [HR] = 2.693, P = 0.005) after adjusting for clinical tumor-node-metastasis (TNM) stage. In multivariate analysis of OS, HI-2 was also an independent predictive factor (HR = 2.281, P = 0.009) after adjusting for tumor recurrence. Thus, HI-2 generated from baseline ¹⁸F-FDG PET/CT is significantly associated with survival of patients with gastric cancer. Preoperative assessment of HI-2 by ¹⁸F-FDG PET/CT might be promising to identify patients with poor prognosis.

Can PET-CT predict diagnostic success in ultrasonography-guided transthoracic fine needle aspiration biopsies in lung cancers?

OBJECTIVE

To examine any correlations between tumor maximum standard uptake values (SUVmax) in positron emission tomography-computed tomography (PET-CT) and homogeneous/heterogeneous tumor FDG uptake in PET-CT, and the diagnostic success of the procedure in thoracic ultrasonography (US)-guided transthoracic fine needle aspiration biopsy (TFNAB).

METHODS

The files of patients who underwent thoracic US-guided TFNAB between 2013 and 2018 were examined. Patients who underwent thoracic US-guided TFNAB and were diagnosed as having primary lung cancer were considered as the US-TFNAB diagnostic group. Patients whose disease was diagnosed as primary lung cancer using a different diagnostic method (e.g. CT-guided biopsies, fiberoptic bronchoscopy) due to a lack of diagnosis despite undergoing thoracic US-guided TFNAB were allocated to the US-TFNAB non-diagnostic group. The clinical and radiologic characteristics and PET-CT parameters of the two groups were compared.

RESULTS

A total of 104 patients were included in the study; 79 (76%) patients whose disease was diagnosed using US-guided TFNAB, and 25 (24%) patients whose primary lung cancer could not be diagnosed with US-guided TFNAB. The mean SUVmax value of the US-TFNAB diagnostic group was 19.5 ± 10.1, whereas it was 15.1 ± 8.9 in the US-TFNAB non-diagnostic group (p = 0.016). Whether a lesion showed homogeneous or heterogeneous FDG uptake did not effect diagnostic success (p = 0.289). SUVmax value was the only effective independent factor in the diagnostic success of the procedure (p = 0.035).

CONCLUSIONS

High SUVmax values in PET-CT in lung cancers may increase the diagnostic success of US guided-TFNAB procedures.

Advanced modalities of molecular imaging in precision medicine for musculoskeletal malignancies

Musculoskeletal malignancies consist of a heterogenous group of mesenchymal tumors, often with high inter- and intratumoral heterogeneity. The early and accurate diagnosis of these malignancies can have a substantial impact on optimal treatment and quality of life for these patients. Several new applications and techniques have emerged in molecular imaging, including advances in multimodality imaging, the development of novel radiotracers, and advances in image analysis with radiomics and artificial intelligence. This review highlights the recent advances in molecular imaging modalities and the role of non-invasive imaging in evaluating tumor biology in the era of precision medicine.

AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics

INTRODUCTION

The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes.

OBJECTIVE

The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.

Preparation and Evaluation of ZD2 Peptide 64Cu-DOTA Conjugate as a Positron Emission Tomography Probe for Detection and Characterization of Prostate Cancer

Positron emission tomography (PET) is a sensitive modality for cancer molecular imaging. We aim to develop a PET probe for sensitive detection and risk stratification of prostate cancer by targeting an abundant microenvironment oncoprotein, extradomain-B fibronectin (EDB-FN). The probe consists of a small ZD2 peptide specific to EDB-FN and a ⁶⁴Cu-DOTA chelate. The probe was synthesized using standard solid-phase peptide chemistry and chelated to ⁶⁴Cu prior to imaging. PET images were acquired at 4 and 22 h after intravenously injecting a 200 μCi probe into mice bearing human PC3 and LNCaP tumors, which represent highly aggressive and slow-growing prostate tumors, respectively. At 4 and 22 h postinjection, tumors could be clearly identified in the PET images. A significant higher signal was observed in PC3 tumors than in LNCaP tumors at 22 h (p = 0.01). Probe accumulation was also higher in PC3 tumors at 24 h. These data demonstrated that PET molecular imaging of EDB-FN in the tumor microenvironment of prostate cancer allows efficient differentiation of PC3 and LNCaP tumors in vivo. The ZD2 peptide-targeted PET probe shows potential in the detection and characterization of high-risk prostate cancer to improve the clinical management of prostate cancer.

Correlation between DCE-MRI radiomics features and Ki-67 expression in invasive breast cancer

The aim of the present study was to investigate the association between Ki-67 expression and radiomics features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with invasive breast cancer. A total of 53 cases with low-Ki-67 expression (Ki-67 proliferation index <14%) and 106 cases with high-Ki-67 expression (Ki-67 proliferation index >14%) were investigated. A systematic approach was applied that focused on the automated segmentation of lesions and extraction of radiomics features. For each lesion 5 morphology, 4 gray-scale histogram and 6 texture features were obtained, and statistical analyzes were performed to assess the differences in these features between the low- and high-Ki-67 expressions. One morphology metric (area), 3 gray-scale histogram indexes (standard deviation, skewness and kurtosis) and 3 texture features (contrast, homogeneity and inverse differential moment) demonstrated a significant difference (P<0.05), with low-Ki-67 expression lesions tending to be smaller, clearer and heterogeneous when compared with the high-Ki-67 expressed cases. These results may provide a noninvasive means to better understand the proliferation of breast cancer.

