Prognostic Value of Tumor Heterogeneity and SUVmax of Pretreatment 18F-FDG PET/CT for Salivary Gland Carcinoma With High-Risk Histology

Postradiotherapy Response Assessment Using 18F-FDG PET/CT in Salivary Gland Carcinoma-A Multicenter Study

PURPOSE

This multicenter study investigates the efficacy of 18F-FDG PET/CT in postradiotherapy (post-RT) response evaluation in salivary gland carcinoma (SGC).

METHODS

We retrospectively reviewed 115 SGC patients who underwent definitive or adjuvant RT followed by 18F-FDG PET/CT between 2004 and 2021. Most tumors were parotid gland malignancies (50%). The most common histological subtypes were adenoid cystic (29%) and mucoepidermoid carcinomas (18%).

RESULTS

The median follow-up was 65 months. Post-RT anatomic images (CT/MRI) revealed complete response (CR) in 51 patients (44%). Among 53 patients with partial response or stable disease, only 17 (32%) patients experienced locoregional recurrence, with a 5-year locoregional control rate of 69%. Post-RT 18F-FDG PET/CT documented metabolic CR in 81 patients (70%). Metabolic complete responders had significantly higher 5-year locoregional control (90% vs 43%), distant metastasis-free survival (80% vs 48%), progression-free survival (76% vs 24%), and overall survival rates (89% vs 42%) compared with non-complete responders (all P < 0.001), as confirmed in both univariate and multivariate analyses. It identified additional viable tumors in 18 cases (16%) and facilitated salvage local therapies in 7 patients (6%). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of post-RT 18F-FDG PET/CT were 63%, 91%, 70%, 88%, and 84%, respectively, in predicting locoregional recurrence. 18F-FDG PET/CT showed significantly higher sensitivity (88% vs 36%, P = 0.011) in tumors with pre-RT SUVmax ≥7.39 compared with those with SUVmax <7.39.

CONCLUSIONS

Post-RT 18F-FDG PET/CT demonstrates high negative predictive value and specificity, with metabolic CR predicting excellent outcomes. Additionally, it exhibits higher sensitivity for high-SUVmax SGC, facilitating early detection of viable tumors.

Applying deep learning-based ensemble model to [18F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases

OBJECTIVES

To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[18F]fluoro-D-glucose ([18F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs).

MATERIALS AND METHODS

This retrospective study included 62 patients with 63 PGDs who underwent pretreatment [18F]-FDG-PET/computed tomography (CT). The lesions were assigned to the training (n = 44) and testing (n = 19) cohorts. In total, 49 [18F]-FDG-PET-based radiomic features were utilized to differentiate benign from malignant PGDs using five different conventional ML algorithmic models (random forest, neural network, k-nearest neighbors, logistic regression, and support vector machine) and the deep learning (DL)-based ensemble ML model. In the training cohort, each conventional ML model was constructed using the five most important features selected by the recursive feature elimination method with the tenfold cross-validation and synthetic minority oversampling technique. The DL-based ensemble ML model was constructed using the five most important features of the bagging and multilayer stacking methods. The area under the receiver operating characteristic curves (AUCs) and accuracies were used to compare predictive performances.

RESULTS

In total, 24 benign and 39 malignant PGDs were identified. Metabolic tumor volume and four GLSZM features (GLSZM_ZSE, GLSZM_SZE, GLSZM_GLNU, and GLSZM_ZSNU) were the five most important radiomic features. All five features except GLSZM_SZE were significantly higher in malignant PGDs than in benign ones (each p < 0.05). The DL-based ensemble ML model had the best performing classifier in the training and testing cohorts (AUC = 1.000, accuracy = 1.000 vs AUC = 0.976, accuracy = 0.947).

CONCLUSIONS

The DL-based ensemble ML model using [18F]-FDG-PET-based radiomic features can be useful for differentiating benign from malignant PGDs. The DL-based ensemble ML model using [18F]-FDG-PET-based radiomic features can overcome the previously reported limitation of [18F]-FDG-PET/CT scan for differentiating benign from malignant PGDs. The DL-based ensemble ML approach using [18F]-FDG-PET-based radiomic features can provide useful information for managing PGD.

