Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer

Prognostic value of textural indices extracted from pretherapeutic 18-F FDG-PET/CT in head and neck squamous cell carcinoma

BACKGROUND

This study aimed at assessing the prognostic value of textural indices extracted from 18F-fluorodeoxyglucose positron-emission tomography (FDG-PET)/CT in a large cohort of patients with head and neck squamous cell carcinomas (HNSCC) of any anatomic subsite and staging.

METHODS

Consecutive patients with HNSCC referred for a pretreatment FDG-PET/CT were retrospectively included and followed up for a minimum of 2 years. Standardized uptake value, metabolic tumor volume (MTV), and textural indices were calculated using LIFEx software. Prognostic significance of parameters was assessed in univariate and multivariate analysis.

RESULTS

Textural indices were extracted in 284 patients (mean age = 63.7±9.6 years). In univariate analysis, MTV and 4 textural indices-Correlation, Entropy, Energy, and Coarseness-were significantly correlated with overall survival (OS). In multivariate analysis, MTV (P = .008) and Correlation (P = .028) remained independently correlated to OS.

CONCLUSION

This study showed that MTV and 1 textural index extracted from pretherapeutic FDG-PET/CT (Correlation) were independent prognostic factors of OS in patients with HNSCC.

Radiomic Profiling of Head and Neck Cancer: 18F-FDG PET Texture Analysis as Predictor of Patient Survival

Background and Purpose

The accurate prediction of prognosis and pattern of failure is crucial for optimizing treatment strategies for patients with cancer, and early evidence suggests that image texture analysis has great potential in predicting outcome both in terms of local control and treatment toxicity. The aim of this study was to assess the value of pretreatment ¹⁸F-FDG PET texture analysis for the prediction of treatment failure in primary head and neck squamous cell carcinoma (HNSCC) treated with concurrent chemoradiation therapy.

Methods

We performed a retrospective analysis of 90 patients diagnosed with primary HNSCC treated between January 2010 and June 2017 with concurrent chemo-radiotherapy. All patients underwent ¹⁸F-FDG PET/CT before treatment. ¹⁸F-FDG PET/CT texture features of the whole primary tumor were measured using an open-source texture analysis package. Least absolute shrinkage and selection operator (LASSO) was employed to select the features that are associated the most with clinical outcome, as progression-free survival and overall survival. We performed a univariate and multivariate analysis between all the relevant texture parameters and local failure, adjusting for age, sex, smoking, primary tumor site, and primary tumor stage. Harrell c-index was employed to score the predictive power of the multivariate cox regression models.

Results

Twenty patients (22.2%) developed local failure, whereas the remaining 70 (77.8%) achieved durable local control. Multivariate analysis revealed that one feature, defined as low-intensity long-run emphasis (LILRE), was a significant predictor of outcome regardless of clinical variables (hazard ratio < 0.001, P=0.001).The multivariate model based on imaging biomarkers resulted superior in predicting local failure with a c-index of 0.76 against 0.65 of the model based on clinical variables alone.

Conclusion

LILRE, evaluated on pretreatment ¹⁸F-FDG PET/CT, is associated with higher local failure in patients with HNSCC treated with chemoradiotherapy. Using texture analysis in addition to clinical variables may be useful in predicting local control.

Integrating quantitative morphological and intratumoural textural characteristics in FDG-PET for the prediction of prognosis in pharynx squamous cell carcinoma patients

AIM

To assess potential prognostic factors in pharynx squamous cell carcinoma (SCC) patients by quantitative morphological and intratumoural characteristics obtained by 2-[¹⁸F]-fluoro-2-deoxy-d-glucose positron-emission tomography/computed tomography (FDG-PET/CT).

MATERIALS AND METHODS

The cases of 54 patients with pharynx SCC who underwent chemoradiation therapy were analysed retrospectively. Using their FDG-PET data, the quantitative morphological and intratumoural characteristics of 14 parameters were calculated. The progression-free survival (PFS) and overall survival (OS) information was obtained from patient medical records. Univariate and multivariate analyses were performed to assess the 14 quantitative parameters as well as the T-stage, N-stage, and tumour location data for their relation to PFS and OS. When an independent predictor was suggested in the multivariate analysis, the parameter was further assessed using the Kaplan-Meier method.

RESULTS

In the assessment of PFS, the univariate and multivariate analyses indicated the following as independent predictors: the texture parameter of homogeneity and the morphological parameter of sphericity. In the Kaplan-Meier analysis, the PFS rate was significantly improved in the patients who had both a higher value of homogeneity (p=0.01) and a higher value of sphericity (p=0.002). With the combined use of homogeneity and sphericity, the patients with different PFS rates could be divided more clearly.

CONCLUSION

The quantitative parameters of homogeneity and sphericity obtained by FDG-PET can be useful for the prediction of the PFS of pharynx SCC patients, especially when used in combination.