Metabolic heterogeneity on baseline 18FDG-PET/CT scan is a predictor of outcome in primary mediastinal B-cell lymphoma

An important unmet need in the management of primary mediastinal B-cell lymphoma (PMBCL) is to identify the patients for whom first-line therapy will fail to intervene before the lymphoma becomes refractory. High heterogeneity of intratumoral 18F-fluorodeoxyglucose (18FDG) uptake distribution on positron emission tomography/computed tomography (PET/CT) scans has been suggested as a possible marker of chemoresistance in solid tumors. In the present study, we investigated the prognostic value of metabolic heterogeneity (MH) in 103 patients with PMBCL prospectively enrolled in the International Extranodal Lymphoma Study Group (IELSG) 26 study, aimed at clarifying the role of PET in this lymphoma subtype. MH was estimated using the area under curve of cumulative standardized uptake value-volume histogram (AUC-CSH) method. Progression-free survival at 5 years was 94% vs 73% in low- and high-MH groups, respectively (P = .0001). In a Cox model of progression-free survival including dichotomized MH, metabolic tumor volume, total lesion glycolysis (TLG), international prognostic index, and tumor bulk (mediastinal mass > 10 cm), as well as age as a continuous variable, only TLG (P < .001) and MH (P < .001) retained statistical significance. Using these 2 features to construct a simple prognostic model resulted in early and accurate (positive predictive value, 89%; negative predictive value, ≥90%) identification of patients at high risk for progression at a point that would allow the use of risk-adapted treatments. This may provide an important opportunity for the design of future trials aimed at helping the minority of patients who harbor chemorefractory PMBCL. The study is registered at ClinicalTrials.gov as NCT00944567.

Can positron emission tomography/computed tomography be predictive of diagnostic success in endobronchial biopsies performed through a fiber-optic bronchoscopy in lung cancer?

PURPOSE

The purpose of this study is to investigate the effect of homogeneous/heterogeneous (necrotic) involvement and maximum standardized uptake value (SUVmax) value of the lesion on positron emission tomography-computed tomography (PET-CT) of patients who underwent fiberoptic bronchoscopy (FOB) for prediagnosis of lung cancer and biopsy for endobronchial lesion on the diagnostic success of biopsy procedure.

METHODS

Between January 2014 and December 2016, patients with final diagnosis of pulmonary malignancy as determined by FOB biopsy and patients who failed to be diagnosed by FOB biopsy and diagnosed with pulmonary malignancy by a different diagnostic method were examined. These patients were divided into two groups as those with diagnosis by FOB biopsy (Group 1) and those who failed to be diagnosed by this method and diagnosed with pulmonary malignancy by a different diagnostic method (Group 2). The SUVmax values of the two groups were compared with lesion characteristics of homogeneous, heterogeneous involvement/presence of necrotic component as shown by PET-CT. Group data were assessed by Chi-square test and Mann-Whitney U-test. In all tests, P < 0.05 was considered significant.

FINDINGS

A total of 193 participants with a mean age of 61 ± 9.4 were included in the study. There were 128 (66.3%) cases in Group 1 and 65 (33.7%) cases in Group 2. The mean SUVmax value was 16.4 in Group 1 and 15.1 in Group 2. There was no statistically significant difference between the two groups (P = 0.329). Homogeneous involvement was present in 103 (80.3%) cases in Group 1 versus 42 (64.6%) cases in Group 2. In the presence of homogeneous PET-CT involvement, diagnosis rate by biopsy was significantly higher (P = 0.016).

CONCLUSION

We concluded that the high SUVmax value of the mass lesion on PET-CT did not increase the diagnostic value of the biopsy procedure in patients prediagnosed with lung cancer and that the diagnostic success of FOB biopsy was poor in cases where PET-CT showed heterogeneous involvement of the mass lesion.

Validation of [18F]FLT as a perfusion-independent imaging biomarker of tumour response in EGFR-mutated NSCLC patients undergoing treatment with an EGFR tyrosine kinase inhibitor

Background

3′-Deoxy-3′-[¹⁸F]fluorothymidine ([¹⁸F]FLT) was proposed as an imaging biomarker for the assessment of in vivo cellular proliferation with positron emission tomography (PET). The current study aimed to validate [¹⁸F]FLT as a perfusion-independent PET tracer, by gaining insight in the intra-tumoural relationship between [¹⁸F]FLT uptake and perfusion in non-small cell lung cancer (NSCLC) patients undergoing treatment with a tyrosine kinase inhibitor (TKI).

Six patients with metastatic NSCLC, having an activating epidermal growth factor receptor (EGFR) mutation, were included in this study. Patients underwent [¹⁵O]H₂O and [¹⁸F]FLT PET/CT scans at three time points: before treatment and 7 and 28 days after treatment with a TKI (erlotinib or gefitinib). Parametric analyses were performed to generate quantitative 3D images of both perfusion measured with [¹⁵O]H₂O and proliferation measured with [¹⁸F]FLT volume of distribution (V_T). A multiparametric classification was performed by classifying voxels as low and high perfusion and/or low and high [¹⁸F]FLT V_T using a single global threshold for all scans and subjects. By combining these initial classifications, voxels were allocated to four categories (low perfusion-low V_T, low perfusion-high V_T, high perfusion-low V_T and high perfusion-high V_T).