Intratumoral metabolic heterogeneity by 18F-FDG PET/CT to predict prognosis for patients with thymic epithelial tumors

BACKGROUND

The aim of the present study was to evaluate the impact of intratumoral metabolic heterogeneity and quantitative 18F-FDG PET/CT imaging parameters in predicting patient outcomes in thymic epithelial tumors (TETs).

METHODS

This retrospective study included 100 patients diagnosed with TETs who underwent pretreatment 18F-FDG PET/CT. The maximum and mean standardized uptake values (SUVmax and SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on PET/CT were measured. Heterogeneity index-1 (HI-1; standard deviation [SD] divided by SUVmean) and heterogeneity index-2 (HI-2; linear regression slopes of the MTV according with different SUV thresholds), were evaluated as heterogeneity indices. Associations between these parameters and patient survival outcomes were analyzed.

RESULTS

The univariate analysis showed that Masaoka stage, TNM stage, WHO classification, SUVmax, SUVmean, TLG, and HI-1 were significant prognostic factors for progression-free survival (PFS), while MTV, HI-2, age, gender, presence of myasthenia gravis, and maximum tumor diameter were not. Subsequently, multivariate analyses showed that HI-1 (p < 0.001) and TNM stage (p = 0.002) were independent prognostic factors for PFS. For the overall survival analysis, TNM stage, WHO classification, SUVmax, and HI-1 were significant prognostic factors in the univariate analysis, while TNM stage remained an independent prognostic factor in multivariate analyses (p = 0.024). The Kaplan Meier survival analyses showed worse prognoses for patients with TNM stages III and IV and HI-1 ≥ 0.16 compared to those with stages I and II and HI-1 < 0.16 (log-rank p < 0.001).

CONCLUSION

HI-1 and TNM stage were independent prognostic factors for progression-free survival in TETs. HI-1 generated from baseline 18F-FDG PET/CT might be promising to identify patients with poor prognosis.

Insights Into Pediatric Secretory Carcinoma of the Salivary Gland: A Case Report

Secretory carcinoma of the salivary gland (SCSG) is a rare head and neck tumor in adults and exceptional at the pediatric age. Its varied histological subtypes and distinct clinical presentation pose diagnostic and therapeutic challenges. Therefore, standardized guidelines are of utmost importance for the care of these patients, especially in children. Here we present an 11-year-old male presented with a left cheek mass initially diagnosed as lipoma. A wide resection was performed and SCSG was revealed in the histopathologic and immunohistochemistry analysis. The presentation of this case provides valuable information on the diagnostic and therapeutic complexities of SCSG. It emphasizes the need for standardized guidelines and further research to optimize pediatric patient outcomes. Overall, this case report is a crucial resource for clinicians and researchers, highlighting the importance of interdisciplinary collaboration and early intervention in managing SCSG.

Unexpected focal fluorodeoxyglucose uptake in main organs; pass through or pass by?

Since the inception of fluorine-18 fluorodeoxyglucose (F-18 FDG), positron emission tomography/computed tomography (PET/CT) utilizing F-18 FDG has become widely accepted as a valuable imaging modality in the field of oncology, with global prevalence in clinical practice. Given that a single Torso PET/CT scan encompasses the anatomical region from the skull base to the upper thigh, the detection of incidental abnormal focal hypermetabolism in areas of limited clinical interest is both feasible and not uncommon. Numerous investigations have been undertaken to delineate the distinctive features of these findings, yet the outcomes have proven inconclusive. The incongruent results of these studies present a challenge for physicians, leaving them uncertain about the appropriate course of action. This article provides a succinct overview of the characteristics of fluorodeoxyglucose, followed by a comprehensive discussion of the imaging findings and clinical significance associated with incidental focal abnormal F-18 FDG activity in several representative organs. In conclusion, while the prevalence of unrecognized malignancy varies across organs, malignancies account for a substantial proportion, ranging from approximately one-third to over half, of incidental focal uptake. In light of these rates, physicians are urged to exercise vigilance in not disregarding unexpected uptake, facilitating more assured clinical decisions, and advocating for further active evaluation.