Semi-quantitative analysis of pre-treatment morphological and intratumoral characteristics using 18F-fluorodeoxyglucose positron-emission tomography as predictors of treatment outcome in nasal and paranasal squamous cell carcinoma

Background

To investigate the utility of quantitative morphological and intratumoral characteristics obtained by ¹⁸F-fluorodeoxyglucose positron-emission tomography/computed tomography (FDG-PET/CT) for the prediction of treatment outcome in patients with nasal or paranasal cavity squamous cell carcinoma (SCC).

Methods

Twenty-four patients with nasal or paranasal cavity SCC who received curative non-surgical therapy (a combination of super-selective arterial cisplatin infusion and radiotherapy) were retrospectively analyzed. From pre-treatment FDG-PET data, a total of 13 parameters of quantitative morphological characteristics (tumor volume, surface area and sphericity), intratumoral characteristics (the maximum and mean standard uptake value, three intratumoral histogram and four textural parameters) and total lesion glycolysis (TLG) were respectively calculated. Information regarding the treatment outcome was determined from the histological diagnosis or clinical follow-up. Each of the 13 quantitative parameters as well as T- and N-stage was assessed for its relation to treatment outcome of local control or failure.

Results

In univariate analysis, significant differences in surface area and sphericity between the local control and failure groups were observed. The receiver operating characteristic (ROC) curve analysis showed that sphericity had the highest accuracy of 0.88. In the multivariate analysis, sphericity was revealed as an independent predictor of the local control or failure.

Conclusions

The quantitative parameters of sphericity are useful to predict the treatment outcome in patients with nasal or paranasal SCC.

Texture analysis of 3D dose distributions for predictive modelling of toxicity rates in radiotherapy

BACKGROUND AND PURPOSE

To explore the use of texture analysis (TA) features of patients' 3D dose distributions to improve prediction modelling of treatment complication rates in prostate cancer radiotherapy.

MATERIAL AND METHODS

Late toxicity scores, dose distributions, and non-treatment related (NTR) predictors for late toxicity, such as age and baseline symptoms, of 351 patients of the hypofractionation arm of the HYPRO randomized trial were used in this study. Apart from DVH parameters, also TA features of rectum and bladder 3D dose distributions were used for predictive modelling of gastrointestinal (GI) and genitourinary (GU) toxicities. Logistic Normal Tissue Complication Probability (NTCP) models were derived, using only NTR parameters, NTR + DVH, NTR + TA, and NTR + DVH + TA.

RESULTS

For rectal bleeding, the area under the curve (AUC) for using only NTR parameters was 0.58, which increased to 0.68, and 0.73, when adding DVH or TA parameters respectively. For faecal incontinence, the AUC went up from 0.63 (NTR only), to 0.68 (+DVH) and 0.73 (+TA). For nocturia, adding TA features resulted in an AUC increase from 0.64 to 0.66, while no improvement was seen when including DVH parameters in the modelling. For urinary incontinence, the AUC improved from 0.68 to 0.71 (+DVH) and 0.73 (+TA). For GI, model improvements resulting from adding TA parameters to NTR instead of DVH were statistically significant (p < 0.04).

CONCLUSION

Inclusion of 3D dosimetric texture analysis features in predictive modelling of GI and GU toxicity rates in prostate cancer radiotherapy improved prediction performance, which was statistically significant for GI.

Radiomics in Oncological PET/CT: Clinical Applications

18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is widely used for staging, evaluating treatment response, and predicting prognosis in malignant diseases. FDG uptake and volumetric PET parameters such as metabolic tumor volume have been used and are still used as conventional PET parameters to assess biological characteristics of tumors. However, in recent years, additional features derived from PET images by computational processing have been found to reflect intratumoral heterogeneity, which is related to biological tumor features, and to provide additional predictive and prognostic information, which leads to the concept of radiomics. In this review, we focus on recent clinical studies of malignant diseases that investigated intratumoral heterogeneity on PET/CT, and we discuss its clinical role in various cancers.

Robustness versus disease differentiation when varying parameter settings in radiomics features: application to nasopharyngeal PET/CT

OBJECTIVES

To investigate the impact of parameter settings as used for the generation of radiomics features on their robustness and disease differentiation (nasopharyngeal carcinoma (NPC) versus chronic nasopharyngitis (CN) in FDG PET/CT imaging).

METHODS

We studied 106 patients (69/37 NPC/CN, pathology confirmed), and extracted 57 radiomics features under different parameter settings. Robustness was assessed by the intra-class correlation coefficient (ICC). Logistic regression with leave-one-out cross validation was used to generate classification probabilities, and diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

Varying averaging strategies and symmetry, 4/26 GLCM features showed poor range of pairwise ICCs of 0.02-0.98, while depicting good AUCs of 0.82-0.91. Varying distances, 5/26 GLCM features showed ICCs of 0.82-0.99 while corresponding AUCs were 0.52-0.91. 6/13 GLRLM features showed both high AUC (0.81-0.89) and high ICC (0.85-0.99) regarding to averaging strategies. 7/13 GLSZM features showed AUCs of 0.81-0.90 while having ICCs of 0.01-0.99 under different neighbourhoods. 2/5 NGTDM features showed AUCs of 0.81-0.85 while having ICCs of 0.19-0.89 for different window sizes. Differentiating a subset of NPC (stages I-II) form CN, both SumEntropy and SZLGE achieved significantly higher AUCs than metabolically active tumour volume (AUC: 0.91 vs. 0.72, p<0.01).