Results

A total of 17 perfusion and 18 [¹⁸F]FLT PET/CT scans were evaluated. The average tumour values across all lesions were 0.53 ± 0.26 mL cm^− 3 min^− 1 and 4.25 ± 1.71 mL cm^− 3 for perfusion and [¹⁸F]FLT V_T, respectively. Multiparametric analysis suggested a shift in voxel distribution, particularly regarding the V_T: from an average of ≥ 77% voxels classified in the “high V_T category” to ≥ 85% voxels classified in the “low V_T category”. The shift was most prominent 7 days after treatment and remained relatively similar afterwards. Changes in perfusion and its spatial distribution were minimal.

Conclusion

The present study suggests that [¹⁸F]FLT might be a perfusion-independent PET tracer for measuring tumour response as parametric changes in [¹⁸F]FLT uptake occurred independent from changes in perfusion.

Trial registration

Nederlands Trial Register (NTR), NTR3557. Registered 2 August 2012

Electronic supplementary material

The online version of this article (10.1186/s13550-018-0376-6) contains supplementary material, which is available to authorized users.

A Novel Framework for Automated Segmentation and Labeling of Homogeneous Versus Heterogeneous Lung Tumors in [18F]FDG-PET Imaging

PURPOSE

Determination of intra-tumor high-uptake area using 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography (PET) imaging is an important consideration for dose painting in radiation treatment applications. The aim of our study was to develop a framework towards automated segmentation and labeling of homogeneous vs. heterogeneous tumors in clinical lung [¹⁸F]FDG-PET with the capability of intra-tumor high-uptake region delineation.

PROCEDURES

We utilized and extended a fuzzy random walk PET tumor segmentation algorithm to delineate intra-tumor high-uptake areas. Tumor textural feature (TF) analysis was used to find a relationship between tumor type and TF values. Segmentation accuracy was evaluated quantitatively utilizing 70 clinical [¹⁸F]FDG-PET lung images of patients with a total of 150 solid tumors. For volumetric analysis, the Dice similarity coefficient (DSC) and Hausdorff distance (HD) measures were extracted with respect to gold-standard manual segmentation. A multi-linear regression model was also proposed for automated tumor labeling based on TFs, including cross-validation analysis.

RESULTS

Two-tailed t test analysis of TFs between homogeneous and heterogeneous tumors revealed significant statistical difference for size-zone variability (SZV), intensity variability (IV), zone percentage (ZP), proposed parameters II and III, entropy and tumor volume (p < 0.001), dissimilarity, high intensity emphasis (HIE), and SUV_min (p < 0.01). Lower statistical differences were observed for proposed parameter I (p = 0.02), and no significant differences were observed for SUV_max and SUV_mean. Furthermore, the Spearman rank analysis between visual tumor labeling and TF analysis depicted a significant correlation for SZV, IV, entropy, parameters II and III, and tumor volume (0.68 ≤ ρ ≤ 0.84) and moderate correlation for ZP, HIE, homogeneity, dissimilarity, parameter I, and SUV_min (0.22 ≤ ρ ≤ 0.52), while no correlations were observed for SUV_max and SUV_mean (ρ < 0.08). The multi-linear regression model for automated tumor labeling process resulted in R ² and RMSE values of 0.93 and 0.14, respectively (p < 0.001), and generated tumor labeling sensitivity and specificity of 0.93 and 0.89. With respect to baseline random walk segmentation, the results showed significant (p < 0.001) mean DSC, HD, and SUV_mean error improvements of 21.4 ± 11.5 %, 1.4 ± 0.8 mm, and 16.8 ± 8.1 % in homogeneous tumors and 7.4 ± 4.4 %, 1.5 ± 0.6 mm, and 7.9 ± 2.7 % in heterogeneous lesions. In addition, significant (p < 0.001) mean DSC, HD, and SUV_mean error improvements were observed for tumor sub-volume delineations, namely 5 ± 2 %, 1.5 ± 0.6 mm, and 7 ± 3 % for the proposed Fuzzy RW method compared to RW segmentation.

CONCLUSION

We proposed and demonstrated an automatic framework for significantly improved segmentation and labeling of homogeneous vs. heterogeneous tumors in lung [¹⁸F]FDG-PET images.

[18F]FDG-PET/CT texture analysis in thyroid incidentalomas: preliminary results

Background

significance of incidental thyroid 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) uptake on positron emission tomography/computed tomography (PET/CT) scans remains controversial. We aimed to evaluate the ability of [¹⁸F]FDG-PET/CT texture analysis to predict final diagnosis in thyroid incidentaloma.

Methods

We retrospectively evaluated medical records of all patients who performed a [¹⁸F]FDG-PET/CT from January 2012 to October 2016. Those patients who presented a thyroid incidentaloma described in the medical records and performed a fine needle aspiration in our institution were considered for the analysis. Cytological and/or histological results were used as reference standard to define the final diagnosis. In case of negative cytology, the nodule was considered benign. In case of non-diagnostic or inconclusive results ultrasound, follow-up and further cytology/histology were used as final diagnosis. For suspected or positive cytological result, histology was used as reference standard. PET images were segmented using a General Electric AW workstation running PET VCAR software (GE Healthcare, Waukesha, WI, USA) settled with a threshold of 40% SUV_max. LifeX software (http://www.lifexsoft.org) was used to perform texture analysis. Statistical analysis was performed with R package (https://www.r-project.org).