A multicenter retrospective analysis of patients with salivary gland carcinoma treated with postoperative radiotherapy alone or chemoradiotherapy

BACKGROUND

The aim of this study was to interrogate if the use of postoperative chemoradiotherapy (POCRT) correlated with superior oncological outcomes for certain subgroups of patients with high-risk salivary gland carcinoma (SGC), compared with postoperative radiotherapy (PORT) alone.

METHODS

This multicenter retrospective study included 411 patients with surgically resected SGC who underwent PORT (n = 263) or POCRT (n = 148) between 2000 and 2015. Possible correlations of clinical parameters with outcomes were examined using the Kaplan-Meier analysis and Cox proportional-hazards regression model.

RESULTS

The median follow-up of survivors is 10.9 years. For the entire cohort, adding concurrent chemotherapy to PORT was not associated with OS, PFS, or LRC improvement. However, patients with nodal metastasis who underwent POCRT had significantly higher 10-year OS (46.2% vs. 18.2%, P = 0.009) and PFS (38.7% vs. 10.0%, P = 0.009) rates than those treated with PORT alone. The presence of postoperative macroscopic residual tumor (R2 resection) was identified as an independent prognosticator for inferior OS (P = 0.032), PFS (P = 0.001), and LRC (P = 0.007). Importantly, POCRT significantly correlated with higher 10-year LRC rates in patients with R2 resection (74.2% vs. 40.7%, P = 0.034) or adenoid cystic carcinoma (AdCC, 97.6% vs. 83.6%, P = 0.039). On multivariate analyses, the use of POCRT significantly predicted superior OS (P = 0.037) and PFS (P = 0.013) for node-positive patients and LRC for patients with R2 resection (P = 0.041) or AdCC (P = 0.005).

CONCLUSIONS

For surgically resected SGC, POCRT was associated with improved long-term OS and PFS for patients with nodal metastasis and superior LRC for patients with R2 resection or AdCC.

The Use of Radiomic Features to Predict Human Papillomavirus (HPV) Status in Head and Neck Tumors: A Review

Head and neck cancers represent a significant source of morbidity and mortality across the world. The individual genetic makeup of each tumor can help to determine the course of treatment and can help clinicians predict prognosis. Non-invasive tools to determine the genetic status of these tumors, particularly p16 (human papillomavirus (HPV)) status could prove extremely valuable to treating clinicians and surgeons. The field of radiomics is a burgeoning area of radiology practice that aims to provide quantitative biomarkers that can be derived from radiological images and could prove useful in determining p16 status non-invasively. In this review, we summarize the current evidence for the use of radiomics to determine the HPV status of head and neck tumors. .

Metabolic activity grows in human cancers pushed by phenotypic variability

Different evolutionary processes push cancers to increasingly aggressive behaviors, energetically sustained by metabolic reprogramming. The collective signature emerging from this transition is macroscopically displayed by positron emission tomography (PET). In fact, the most readily PET measure, the maximum standardized uptake value (SUV_max), has been found to have prognostic value in different cancers. However, few works have linked the properties of this metabolic hotspot to cancer evolutionary dynamics. Here, by analyzing diagnostic PET images from 512 patients with cancer, we found that SUV_max scales superlinearly with the mean metabolic activity (SUV_mean), reflecting a dynamic preferential accumulation of activity on the hotspot. Additionally, SUV_max increased with metabolic tumor volume (MTV) following a power law. The behavior from the patients data was accurately captured by a mechanistic evolutionary dynamics model of tumor growth accounting for phenotypic transitions. This suggests that non-genetic changes may suffice to fuel the observed sustained increases in tumor metabolic activity.

Significance of incidental focal fluorine-18 fluorodeoxyglucose uptake in colon/rectum, thyroid, and prostate: With a brief literature review

BACKGROUND

Fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT), a functional imaging method, is usually performed on the entire torso, and regions of unexpected suspicious focal hypermetabolism are not infrequently observed. Among the regions, colon, thyroid, and prostate were found to be the common organs in a recent umbrella review. Some studies reported that a high rate of malignancy was shown in incidentally identified focal hypermetabolic regions and suggested that further examinations should not be ignored.