CONCLUSIONS

Radiomics features depicting poor absolute-scale robustness regarding to parameter settings can still lead to good diagnostic performance. As such, robustness of radiomics features should not be overemphasized for removal of features towards assessment of clinical tasks. For differentiating NPC from CN, some radiomics features (e.g. SumEntropy, SZLGE, LGZE) outperformed conventional metrics.

KEY POINTS

• Poor robustness did not necessarily translate into poor differentiation performance. • Absolute-scale robustness of radiomics features should not be overemphasized. • Radiomics features SumEntropy, SZLGE and LGZE outperformed conventional metrics.

Heterogeneity and irregularity of pretreatment 18F-fluorodeoxyglucose positron emission tomography improved prognostic stratification of p16-negative high-risk squamous cell carcinoma of the oropharynx

OBJECTIVES

Human papillomavirus-negative oropharyngeal squamous cell carcinoma (OPSCC) has unfavorable survival outcomes. Two outcomes have been identified based on smoking history and tumor stage. We investigate the prognostic role of pre-treatment positron emission tomography (PET) in high-risk OPSCC.

MATERIALS AND METHODS

We enrolled 147 M0 OPSCC patients with p16-negative staining and a history of heavy smoking (>10 pack-years) or T4 disease. All patients completed primary chemoradiotherapy, and 42% maximum standard uptake values (SUV_max) were used as the threshold for primary tumor. Patients were classified into training and validation cohorts with a ratio of 1:1.5 according to the PET date. Heterogeneity and irregularity indices were obtained. PET parameters with significant impact on progression-free survival (PFS) in receiver operating characteristic curves and univariate Cox models were identified and included in recursive partitioning analysis (RPA) for constructing a prognostic model. The RPA-based prognostic model was further tested in the validation cohort using multivariate Cox models.

RESULTS

Fifty-eight and 89 patients were in the training and validation groups, respectively. Heterogeneity parameter, SUV-entropy (derived from histogram analysis), and irregularity index, and asphericity were significantly associated with PFS. The RPA model revealed that patients with both high SUV-entropy and high asphericity experienced the worst PFS. Results were confirmed in the validation group. The overall concordance index for PFS of the model was 0.75, which was higher than the clinical stages, performance status, SUV_max, and metabolic tumor volume of PET.

CONCLUSIONS

PET prognostic model provided useful prediction of PFS for patients with high-risk OPSCC.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancement in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration has ushered in the era of radiomics, a paradigm shift that holds tremendous potential in clinical decision support as well as drug discovery. However, there are important issues to consider to incorporate radiomics into a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that point to enterprise development (Part 2). In Part 2 of this two-part series, we study the components of the strategy pipeline, from clinical implementation to building enterprise solutions.

Texture analysis of 18F-FDG PET/CT for grading thymic epithelial tumours: usefulness of combining SUV and texture parameters

OBJECTIVE

To retrospectively investigate the standardized uptake value (SUV)-related and heterogeneous texture parameters individually and in combination for differentiating between low- and high-risk ¹⁸Fluorone-fludeoxyglucose (¹⁸F-FDG)-avid thymic epithelial tumours (TETs) with positron emission tomography (PET)/CT.

METHODS

SUV-related and 6 texture parameters (entropy, homogeneity, dissimilarity, intensity variability, size-zone variability and zone percentage) were compared between 11 low-risk and 23 high-risk TETs (metabolic tumour volume >10.0 cm³ and SUV ≥2.5). Diagnostic performance was evaluated by receiver operating characteristic analysis. The diagnostic value of combining SUV and texture parameters was examined by a scoring system.

RESULTS

High-risk TETs were significantly higher in SUVmax (p = 0.022), entropy (p = 0.038), intensity variability (p = 0.041) and size-zone variability (p = 0.045) than low-risk TETs. Diagnostic accuracies of these 4 parameters, dissimilarity and zone percentage which also showed significance in receiver operating characteristic analysis ranged between 64.7 and 73.5% without significant differences in AUC (range; 0.71 to 0.75) (p ≥ 0.05 each). Each parameter was scored as 0 (negative for high-risk) or 1 (positive for high-risk) according to each threshold criterion, then scores were summed [0 or 1 for low-risk TETs (median; 1); ≥2 for high-risk TETs (median; 4)]. The sensitivity, specificity and accuracy of detecting high-risk TETs were 100, 81.8 and 94.1%, respectively, with an AUC of 0.99.

CONCLUSION

The diagnostic performances of individual SUVmax and texture parameters were relatively low. However, combining these parameters can significantly increase diagnostic performance when differentiating between relatively large low- and high-risk ¹⁸F-FDG-avid TETs. Advances in knowledge: Combined use of SUVmax and texture parameters can significantly increase the diagnostic performance when differentiating between low- and high-risk TETs.