Results

We identified 55 patients with incidental thyroid [¹⁸F]FDG uptake. Five patients were excluded from the analysis because a final diagnosis was not available. Thirty-two out of 50 patients had benign nodules while in 18/50 cases a malignancy (primary thyroid cancer = 15, metastases = 3) was diagnosed. Conventional PET parameters and histogram-based features were calculated for all 50 patients, while other matrices-based features were available for 28/50 patients. SUV_max and skewness resulted significantly different in benign and malignant nodules (p = 0.01 and = 0.02, respectively). Using ROC analysis, seven features were identified as potential predictors. Among all the textural features tested, skewness showed the best area under the curve (= 0.66). SUV-based parameters resulted in the highest specificity while MTV, TLG, skewness and kurtosis, as well as correlation_GLCM resulted better in sensitivity.

Conclusions

[¹⁸F]FDG-PET/CT texture analysis seems to be a promising approach to stratify the patients with thyroid incidentaloma identified on PET scans, with respect to the risk of the diagnosis of a malignant thyroid nodule and thus, could refine the selection of the patients to be referred for cytology.

18F-FDG Uptake During Early Adjuvant Chemotherapy Predicts Histologic Response in Pediatric and Young Adult Patients with Osteosarcoma

The purpose of this study was to determine the relationship of ¹⁸F-FDG uptake in the primary tumor at diagnosis, during therapy, and after therapy with a histologic response and event-free survival in pediatric and young adult patients with osteosarcoma (OS). Methods: Serial (baseline and 5 and 10 wk after start of therapy) ¹⁸F-FDG PET/CT imaging was performed in patients with newly diagnosed OS treated uniformly in a therapeutic trial at a single institution. Whole-body images were obtained approximately 1 h after injection of ¹⁸F-FDG. Logistic regression was used to study the association of tumor uptake and changes in SUV_max between 0, 5, and 10 wk for both clinical endpoints. Results: Thirty-four patients (17 males; median age, 12.2 y; age range, 6.8-19.1 y) underwent PET imaging; 25 (74%) had localized disease. Primary tumor locations included the femur (n = 17; 50%), tibia (n = 9; 26%), and humerus (n = 5; 15%). Logistic regression showed that SUV_max at 5 wk (P = 0.034) and 10 wk (P = 0.022) and percentage change from baseline at 10 wk (P = 0.021) were highly predictive of a histologic response. Using SUV_max of 4.04 at week 5, SUV_max of 3.15 at week 10, and 60% decrease from baseline at week 10 as cutoff values, we determined that the respective sensitivities were 0.93, 0.93, and 0.79 and that the respective specificities were 0.53, 0.71, and 0.76. Conclusion: SUV_max on routine images at 5 or 10 wk and percentage change in SUV_max from baseline to week 10 were metabolic predictors of a histologic response in OS. These findings may be useful in the early identification of patients who are responding poorly to therapy and may benefit from a change in treatment.

Metabolic Radiomics for Pretreatment 18F-FDG PET/CT to Characterize Locally Advanced Breast Cancer: Histopathologic Characteristics, Response to Neoadjuvant Chemotherapy, and Prognosis

Radiomics has been spotlighted as imaging biomarker for estimation of intratumoral heterogeneity (ITH) which is regarded as the main reason for resistance to tumor treatment. Although a number of studies has shown clinical evidences that separate measurement of metabolic ITH by texture features (TFs) on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) has prognostic ability in various tumors, there has been no consensus regarding the best parameter representing ITH. Besides, it is yet uncertain that TFs are useful for estimation of histopathologic markers, prediction of response to neoadjuvant chemotherapy (NAC), or prognostic ability in breast cancer. To depart from the traditional approach, we evaluated the clinical usefulness of integrated metabolic radiomics using unsupervised clustering with 109 TFs measured from pretreatment ¹⁸F-FDG PET/CT scans of 73 patients with locally advanced breast cancer (LABC) underwent NAC before surgery. Our study shows that metabolic radiomics patterns of LABC are associated with Ki67 expression, achievement of pathologic complete response after NAC, and risk of recurrence. Integrated metabolic radiomics has potential for clinically relevant pretreatment biomarker with predictive and prognostic ability for personalized management in LABC.

The future of personalised radiotherapy for head and neck cancer

Radiotherapy has long been the mainstay of treatment for patients with head and neck cancer and has traditionally involved a stage-dependent strategy whereby all patients with the same TNM stage receive the same therapy. We believe there is a substantial opportunity to improve radiotherapy delivery beyond just technological and anatomical precision. In this Series paper, we explore several new ideas that could improve understanding of the phenotypic and genotypic differences that exist between patients and their tumours. We discuss how exploiting these differences and taking advantage of precision medicine tools-such as genomics, radiomics, and mathematical modelling-could open new doors to personalised radiotherapy adaptation and treatment. We propose a new treatment shift that moves away from an era of empirical dosing and fractionation to an era focused on the development of evidence to guide personalisation and biological adaptation of radiotherapy. We believe these approaches offer the potential to improve outcomes and reduce toxicity.