AIM

To investigate the malignancy rate of incidental focal FDG uptake, useful PET parameters and their cutoffs in discrimination between malignant and benign lesions.

METHODS

Retrospectively, the final reports of 16510 F-18 FDG PET/CT scans performed at our hospital between January 2016 and March 2022 were reviewed to identify incidentally observed FDG uptake in the colon/rectum, thyroid, and prostate. The scans of patients with current or prior malignancies at each corresponding location, without the final reports of histopathology or colonoscopy (for colon and rectum) for the corresponding hypermetabolic regions, or with diffuse (not focal) hypermetabolism were excluded. Finally, 88 regions of focal colorectal hypermetabolism in 85 patients (48 men and 37 women with mean age 67.0 ± 13.4 years and 63.4 ± 15.8 years, respectively), 48 focal thyroid uptakes in 48 patients (12 men and 36 women with mean age 62.2 ± 13.1 years and 60.8 ± 12.4 years, respectively), and 39 focal prostate uptakes in 39 patients (mean age 71.8 ± 7.5 years) were eligible for this study. For those unexpected focal hypermetabolic regions, rates of malignancy were calculated, PET parameters, such as standardized uptake value (SUV), capable of distinguishing between malignant and benign lesions were investigated, and the cutoffs of those PET parameters were determined by plotting receiver operating characteristic curves.

RESULTS

In the colon and rectum, 29.5% (26/88) were malignant and 33.0% (29/88) were premalignant lesions. Both SUVmax and SUVpeak differentiated malignant/premalignant from benign lesions, however, no parameters could distinguish malignant from premalignant lesions. Higher area under the curve was shown with SUVmax (0.752, 95%CI: 0.649-0.856, P < 0.001) and the cutoff was 7.6. In the thyroid, 60.4% (29/48) were malignant. The majority were well-differentiated thyroid cancers (89.7%, 26/29). The results of BRAF mutation tests were available for 20 of the 26 well-differentiated thyroid cancers and all 20 had the mutation. Solely SUVmax differentiated malignant from benign lesions and the cutoff was 6.9. In the prostate, 56.4% (22/39) were malignant. Only SUVmax differentiated malignant from benign lesions and the cutoff was 3.8. Overall, among the 175 focal hypermetabolic regions, 60.6% (106/175) were proven to be malignant and premalignant (in colon and rectum) lesions.

CONCLUSION

Approximately 60% of the incidentally observed focal F-18 FDG uptake in the colon/rectum, thyroid, and prostate were found to be malignant. Of the several PET parameters, SUVmax was superior to others in distinguishing between malignant/premalignant and benign lesions. Based on these findings, incidental focal hypermetabolism should not be ignored and lead physicians to conduct further investigations with greater confidence.

Assessing dynamic metabolic heterogeneity in non-small cell lung cancer patients via ultra-high sensitivity total-body [18F]FDG PET/CT imaging: quantitative analysis of [18F]FDG uptake in primary tumors and metastatic lymph nodes

PURPOSE

This study aimed to quantitatively assess [¹⁸F]FDG uptake in primary tumor (PT) and metastatic lymph node (mLN) in newly diagnosed non-small cell lung cancer (NSCLC) using the total-body [¹⁸F]FDG PET/CT and to characterize the dynamic metabolic heterogeneity of NSCLC.

METHODS

The 60-min dynamic total-body [¹⁸F]FDG PET/CT was performed before treatment. The PTs and mLNs were manually delineated. An unsupervised K-means classification method was used to cluster patients based on the imaging features of PTs. The metabolic features, including Patlak-Ki, Patlak-Intercept, SUV_mean, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and textural features, were extracted from PTs and mLNs. The targeted next-generation sequencing of tumor-associated genes was performed. The expression of Ki67, CD3, CD8, CD34, CD68, and CD163 in PTs was determined by immunohistochemistry.