Texture analysis of FDG PET/CT for differentiating between FDG-avid benign and metastatic adrenal tumors: efficacy of combining SUV and texture parameters

PURPOSE

To retrospectively investigate the SUV-related and texture parameters individually and in combination for differentiating between F-18-fluorodeoxyglucose (FDG)-avid benign and metastatic adrenal tumors with PET/CT.

METHODS

Thirteen benign adrenal tumors (BATs) and 22 metastatic adrenal tumors (MATs) with a metabolic tumor volume (MTV) > 10.0 cm³ and SUV ≥ 2.5 were included. SUVmax, MTV, total lesion glycolysis, and four textural parameters [entropy, homogeneity, intensity variability (IV), and size-zone variability] were obtained. These parameters were compared between BATs and MATs using Mann-Whitney U test, and the diagnostic performance was evaluated by the area under the curve (AUC) values derived from the receiver operating characteristic analysis. The diagnostic value of combining SUV and texture parameters was examined using a scoring system.

RESULTS

MATs showed significantly higher SUV_max (p = 0.004), entropy (p = 0.013), IV (p = 0.006), and lower homogeneity (p = 0.019) than BATs. The accuracies for diagnosing MATs were 82.9, 82.9, 85.7, and 71.4% for SUV_max, entropy, IV, and homogeneity, respectively. No significant differences in AUC were found among these parameters (p > 0.05 each). When each parameter was scored as 0 (negative for malignancy) and 1 (positive for malignancy) according to each threshold criterion and the four parameter summed scores 0, 1, and 2 were defined as benignity and 3 and 4 as malignancy, the sensitivity and specificity and accuracy to predict MATs were 100% (22/22), 84.6% (11/13), and 94.3% (33/35), respectively, with 0.97 of the AUC.

CONCLUSION

The combined use of SUV_max and texture parameters has a potential to significantly increase the diagnostic performance to differentiate between large FDG-avid BATs and MATs.

Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer Treated With Definitive Radiotherapy: Which Threshold Is the Best Predictor of Local Control?

PURPOSE

In the context of oropharyngeal cancer treated with definitive radiotherapy, the aim of this retrospective study was to identify the best threshold value to compute metabolic tumor volume (MTV) and/or total lesion glycolysis to predict local-regional control (LRC) and disease-free survival.

METHODS

One hundred twenty patients with a locally advanced oropharyngeal cancer from 2 different institutions treated with definitive radiotherapy underwent FDG PET/CT before treatment. Various MTVs and total lesion glycolysis were defined based on 2 segmentation methods: (i) an absolute threshold of SUV (0-20 g/mL) or (ii) a relative threshold for SUVmax (0%-100%). The parameters' predictive capabilities for disease-free survival and LRC were assessed using the Harrell C-index and Cox regression model.

RESULTS

Relative thresholds between 40% and 68% and absolute threshold between 5.5 and 7 had a similar predictive value for LRC (C-index = 0.65 and 0.64, respectively). Metabolic tumor volume had a higher predictive value than gross tumor volume (C-index = 0.61) and SUVmax (C-index = 0.54). Metabolic tumor volume computed with a relative threshold of 51% of SUVmax was the best predictor of disease-free survival (hazard ratio, 1.23 [per 10 mL], P = 0.009) and LRC (hazard ratio: 1.22 [per 10 mL], P = 0.02).

CONCLUSIONS

The use of different thresholds within a reasonable range (between 5.5 and 7 for an absolute threshold and between 40% and 68% for a relative threshold) seems to have no major impact on the predictive value of MTV. This parameter may be used to identify patient with a high risk of recurrence and who may benefit from treatment intensification.

Clinical utility of texture analysis of 18F-FDG PET/CT in patients with Stage I lung cancer treated with stereotactic body radiotherapy

We evaluated the reproducibility and predictive value of texture parameters and existing parameters of 18F-FDG PET/CT images in Stage I non-small-cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT). Twenty-six patients with Stage I NSCLC (T1-2N0M0) were retrospectively analyzed. All of the patients underwent an 18F-FDG PET/CT scan before treatment and were treated with SBRT. Each tumor was delineated using PET Edge (MIM Software Inc., Cleveland, OH), and texture parameters were calculated using open-source code CGITA. From 18F-FDG PET/CT images, three conventional parameters, including maximum standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), and four texture parameters, including entropy and dissimilarity (derived from a co-occurrence matrix) and high-intensity large-area emphasis (HILAE) and zone percentage (derived from a size-zone matrix) were analyzed. Reproducibility was evaluated using two independent delineations conducted by two observers. The ability to predict local control (LC), progression-free survival (PFS) and overall survival (OS) was tested for each parameter. All of the seven parameters except zone percentage showed good reproducibility, with intraclass correlation coefficient values >0.8. In univariate analysis, only HILAE was a significant predictor for LC. Histology, dose fractionation, and maximum SUV were associated with PFS, and histology and dose fractionation were associated with OS. We showed that texture parameters derived from 18F-FDG PET/CT were reproducible and potentially beneficial for predicting LC in Stage I lung cancer patients treated with SBRT.