Dual-time point 18F-FDG-PET and PET/CT for Differentiating Benign From Malignant Musculoskeletal Lesions: Opportunities and Limitations

In this review, we summarize the false-positive and false-negative results of standard ¹⁸F-FDG-PET/CT in characterizing musculoskeletal lesions and discussed the added value and limitations of dual-time point imaging (DTPI) and delayed imaging in differentiating malignant from benign musculoskeletal lesions, based on review of the peer-reviewed literature. The quantitative and semiquantitative parameters adopted for DTPI are standardized uptake value (mainly maximum standardized uptake value [SUVmax]) and retention index (RI), calculated as RI (%) = 100% × (SUV [maxD-Delayed] - SUV [maxE-Early])/SUV [maxE-Early], although the criteria and cutoff for diagnosing malignancy in studies have varied considerably. Also, there has been considerable heterogeneity in protocol (time point of delayed imaging), interpretation, and results in dual-time point (DTP) ¹⁸F-FDG-PET for differentiating malignant from benign musculoskeletal lesions in various research studies. The specificity of DTPI is a function of many factors such as the nature of the musculoskeletal lesion or malignancy in question, the prevalence of false-positive etiologies in the patient population, and the cutoff values (either SUVmax or RI) employed to define a malignancy. Despite the apparent conflicting reports on the performance, there have been certain common points of agreement regarding DTPI: (1) DTP PET increases the sensitivity of ¹⁸F-FDG-PET/CT due to continued clearance of background activity and increasing ¹⁸F-FDG accumulation in malignant lesions, when the same diagnostic criteria (as in the initial standard single-time point imaging) are used. Increased sensitivity for lesion detection can be viewed as a strong point of DTP and delayed-time point imaging. (2) The causes for false positives (such as active infectious or inflammatory lesions and locally aggressive benign tumors) and false negatives (eg, low-grade sarcomas) are the major hurdles accounting for reduced diagnostic value of the technique, with overlap of ¹⁸F-FDG uptake patterns between benign and malignant musculoskeletal lesions on DTPI. (3) DTPI, however, could still be potentially useful in increasing the confidence of interpretation such as differentiating malignancy from sites of inactive or chronic inflammation, post-treatment viable residue vs necrosis, and certain other benign lesions. (4) Consideration of diagnostic CT component of PET/CT and the patient's clinical picture can lead to increase in specificity of interpretation in a given case scenario. Further systematic research, adoption of uniform protocol, and interpretation criterion could evolve the specific indications and interpretation criteria of DTPI for improved diagnostic accuracy in musculoskeletal lesions and its clinical applications.

Imaging of Chemokine Receptor 4 Expression in Neuroendocrine Tumors - a Triple Tracer Comparative Approach

C-X-C motif chemokine receptor 4 (CXCR4) and somatostatin receptors (SSTR) are overexpressed in gastro-entero-pancreatic neuroendocrine tumors (GEP-NET). In this study, we aimed to elucidate the feasibility of non-invasive CXCR4 positron emission tomography/computed tomography (PET/CT) imaging in GEP-NET patients using [⁶⁸Ga]Pentixafor in comparison to ⁶⁸Ga-DOTA-D-Phe-Tyr3-octreotide ([⁶⁸Ga]DOTATOC) and ¹⁸F-fluorodeoxyglucose ([¹⁸F]FDG). Twelve patients with histologically proven GEP-NET (3xG1, 4xG2, 5xG3) underwent [⁶⁸Ga]DOTATOC, [¹⁸F]FDG, and [⁶⁸Ga]Pentixafor PET/CT for staging and planning of the therapeutic management. Scans were analyzed on a patient as well as on a lesion basis and compared to immunohistochemical staining patterns of CXCR4 and somatostatin receptors SSTR2a and SSTR5. [⁶⁸Ga]Pentixafor visualized tumor lesions in 6/12 subjects, whereas [¹⁸F]FDG revealed sites of disease in 10/12 and [⁶⁸Ga]DOTATOC in 11/12 patients, respectively. Regarding sensitivity, SSTR-directed PET was the superior imaging modality in all G1 and G2 NET. CXCR4-directed PET was negative in all G1 NET. In contrast, 50% of G2 and 80% of G3 patients exhibited [⁶⁸Ga]Pentixafor-positive tumor lesions. Whereas CXCR4 seems to play only a limited role in detecting well-differentiated NET, increasing receptor expression could be non-invasively observed with increasing tumor grade. Thus, [⁶⁸Ga]Pentixafor PET/CT might serve as non-invasive read-out for evaluating the possibility of CXCR4-directed endoradiotherapy in advanced dedifferentiated SSTR-negative tumors.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

Prediction of Recurrence by Preoperative Intratumoral FDG Uptake Heterogeneity in Endometrioid Endometrial Cancer

PURPOSE: To investigate the prognostic value of preoperative intratumoral ¹⁸F-FDG uptake heterogeneity (IFH) derived from positron emission tomography (PET)/computed tomography (CT) in patients with endometrioid endometrial cancer. METHODS: We retrospectively evaluated clinicopathological data from patients with pathologically proven endometrioid endometrial cancer who had undergone ¹⁸F-FDG PET/CT scans before surgery. Patients were divided into two groups according to their IFH. The main outcome measure was disease-free survival (DFS). RESULTS: Between January 2010 and January 2015, data from 72 patients were available for analysis. The median duration of DFS was 23 months (range, 6 to 57 months), and 4 (5.6%) patients experienced recurrence. There were significant differences in tumor size, IFH, and DFS between patients with and without recurrence. In regression analysis, high IFH value [P = .007, hazard ratio (HR) 2.545, 95% confidence interval (CI) 1.468-8.674] was the only independent risk factor for recurrence. The Kaplan-Meier survival graphs showed that DFS significantly differed in groups categorized based on IFH (P < .001, log-rank test). CONCLUSIONS: Preoperative IFH measured by ¹⁸F-FDG PET/CT was associated with recurrence of endometrioid endometrial cancer. The finding supports evidence that FDG-based heterogeneity can be a novel and useful predictor of endometrioid endometrial cancer recurrence.