RESULTS

A total of 30 patients with stage IIIA-IV NSCLC were enrolled. Patients were divided into fast dynamic FDG metabolic group (F-DFM) and slow dynamic FDG metabolic group (S-DFM) by the unsupervised K-means classification of PTs. The F-DFM group showed significantly higher Patlak-Ki (P < 0.001) and SUV_mean (P < 0.001) of PTs compared with the S-DFM group, while no significant difference was observed in Patlak-Ki and SUV_mean of mLNs between the two groups. The texture analysis indicated that PTs in the S-DFM group were more heterogeneous in FDG uptake than those in the F-DFM group. Higher T cells (CD3⁺/CD8⁺) and macrophages (CD68⁺/CD163⁺) infiltration in the PTs were observed in the F-DFM group. No significant difference was observed in tumor mutational burden between the two groups.

CONCLUSION

The dynamic total-body [¹⁸F]FDG PET/CT stratified NSCLC patients into the F-DFM and S-DFM groups, based on Patlak-Ki and SUV_mean of PTs. PTs in the F-DFM group seemed to be more homogenous in terms of [¹⁸F]FDG uptake than those in the S-DFM group. The higher infiltrations of T cells and macrophages were observed in the F-DFM group, which suggested a potential benefit from immunotherapy.

Assessment of incidental focal colorectal uptake by analysis of fluorine-18 fluorodeoxyglucose positron emission tomography parameters

BACKGROUND

Colon and rectal cancers are among the top five cancers worldwide in terms of their incidence and mortality rates. As the treatment options for cure include surgery even in specific advanced-stage cases, the early detection of lesions is important for applying active treatment methods. Fluorine-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) is an established imaging study for many types of cancers; however, physiologic uptake in the gastrointestinal tract is a frequent finding and may interfere with lesion identification. Nevertheless, as unexpectedly observed focal colorectal F-18 FDG uptake may harbor malignant lesions, further examination must not be avoided.

AIM

To assess the clinical implications of unexpected focal colorectal F-18 FDG uptake by analyzing FDG PET parameters.

METHODS

A total of 15143 F-18 FDG PET/CT scans performed at our hospital between January 2016 and September 2021 were retrospectively reviewed to identify incidentally observed focal colorectal FDG uptake. Finally, 83 regions showing focal colorectal FDG uptake with final histopathological reports from 80 patients (45 men and 35 women with mean ages of 66.9 ± 10.7 years and 63.7 ± 15.3 years, respectively) were eligible for inclusion in the present study. Each focal hypermetabolic colorectal region was classified as malignant, premalignant, or benign according to the histopathological report. PET parameters such as maximum and peak standardized uptake value (SUVmax and SUVpeak), metabolic tumor volume (MTV), mean SUV of the metabolic tumor volume (mSUVmtv), and total lesion glycolysis (TLG) were measured or calculated for the corresponding hypermetabolic regions. Parametric and non-parametric statistical comparisons of these parameters were performed among the three groups. Receiver operating characteristic curves were plotted to identify cut-off values.

RESULTS

The detection rate of incidental focal colorectal uptake was 0.53% (80/15,143). Of the 83 regions with unexpected focal colorectal hypermetabolism, 28.9% (24/83) were malignant, 32.5% (27/83) were premalignant, and 38.6% (32/83) were benign. Overall, 61.4% of the regions had malignant or premalignant lesions. SUVmax, SUVpeak, and mSUVmtv differentiated malignant and/or premalignant lesions from benign lesions with statistical significance (P < 0.05). mSUVmtv3.5 differentiated malignant from benign lesions, with the largest area under the curve (AUC) of 0.792 and a cut-off of 4.9. SUVmax showed the largest AUC of 0.758 with a cut-off value of 7.5 for distinguishing between premalignant and benign lesions. Overall, SUVmax with a cut-off value of 7.6 (AUC: 0.770, 95% confidence interval (CI): 0.668-0.872; sensitivity, 0.686; specificity, 0.688) was a superior parameter for distinguishing between malignant/premalignant and benign lesions or physiologic uptake. No parameters differentiated malignant from premalignant lesions. Moderate or weak positive correlations were observed between the long diameter of the malignant lesions and PET parameters such as SUVpeak and some mSUVmtv.

CONCLUSION

Approximately two-thirds (61.4%) of incidental focal hypermetabolic colorectal regions were malignant/premalignant lesions, for which SUVmax was an independent diagnostic parameter. Unexpected suspicious focal colorectal FDG uptake should not be avoided and consideration for further evaluation is strongly recommended not to miss the two-thirds.

Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers

Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.

Risk Stratification Using 18F-FDG PET/CT and Artificial Neural Networks in Head and Neck Cancer Patients Undergoing Radiotherapy

This study retrospectively analyzed the performance of artificial neural networks (ANN) to predict overall survival (OS) or locoregional failure (LRF) in HNSCC patients undergoing radiotherapy, based on 2-[¹⁸F]FDG PET/CT and clinical covariates. We compared predictions relying on three different sets of features, extracted from 230 patients. Specifically, (i) an automated feature selection method independent of expert rating was compared with (ii) clinical variables with proven influence on OS or LRF and (iii) clinical data plus expert-selected SUV metrics. The three sets were given as input to an artificial neural network for outcome prediction, evaluated by Harrell’s concordance index (HCI) and by testing stratification capability. For OS and LRF, the best performance was achieved with expert-based PET-features (0.71 HCI) and clinical variables (0.70 HCI), respectively. For OS stratification, all three feature sets were significant, whereas for LRF only expert-based PET-features successfully classified low vs. high-risk patients. Based on 2-[¹⁸F]FDG PET/CT features, stratification into risk groups using ANN for OS and LRF is possible. Differences in the results for different feature sets confirm the relevance of feature selection, and the key importance of expert knowledge vs. automated selection.

Salivary gland carcinoma in children and adolescents: The EXPeRT/PARTNER diagnosis and treatment recommendations

Salivary gland carcinomas (SGCs) are rare during childhood and adolescence. Consequently, no standardized recommendations for the diagnosis and therapeutic management of pediatric SGC are available, and pediatric oncologists and surgeons generally follow adult guidelines. Complete surgical resection with adequate margins constitutes the cornerstone of treatment. However, the indications and modalities of adjuvant therapy remain controversial and may be challenging in view of the potential long-term toxicities in the pediatric population. This paper presents the consensus recommendations for the diagnosis and treatment of children and adolescents with SGCs, established by the European Cooperative Study Group for Pediatric Rare Tumors (EXPeRT) within the EU-funded PARTNER project (Paediatric Rare Tumours Network - European Registry).

Management of Salivary Gland Malignancy: ASCO Guideline

PURPOSE

To provide evidence-based recommendations for practicing physicians and other healthcare providers on the management of salivary gland malignancy.

METHODS

ASCO convened an Expert Panel of medical oncology, surgical oncology, radiation oncology, neuroradiology, pathology, and patient advocacy experts to conduct a literature search, which included systematic reviews, meta-analyses, randomized controlled trials, and prospective and retrospective comparative observational studies published from 2000 through 2020. Outcomes of interest included survival, diagnostic accuracy, disease recurrence, and quality of life. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations.

RESULTS

The literature search identified 293 relevant studies to inform the evidence base for this guideline. Six main clinical questions were addressed, which included subquestions on preoperative evaluations, surgical diagnostic and therapeutic procedures, appropriate radiotherapy techniques, the role of systemic therapy, and follow-up evaluations.

RECOMMENDATIONS

When possible, evidence-based recommendations were developed to address the diagnosis and appropriate preoperative evaluations for patients with a salivary gland malignancy, therapeutic procedures, and appropriate treatment options in various salivary gland histologies.Additional information is available at www.asco.org/head-neck-cancer-guidelines.

A Systematic Review of PET Textural Analysis and Radiomics in Cancer

Background: Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies. Methods: PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted. Results: A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20–1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1–286). Conclusions: PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.

The Performance of a Dual-Energy CT Derived Radiomics Model in Differentiating Serosal Invasion for Advanced Gastric Cancer Patients After Neoadjuvant Chemotherapy: Iodine Map Combined With 120-kV Equivalent Mixed Images

Objectives

The aim was to determine whether the dual-energy CT radiomics model derived from an iodine map (IM) has incremental diagnostic value for the model based on 120-kV equivalent mixed images (120 kVp) in preoperative restaging of serosal invasion with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NAC).