CONSORT-Independent prognostic value of asphericity of pretherapeutic F-18 FDG uptake by primary tumors in patients with breast cancer

BACKGROUND

The aim of this study was to evaluate the prognostic implication of asphericity (ASP); spatial irregularity; of pretherapeutic F 2-deoxy-2-fluoro-D-glucose (F FDG) tumor uptake in patients with invasive ductal carcinoma (IDC) of the breast.

METHODS

One hundred thirty-one female IDC patients (mean age = 48.1 ± 10.4 years), with pathological tumor size greater than 2 cm were retrospectively evaluated using F FDG positron emission tomography/computed tomography (PET/CT). ASP of F FDG distribution was calculated on the basis of the deviation of the tumor shape from spherical symmetry. Progression-free survival (PFS) was predicted on the basis of the univariate and multivariate analyses of the measured clinicopathologic factors and metabolic PET parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG)].

RESULTS

The PFS rate among the 131 patients was 90.1%. The mean follow-up time was 50 months for the entire study cohort and 26 months for the patients with recurrent disease. It is evident from the univariate analysis that N stage, hormonal receptor (Estrogen, ER/Progesterone, PR) status, MTV (≤4.2 mL), and ASP (≤15.1%) affected the PFS. Hazard ratios (HRs) estimated from the multivariate Cox regression analysis show that N stage (HR = 17.6), ASP (HR = 11.9), and hormonal receptor status (HR = 6.9) were independent prognostic factors in predicting PFS. In the subgroup of patients with lymph node metastasis, ASP (HR = 10.9) and hormonal receptor status (HR = 9.1) were independent prognostic factors for PFS.

CONCLUSION

ASP of F FDG uptake is an independent predictor of outcome in IDC patients, and can be used for prognostic stratification.

Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer

Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk assessment and the quantification of intratumoural heterogeneity. In this work, 1615 radiomic features (quantifying tumour image intensity, shape, texture) extracted from pre-treatment FDG-PET and CT images of 300 patients from four different cohorts were analyzed for the risk assessment of locoregional recurrences (LR) and distant metastases (DM) in head-and-neck cancer. Prediction models combining radiomic and clinical variables were constructed via random forests and imbalance-adjustment strategies using two of the four cohorts. Independent validation of the prediction and prognostic performance of the models was carried out on the other two cohorts (LR: AUC = 0.69 and CI = 0.67; DM: AUC = 0.86 and CI = 0.88). Furthermore, the results obtained via Kaplan-Meier analysis demonstrated the potential of radiomics for assessing the risk of specific tumour outcomes using multiple stratification groups. This could have important clinical impact, notably by allowing for a better personalization of chemo-radiation treatments for head-and-neck cancer patients from different risk groups.

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.

Value of Intratumoral Metabolic Heterogeneity and Quantitative 18F-FDG PET/CT Parameters to Predict Prognosis in Patients With HPV-Positive Primary Oropharyngeal Squamous Cell Carcinoma

OBJECTIVE

The aim of this study was to evaluate the impact of intratumoral metabolic heterogeneity and quantitative FDG PET/CT imaging parameters for predicting patient outcomes in primary oropharyngeal squamous cell cancer (OPSCC).

PATIENTS AND METHODS

We retrospectively investigated 105 patients with HPV-positive OPSCC. SUVmax and metabolic tumor volume (MTV) were measured for the primary tumors and when available for the metastatic sites. Primary tumor intratumoral metabolic heterogeneity was calculated as the area under a cumulative SUV volume histograms curve (AUC-CSH). The median follow-up time was 35.4 months (range, 3-92 months). Outcome end point was event-free survival (EFS). Kaplan-Meier survival plots and Cox regression analyses were performed.

RESULTS

Of the 105 patients included, 19 patients relapsed and 11 deceased during the study period. AUC-CSH indexes were associated with EFS using PET gradient-based (P = 0.034) and 50% threshold (P = 0.02) segmentation methods, on multivariate analysis. Kaplan-Meier survival analysis using optimum cutoff of 16.7 SUVmax and 12.7 mL total MTV were significant predictors of EFS. Combining SUVmax and AUC-CSH index in 3 subgroups, patients with higher intratumoral heterogeneity and higher SUVmax were associated with worse outcome (log-rank, P = 0.026). Similarly, patients with higher intratumoral heterogeneity tumors and higher MTV had worse prognosis (log-rank, P = 0.022).

CONCLUSIONS

Intratumoral metabolic heterogeneity using FDG PET was a prognostic factor for EFS in patients with primary HPV (+) OPSCC. The combined predictive effect of FDG avidity, metabolic tumor burden, and intratumoral heterogeneity provided prognostic survival information in these patients.

[18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type

BACKGROUND

In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography.

METHODS

We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV_max), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann-Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis.

RESULTS

Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV_max, the risk of pelvic LN metastasis can be scored accordingly. The TLG_mean was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM).

CONCLUSION

This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG_mean, respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology.

Multiparametric imaging using 18F-FDG PET/CT heterogeneity parameters and functional MRI techniques: prognostic significance in patients with primary advanced oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiotherapy

Background

In this study, PET heterogeneity was combined with functional MRI techniques to refine the prediction of prognosis in patients with oropharyngeal or hypopharyngeal squamous cell carcinoma (OHSCC).