Predictive Value of Standardized Intratumoral Metabolic Heterogeneity in Locally Advanced Cervical Cancer Treated With Chemoradiation

OBJECTIVE

The aim of this study was to propose and evaluate a novel image metric for quantifying spatial heterogeneity of tumor F-fluorodeoxyglucose (FDG) uptake within the context of predicting response to chemoradiation in locally advanced cervical cancer.

METHODS

Ninety patients with locally advanced cervical cancer treated with concomitant chemoradiation were included in this study. Each patient underwent two whole-body F-FDG positron emission tomography/computed tomography scans with one before the initiation of treatment for staging and the other at 12 weeks after treatment completion for response assessment. Patients were categorized in terms of response to chemoradiation into two major groups: complete metabolic responders and noncomplete metabolic responders. The capacity of the proposed intratumoral heterogeneity metric to differentiate patients with respect to response to therapy was evaluated and compared with the use of standardized uptake value indices and various texture parameters that had been previously introduced for predicting tumor response to chemoradiation.

RESULTS

At baseline, the proposed intratumoral heterogeneity metric along with four texture features, including entropy and energy derived from gray-level co-occurrence matrices and gray-level nonuniformity and zone size nonuniformity from gray-level zone size matrices, was capable of differentiating responders' groups with P values of 0.0026, 0.0252, 0.0240, 0.0234, and 0.0188, respectively. Furthermore, when compared with the texture features exhibiting significant difference between the responders' groups, the proposed metric demonstrated larger area under receiver operating characteristic curve.

CONCLUSIONS

The proposed metric with quantifying spatial heterogeneity of intratumoral FDG accumulation in a normalized manner may be associated with predictive value of poor response to concurrent chemoradiation in locally advanced cervical cancer.

Characterization of PET/CT images using texture analysis: the past, the present… any future?

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'-¹⁸F-fluorothymidine (¹⁸F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic ¹⁸F-FLT PET/CT to assess the robustness of these methods. Methods: Ten NSCLC patients underwent dynamic ¹⁸F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V_T) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy (R² ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V_T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K₁ values (R² = 0.94; intraclass correlation coefficient, 0.96). Parametric K₁ data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric ¹⁸F-FLT V_T images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K₁ data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic ¹⁸F-FLT PET/CT studies; however, SA can also be used.

Prognostic value of preoperative intratumoral FDG uptake heterogeneity in early stage uterine cervical cancer

OBJECTIVE

We investigated the prognostic value of intratumoral [¹⁸F]fluorodeoxyglucose (FDG) uptake heterogeneity (IFH) derived from positron emission tomography/computed tomography (PET/CT) in patients with cervical cancer.

METHODS

Patients with uterine cervical cancer of the International Federation of Obstetrics and Gynecology (FIGO) stage IB to IIA were imaged with [¹⁸F]FDG PET/CT before radical surgery. PET/CT parameters such as maximum and average standardized uptake values (SUV(max) and SUV(avg)), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and IFH were assessed. Regression analyses were used to identify clinicopathological and imaging variables associated with progression-free survival (PFS).

RESULTS

We retrospectively reviewed clinical data of 85 eligible patients. Median PFS was 32 months (range, 6 to 83 months), with recurrence observed in 14 patients (16.5%). IFH at an SUV of 2.0 was correlated with primary tumor size (p<0.001), SUV(tumor) (p<0.001), MTV(tumor) (p<0.001), TLG(tumor) (p<0.001), depth of cervical invasion (p<0.001), and negatively correlated with age (p=0.036). Tumor recurrence was significantly associated with TLG(tumor) (p<0.001), MTV(tumor) (p=0.001), SUV(LN) (p=0.004), IFH (p=0.005), SUV(tumor) (p=0.015), and FIGO stage (p=0.015). Multivariate analysis identified that IFH (p=0.028; hazard ratio, 756.997; 95% CI, 2.047 to 279,923.191) was the only independent risk factor for recurrence. The Kaplan-Meier survival graphs showed that PFS significantly differed in groups categorized based on IFH (p=0.013, log-rank test).

CONCLUSION

Preoperative IFH was significantly associated with cervical cancer recurrence. [¹⁸F]FDG based heterogeneity may be a useful and potential predicator of patient recurrence before treatment.

Molecular Imaging and Precision Medicine in Head and Neck Cancer

The concept of using tumor genomic profiling information has revolutionized personalized cancer treatment. Head and neck (HN) cancer management is being influenced by recent discoveries of activating mutations in epidermal growth factor receptor and related targeted therapies with tyrosine kinase inhibitors, targeted therapies for Kristen Rat Sarcoma, and MET proto-oncogenes. Molecular imaging using PET plays an important role in assessing the biologic behavior of HN cancer with the goal of delivering individualized cancer treatment. This review summarizes recent genomic discoveries in HN cancer and their implications for functional PET imaging in assessing response to targeted therapies, and drug resistance mechanisms.

Value of 18F-FDG heterogeneity for discerning metastatic from benign lymph nodes in nasopharyngeal carcinoma patients with suspected recurrence

OBJECTIVE

This study investigated the value of fluorine-18 fludeoxyglucose (¹⁸F-FDG) heterogeneity as an indicator of metastatic lymph nodes (LNs) in patients with nasopharyngeal carcinoma (NPC). We further assessed whether addition of this parameter improves diagnostic performance beyond that provided by maximum standardized uptake value (SUV_max).

METHODS

We analyzed 74 LNs that were suspicious for metastasis. These LNs were measured for coefficient of variation (CV) of ¹⁸F-FDG uptake, which was used as a parameter for ¹⁸F-FDG heterogeneity.

RESULTS

Multivariate logistic regression analyses revealed that a high CV (hazard ratio, 20.97; 95% confidence interval, 2.26-194.62; p = 0.007) was an independent predictor of metastatic LNs. However, receiver-operating characteristic curve analysis (p = 0.278) and net reclassification (p = 0.539) were unable to show improved diagnostic performance by addition of CV to SUV_max.

CONCLUSION

High CV of ¹⁸F-FDG uptake is an independent risk factor for metastatic LNs in patients with NPC displaying suspicious LNs following treatment. Advances in knowledge: Heterogeneity of ¹⁸F-FDG uptake has a potential as a biomarker of metastatic LNs.

Quantification of Intratumoral Metabolic Macroheterogeneity on 18F-FDG PET/CT and Its Prognostic Significance in Pathologic N0 Squamous Cell Lung Carcinoma

PURPOSE

This study aimed to develop a novel quantification method for intratumoral metabolic macroheterogeneity (IMMH) on F-FDG PET/CT and evaluate its prognostic significance in pathologic N0 (pN0) squamous cell lung carcinoma (SQCLC) patients.

PATIENTS AND METHODS

A total of 83 patients who underwent pretreatment F-FDG PET/CT and were diagnosed with pN0 SQCLC after curative surgery were examined. Patients with tumor measuring greater than 2 cm were included. Metabolic parameters (SUVmax, metabolic tumor volume, and total lesion glycolysis) for the primary lesions were calculated on the F-FDG PET/CT, and IMMH was quantified as the macroheterogeneity factor (MHF), defined as surface/spherical surface area having volume of the primary tumor multiplied by the sphericity. Heterogeneity of the primary tumor was also visually assessed (visual heterogeneity score) and compared with MHF. Univariate and multivariate analyses for recurrence were performed using the Cox proportional hazards regression.

RESULTS

Recurrence was observed in 27 (32.5%) of 83 patients during follow-up period (37.6 ± 25.5 months). Significant correlations were observed between the visual heterogeneity score and the MHF (R = 0.534, P < 0.001). Macroheterogeneity factor was significantly higher in patients who experienced recurrence (median, 1.073 vs 1.016; P = 0.004). Univariate analysis showed that MHF was only significant prognostic factor for recurrence (P = 0.019), and multivariate analysis after adjusting for age, sex, tumor size, histologic grade, and pathologic T stage, high MHF exhibited an association with increased risk of recurrence.

CONCLUSIONS

New quantification method for IMMH on F-FDG PET/CT was developed, and the heterogeneity parameter MHF was well correlated with visual heterogeneity. Macroheterogeneity factor on pretreatment F-FDG PET/CT was the sole prognostic factor predicting recurrence in pN0 SQCLC patients.

Applications and limitations of radiomics

Radiomics is an emerging field in quantitative imaging that uses advanced imaging features to objectively and quantitatively describe tumour phenotypes. Radiomic features have recently drawn considerable interest due to its potential predictive power for treatment outcomes and cancer genetics, which may have important applications in personalized medicine. In this technical review, we describe applications and challenges of the radiomic field. We will review radiomic application areas and technical issues, as well as proper practices for the designs of radiomic studies.

99mTc-phytate as a diagnostic probe for assessing inflammatory reaction in malignant tumors

OBJECTIVE

Once administered intravenously, technetium-99m (99mTc)-labeled phytate binds to calcium in the serum and behaves as a nanoparticle. On the basis of the high permeability of the tumor vasculature, 99mTc-phytate is expected to leak and accumulate specifically in inflammatory cells. The aim of this study was to evaluate the potential of 99mTc-phytate in assessing the degree of inflammation in Ehrlich solid tumors in mice.

MATERIALS AND METHODS

99mTc-phytate was prepared by adding pertechnetate to a solution containing phytic acid and stannous chloride. The blood half-life of this particle following intravenous injection was determined using blood samples from healthy animals, whereas its size was measured by photon correlation spectroscopy. Scintigraphic imaging and biodistribution studies were carried out in tumor-bearing mice at 30 min and 2 h after injection.

RESULTS

The average size of the particles was in the range of 200 nm, suggesting that they are capable of passively passing through fenestrations in tumor vessels, which are 200-2000 nm in size. The blood half-life for 99mTc-phytate was found to be 2.1 min, a result that is in agreement with previous studies. Data from tumor-bearing mice showed high tumor uptake at 2 h after 99mTc-phytate administration. As a result, a high tumor-to-muscle ratio was achieved (T/M = 25.9 ± 7.54).

CONCLUSION

These findings indicate that 99mTc-sodium phytate has promising properties for identifying the type of tumor. This approach will have significant implications for characterizing tumor biology and treatment of malignant lesions.