Methods

A total of 124 patients with primary advanced OHSCC who underwent pretreatment ¹⁸F-FDG PET/CT, dynamic contrast-enhanced MR imaging (DCE-MRI), and diffusion-weighted MR imaging (DWI) were enrolled. Conventional and heterogeneity parameters from ¹⁸F-FDG PET as well as perfusion parameters from DCE-MRI and diffusion parameter from DWI of primary tumors were analyzed in relation to recurrence-free survival (RFS) and overall survival (OS).

Results

Multivariate analysis identified hypopharyngeal tumors (P = 0.038), alcohol drinking (P = 0.006), K^trans ≤ 0.5512 (P = 0.017), and K_ep ≤ 0.8872 (P = 0.005) as adverse prognostic factors for RFS. Smoking (p = 0.009), K^trans ≤ 0.5512 (P = 0.0002), K_ep ≤ 0.8872 (P = 0.004), and the PET heterogeneity parameter uniformity ≤ 0.00381 (P = 0.028) were independent predictors of poor OS. The combination of PET uniformity with DCE-MRI parameters and smoking allowed distinguishing four prognostic groups, with 3-year OS rates of 100%, 76.6%, 57.4%, and 7.1%, respectively (P < 0.0001). This prognostic system appeared superior to both the TNM staging system (P = 0.186) and the combination of conventional PET parameters with DCE-MRI (P = 0.004).

Conclusions

Multiparametric imaging based on PET heterogeneity and DCE-MRI parameters combined with clinical risk factors is superior to the concomitant use of functional MRI coupled with conventional PET parameters. This approach may improve the prognostic stratification of OHSCC patients.

Intratumoral Heterogeneity of Pretreatment 18F-FDG PET Images Predict Disease Progression in Patients With Nasal Type Extranodal Natural Killer/T-cell Lymphoma

PURPOSE

The aim of this study was to investigate whether the textural features of pretreatment F-FDG PET images can predict prognosis for nasal type extranodal natural killer/T-cell lymphoma (ENKTL).

MATERIALS AND METHODS

A retrospective analysis of the pretreatment F-FDG PET images of the patients with newly diagnosed nasal type ENKTL from 2008 to 2013 was conducted. Progression-free survival (PFS) was the main outcome measure. The primary tumor was identified and then delineated using the 40% maximum standardized uptake value (SUVmax) thresholding method. The textural features of the pretreatment F-FDG PET images were extracted. The prognostic significance of the textural features of the PET images were examined using the receiver operating characteristic (ROC) curves and Cox regression analysis. P values <0.05 were considered statistically significant.

RESULTS

In total, 17 patients were enrolled, among whom 11 showed disease progression and 6 died from the disease during the median follow-up period of 27.2 months. Dissimilarity and low-intensity short-zone emphasis (LISZE) were identified as independent predictors of PFS by using the ROC curves and multivariate Cox analysis after adjusting for the clinical variables.

CONCLUSIONS

Dissimilarity and LISZE were the significant predictors of disease progression in patients with nasal type ENKTL and can improve their prognostic stratification.

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.

Correlation of pretreatment 18F-FDG PET tumor textural features with gene expression in pharyngeal cancer and implications for radiotherapy-based treatment outcomes

PURPOSE

This study investigated the correlation of the matrix heterogeneity of tumors on ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) with gene-expression profiling in patients with pharyngeal cancer and determined the prognostic factors for radiotherapy-based treatment outcomes.

METHODS

We retrospectively reviewed the records of 57 patients with stage III-IV oropharyngeal or hypopharyngeal cancer who had completed definitive therapy. Four groups of the textural features as well as 31 indices were studied in addition to maximum standard uptake value, metastatic tumor volume, and total lesion glycolysis. Immunohistochemical data from pretreatment biopsy specimens (Glut1, CAIX, VEGF, HIF-1α, EGFR, Ki-67, Bcl-2, CLAUDIN-4, YAP-1, c-Met, and p16) were analyzed. The relationships between the indices and genomic expression were studied, and the robustness of various textural features relative to cause-specific survival and primary relapse-free survival was analyzed.

RESULTS

The overexpression of VEGF was positively associated with the increased values of the matrix heterogeneity obtained using gray-level nonuniformity for zone (GLNUz) and run-length nonuniformity (RLNU). Advanced T stage (p = 0.01, hazard ratio [HR] = 3.38), a VEGF immunoreactive score of >2 (p = 0.03, HR = 2.79), and a higher GLNUz value (p = 0.04, HR = 2.51) were prognostic factors for low cause-specific survival, whereas advanced T stage, a HIF-1α staining percentage of ≥80%, and a higher GLNUz value were prognostic factors for low primary-relapse free survival.

CONCLUSIONS

The overexpression of VEGF was associated with the increased matrix index of GLNUz and RLNU. For patients with pharyngeal cancer requiring radiotherapy, the treatment outcome can be stratified according to the textural features, T stage, and biomarkers.