PET-Based Personalized Management in Clinical Oncology: An Unavoidable Path for the Foreseeable Future

It is imperative that the thrust of clinical practice in the ensuing years would be to develop personalized management model for various disorders. PET-computed tomography (PET-CT) based molecular functional imaging has been increasingly utilized for assessment of tumor and other nonmalignant disorders and has the ability to explore disease phenotype on an individual basis and address critical clinical decision making questions related to practice of personalized medicine. Hence, it is essential to make a concerted systematic effort to explore and define the appropriate place of PET-CT in personalized clinical practice in each of malignancies, which would strengthen the concept further. The potential advantages of PET based disease management can be classified into broad categories: (1) Traditional: which includes assessment of disease extent such as initial disease staging and restaging, treatment response evaluation particularly early in the course and thus PET-CT response adaptive decision for continuing the same regimen or switching to salvage schedules; there has been continuous addition of newer application of PET based disease restaging in oncological parlance (eg, Richter transformation); (2) Recent and emerging developments: this includes exploring tumor biology with FDG and non-FDG PET tracers. The potential of multitracer PET imaging (particularly new and novel tracers, eg, 68Ga-DOTA-TOC/NOC/TATE in NET, 68Ga-PSMA and 18F-fluorocholine in prostate carcinoma, 18F-fluoroestradiol in breast carcinoma) has provided a scientific basis to stratify and select appropriate targeted therapies (both radionuclide and nonradionuclide treatment), a major boost for individualized disease management in clinical oncology. Integrating the molecular level information obtained from PET with structural imaging further individualizing treatment plan in radiation oncology, precision of interventions and biopsies of a particular lesion and forecasting disease prognosis.

Prognostic value of preoperative intratumoral FDG uptake heterogeneity in patients with epithelial ovarian cancer

OBJECTIVES

To investigate the prognostic value of intratumoral FDG uptake heterogeneity (IFH) derived from PET/CT in patients with epithelial ovarian cancer (EOC).

METHODS

We retrospectively reviewed patients with pathologically proven epithelial ovarian cancer who underwent preoperative ¹⁸F-FDG PET/CT scans. PET/CT parameters such as maximum and average standardized uptake values (SUV_max and SUV_avg), sum of all metabolic tumour volume (MTV), cumulative total lesion glycolysis (TLG) and IFH were assessed. Regression analyses were used to identify clinicopathological and imaging variables associated with disease-free survival (DFS).

RESULTS

Clinicopathological data were reviewed for 61 eligible patients. The median duration of DFS was 13 months (range, 6-26 months), and 18 (29.5 %) patients experienced recurrence. High IFH values were associated with tumour recurrence (P = 0.005, hazard ratio 4.504, 95 % CI 1.572-12.902). The Kaplan-Meier survival graphs showed that DFS significantly differed in groups categorized based on IFH (P = 0.002, log-rank test). Moreover, there were significant differences in DFS (P = 0.009) and IFH (P = 0.040) between patients with and without recurrence.

CONCLUSIONS

Preoperative IFH measured by ¹⁸F-FDG PET/CT was significantly associated with EOC recurrence. FDG-based heterogeneity could be a useful and potential predicator of EOC recurrence before treatment.

KEY POINTS

• Preoperative IFH was significantly associated with recurrence of EOC • Disease-free survival significantly differed in groups categorized by IFH • FDG-based heterogeneity could be a potential predicator of EOC recurrence before treatment.

Direct comparison of (68)Ga-DOTA-TOC and (18)F-FDG PET/CT in the follow-up of patients with neuroendocrine tumour treated with the first full peptide receptor radionuclide therapy cycle

Purpose

To determine the value of ⁶⁸Ga-DOTA-TOC and ¹⁸F-FDG PET/CT for initial and follow-up evaluation of patients with neuroendocrine tumour (NET) treated with peptide receptor radionuclide therapy (PRRT).

Methods

We evaluated 66 patients who had histologically proven NET and underwent both PRRT and three combined ⁶⁸Ga-DOTA-TOC and ¹⁸F-FDG PET/CT studies. ⁶⁸Ga-DOTA-TOC PET/CT was performed before PRRT, 3 months after completion of PRRT and after a further 6 – 9 months. ¹⁸F-FDG PET/CT was done within 2 months of ⁶⁸Ga-DOTA-TOC PET/CT. Follow-up ranged from 11.8 to 80.0 months (mean 34.5 months).

Results

All patients were ⁶⁸Ga-DOTA-TOC PET-positive initially and at follow-up after the first full PRRT cycle. Overall, 62 of the 198 ¹⁸F-FDG PET studies (31 %) were true-positive in 38 of the 66 patients (58 %). Of the 66 patients, 28 (5 grade 1, 23 grade 2) were ¹⁸F-FDG-negative initially and during follow-up (group 1), 24 (5 grade 1, 13 grade 2, 6 grade 3) were ¹⁸F-FDG-positive initially and during follow-up (group 2), 9 patients (2 grade 1, 6 grade 2, 1 grade 3) were ¹⁸F-FDG-negative initially but ¹⁸F-FDG-positive during follow-up (group 3), and 5 patients (all grade 2) were ¹⁸F-FDG-positive initially but ¹⁸F-FDG-negative during follow-up (group 4).¹⁸F-FDG PET showed more and/or larger metastases than ⁶⁸Ga-DOTA-TOC PET in five patients of group 2 and four patients of group 3, all with progressive disease. In three patients with progressive disease who died during follow-up tumour SUVmax increased by 41 – 82 % from the first to the last follow-up investigation.

Conclusion

In NET patients, the presence of ¹⁸F-FDG-positive tumours correlates strongly with a higher risk of progression. Initially, patients with ¹⁸F-FDG-negative NET may show ¹⁸F-FDG-positive tumours during follow-up. Also patients with grade 1 and grade 2 NET may have ¹⁸F-FDG-positive tumours. Therefore, ¹⁸F-FDG PET/CT is a complementary tool to ⁶⁸Ga-DOTA-TOC PET/CT with clinical relevance for molecular investigation.