Overview of the predictive value of quantitative 18 FDG PET in head and neck cancer treated with chemoradiotherapy

18 F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) allows to quantify the metabolic activity of a tumor (glycolysis) and has become a reference tool in oncology for the staging, restaging, radiotherapy planning and monitoring response in many cancers. Quantitative analyses have been introduced in order to overcome some of the limits of the visual methods, allowing an easier and more objective comparison of the inter- and intra-patients variations. The aims of this review were to report available evidences on the clinical value of quantitative PET/CT parameters in HNC. Forty-five studies, for a total of 2928 patients, were analyzed. Most of the data available dealt with the intensity of the metabolism, calculated from the Standard Uptake Value (SUV). Metabolic Tumor Volume (MTV) was well correlated with overall survival and disease free survival, with a higher predictive value than the maximum SUV. Spatial distribution of metabolism and textural analyses seems promising.

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.

Texture analysis of 18F-FDG PET/CT to predict tumour response and prognosis of patients with esophageal cancer treated by chemoradiotherapy

PURPOSE

This retrospective study was done to examine whether the heterogeneity in primary tumour F-18-fluorodeoxyglucose (¹⁸F-FDG) distribution can predict tumour response and prognosis of patients with esophageal cancer treated by chemoradiotherapy (CRT).

METHODS

The enrolled 52 patients with esophageal cancer underwent ¹⁸F-FDG-PET/CT studies before CRT. SUVmax, SUVmean, metabolic tumour volume (MTV, SUV ≥ 2.5), total lesion glycolysis (TLG) and six heterogeneity parameters assessed by texture analysis were obtained. Patients were classified as responders or non-responders according to Response Evaluation Criteria in Solid Tumors. Progression-free survival (PFS) and overall survival (OS) were calculated by the Kaplan-Meier method. Prognostic significance was assessed by Cox proportional hazards analysis.

RESULTS

Thirty four non-responders showed significantly higher MTV (p = 0.006), TLG (p = 0.007), intensity variability (IV; p = 0.003) and size-zone variability (SZV; p = 0.004) than 18 responders. The positive and negative predictive values for non-responders were 77 % and 69 % in MTV, 76 % and 100 % in TLG, 78 % and 67 % in IV and 78 % and 82 % in SZV, respectively. Although PFS and OS were significantly shorter in patients with high MTV (PFS, p = 0.018; OS, p = 0.014), TLG (PFS, p = 0.009; OS, p = 0.025), IV (PFS, p = 0.013; OS, p = 0.007) and SZV (PFS, p = 0.010; OS, p = 0.007) at univariate analysis, none of them was an independent factor, while lymph node status, stage and tumour response status were independent factors at multivariate analysis.

CONCLUSION

Texture features IV and SZV, and volumetric parameters MTV and TLG can predict tumour response, but all of them have limited value in prediction of prognosis of patients with esophageal cancer treated by CRT.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials

Purpose

This study aimed to investigate the variability of textural features (TF) as a function of acquisition and reconstruction parameters within the context of multi-centric trials.

Methods

The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT ⁶⁸Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV) or the absolute deviation (for the noise study) was derived and compared statistically with SUVmax and SUVmean results.

Results

The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP). When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE.

Conclusion

Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials.

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.

Respiration-Averaged CT for Attenuation Correction of PET Images - Impact on PET Texture Features in Non-Small Cell Lung Cancer Patients

PURPOSE

We compared attenuation correction of PET images with helical CT (PET/HCT) and respiration-averaged CT (PET/ACT) in patients with non-small-cell lung cancer (NSCLC) with the goal of investigating the impact of respiration-averaged CT on 18F FDG PET texture parameters.

MATERIALS AND METHODS

A total of 56 patients were enrolled. Tumors were segmented on pretreatment PET images using the adaptive threshold. Twelve different texture parameters were computed: standard uptake value (SUV) entropy, uniformity, entropy, dissimilarity, homogeneity, coarseness, busyness, contrast, complexity, grey-level nonuniformity, zone-size nonuniformity, and high grey-level large zone emphasis. Comparisons of PET/HCT and PET/ACT were performed using Wilcoxon signed-rank tests, intraclass correlation coefficients, and Bland-Altman analysis. Receiver operating characteristic (ROC) curves as well as univariate and multivariate Cox regression analyses were used to identify the parameters significantly associated with disease-specific survival (DSS). A fixed threshold at 45% of the maximum SUV (T45) was used for validation.

RESULTS

SUV maximum and total lesion glycolysis (TLG) were significantly higher in PET/ACT. However, texture parameters obtained with PET/ACT and PET/HCT showed a high degree of agreement. The lowest levels of variation between the two modalities were observed for SUV entropy (9.7%) and entropy (9.8%). SUV entropy, entropy, and coarseness from both PET/ACT and PET/HCT were significantly associated with DSS. Validation analyses using T45 confirmed the usefulness of SUV entropy and entropy in both PET/HCT and PET/ACT for the prediction of DSS, but only coarseness from PET/ACT achieved the statistical significance threshold.

CONCLUSIONS

Our results indicate that 1) texture parameters from PET/ACT are clinically useful in the prediction of survival in NSCLC patients and 2) SUV entropy and entropy are robust to attenuation correction methods.

Intratumoral heterogeneity of (18)F-FDG uptake predicts survival in patients with pancreatic ductal adenocarcinoma

PURPOSE

To assess whether intratumoral heterogeneity measured by (18)F-FDG PET texture analysis has potential as a prognostic imaging biomarker in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

We evaluated a cohort of 137 patients with newly diagnosed PDAC who underwent pretreatment (18)F-FDG PET/CT from January 2008 to December 2010. First-order (histogram indices) and higher-order (grey-level run length, difference, size zone matrices) textural features of primary tumours were extracted by PET texture analysis. Conventional PET parameters including metabolic tumour volume (MTV), total lesion glycolysis (TLG), and standardized uptake value (SUV) were also measured. To assess and compare the predictive performance of imaging biomarkers, time-dependent receiver operating characteristic (ROC) curves for censored survival data and areas under the ROC curve (AUC) at 2 years after diagnosis were used. Associations between imaging biomarkers and overall survival were assessed using Cox proportional hazards regression models.

RESULTS

The best imaging biomarker for overall survival prediction was first-order entropy (AUC = 0.720), followed by TLG (AUC = 0.697), MTV (AUC = 0.692), and maximum SUV (AUC = 0.625). After adjusting for age, sex, clinical stage, tumour size and serum CA19-9 level, multivariable Cox analysis demonstrated that higher entropy (hazard ratio, HR, 5.59; P = 0.028) was independently associated with worse survival, whereas TLG (HR 0.98; P = 0.875) was not an independent prognostic factor.

CONCLUSION

Intratumoral heterogeneity of (18)F-FDG uptake measured by PET texture analysis is an independent predictor of survival along with tumour stage and serum CA19-9 level in patients with PDAC. In addition, first-order entropy as a measure of intratumoral metabolic heterogeneity is a better quantitative imaging biomarker of prognosis than conventional PET parameters.

18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer

Purpose

Texture indices (TI) calculated from 18F-FDG PET tumor images show promise for predicting response to therapy and survival. Their calculation involves a resampling of standardized uptake values (SUV) within the tumor. This resampling can be performed differently and significantly impacts the TI values. Our aim was to investigate how the resampling approach affects the ability of TI to reflect tissue-specific pattern of metabolic activity.

Methods

18F-FDG PET were acquired for 48 naïve-treatment patients with non-small cell lung cancer and for a uniform phantom. We studied 7 TI, SUVmax and metabolic volume (MV) in the phantom, tumors and healthy tissue using the usual relative resampling (RR) method and an absolute resampling (AR) method. The differences in TI values between tissue types and cancer subtypes were investigated using Wilcoxon’s tests.

Results

Most RR-based TI were highly correlated with MV for tumors less than 60 mL (Spearman correlation coefficient r between 0.74 and 1), while this correlation was reduced for AR-based TI (r between 0.06 and 0.27 except for RLNU where r = 0.91). Most AR-based TI were significantly different between tumor and healthy tissues (pvalues <0.01 for all 7 TI) and between cancer subtypes (pvalues<0.05 for 6 TI). Healthy tissue and adenocarcinomas exhibited more homogeneous texture than tumor tissue and squamous cell carcinomas respectively.

Conclusion

TI computed using an AR method vary as a function of the tissue type and cancer subtype more than the TI involving the usual RR method. AR-based TI might be useful for tumor characterization.

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards

Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes.

Heterogeneity of (18)F-FDG PET combined with expression of EGFR may improve the prognostic stratification of advanced oropharyngeal carcinoma

The Ang's risk profile (based on p16, smoking and cancer stage) is a well-known prognostic factor in oropharyngeal squamous cell carcinoma (OPSCC). Whether heterogeneity in (18)F-fluorodeoxyglucose (FDG) positron emission tomographic (PET) images and epidermal growth factor receptor (EGFR) expression could provide additional information on clinical outcomes in advanced-stage OPSCC was investigated. Patients with stage III-IV OPSCC who completed primary therapy were eligible. Zone-size nonuniformity (ZSNU) extracted from pretreatment FDG PET scans was used as an index of image heterogeneity. EGFR and p16 expression were examined by immunohistochemistry. Disease-specific survival (DSS) and overall survival (OS) served as outcome measures. Kaplan-Meier estimates and Cox proportional hazards regression models were used for survival analysis. A bootstrap resampling technique was applied to investigate the stability of outcomes. Finally, a recursive partitioning analysis (RPA)-based model was constructed. A total of 113 patients were included, of which 28 were p16-positive. Multivariate analysis identified the Ang's profile, EGFR and ZSNU as independent predictors of both DSS and OS. Using RPA, the three risk factors were used to devise a prognostic scoring system that successfully predicted DSS in both p16-positive and -negative cases. The c-statistic of the prognostic index for DSS was 0.81, a value which was significantly superior to both AJCC stage (0.60) and the Ang's risk profile (0.68). In patients showing an Ang's high-risk profile (N = 77), the use of our scoring system clearly identified three distinct prognostic subgroups. It was concluded that a novel index may improve the prognostic stratification of patients with advanced-stage OPSCC.