Methods

A total of 155 patients (110 in the training cohort and 45 in the testing cohort) with LAGC who had standard NAC before surgery were retrospectively enrolled. All CT images were analyzed by two radiologists for manual classification. Volumes of interests (VOIs) were delineated semi-automatically, and 1,226 radiomics features were extracted from every segmented lesion in both IM and 120 kVp images, respectively. Spearman's correlation analysis and the least absolute shrinkage and selection operator (LASSO) penalized logistic regression were implemented for filtering unstable and redundant features and screening out vital features. Two predictive models (120 kVp and IM-120 kVp) based on 120 kVp selected features only and 120 kVp combined with IM selected features were established by multivariate logistic regression analysis. We then build a combination model (ComModel) developed with IM-120 kVp signature and ycT. The performance of these three models and manual classification were evaluated and compared.

Result

Three radiomics models showed great predictive accuracy and performance in both the training and testing cohorts (ComModel: AUC: training, 0.953, testing, 0.914; IM-120 kVp: AUC: training, 0.953, testing, 0.879; 120 kVp: AUC: training, 0.940, testing, 0.831). All these models showed higher diagnostic accuracy (ComModel: 88.9%, IM-120 kVp: 84.4%, 120 kVp: 80.0%) than manual classification (68.9%) in the testing group. ComModel and IM-120 kVp model had better performances than manual classification both in the training (both p<0.001) and testing cohorts (p<0.001 and p=0.034, respectively).

Conclusions

Dual-energy CT-based radiomics models demonstrated convincible diagnostic performance in differentiating serosal invasion in preoperative restaging for LAGC. The radiomics features derived from IM showed great potential for improving the diagnostic capability.

Diagnostic value of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography in sublingual and submandibular salivary gland tumors

The aim of the present study was to compare the diagnostic accuracy of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) with that of conventional imaging studies (CIS), such as CT or magnetic resonance imaging (MRI), in the clinical diagnosis and staging of submandibular and sublingual salivary gland tumors. In addition, the data obtained were used to evaluate the significance of maximum standardized uptake value (SUVmax) in diagnosing benign or malignant lesions. For the present study, 18 patients with submandibular or sublingual neoplasms underwent F-18 FDG PET/CT imaging with accompanying CT or MRI. The diagnostic values from 43 F-18 FDG PET/CT scans and 28 CIS of the 18 patients were compared to the gold standard histopathological and/or cytopathological diagnosis. The results demonstrated that the diagnostic accuracy for predicting primary tumors was similar between F-18 FDG PET/CT and CIS. By contrast, PET/CT imaging was more accurate in detecting lymph node metastasis compared with CT or MRI (95.4 vs. 66.7%). F-18 FDG PET/CT had a sensitivity of 88.9% and a specificity of 97.1%, whereas CT or MRI had a sensitivity of 54.5% and a specificity of 75.0%. F-18 FDG PET/CT also enabled screening for distant metastasis, as observed in 10 cases in the present study. Furthermore, there were no significant differences in SUVmax between benign or malignant salivary gland lesions, as high glucose metabolism was also observed in benign tumors. In conclusion, F-18 FDG PET/CT provides more accurate diagnostic information for the evaluation of submandibular and sublingual salivary gland tumors as compared with CIS in terms of lymph node and distant metastasis.

Intratumor Heterogeneity Assessed by 18F-FDG PET/CT Predicts Treatment Response and Survival Outcomes in Patients with Hodgkin Lymphoma

RATIONALE AND OBJECTIVES

Radiomic analysis of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) images enables the extraction of quantitative information of intratumour heterogeneity. This study investigated whether the baseline ¹⁸F-FDG PET/CT radiomics can predict treatment response and survival outcomes in patients with Hodgkin lymphoma (HL).

MATERIALS AND METHODS

Thirty-five patients diagnosed with HL who underwent ¹⁸F-FDG PET/CT scans before and during chemotherapy were retrospectively enrolled in this investigation. For each patient, we extracted 709 radiomic features from pretreatment PET/CT images. Clinical variables (age, gender, B symptoms, bulky tumor, and disease stage) and radiomic signatures (intensity, texture, and wavelet) were analyzed according to response to therapy, progression-free survival (PFS), and overall survival (OS). Receiver operating characteristic curve, logistic regression, and Cox proportional hazards model were used to examine potential predictive and prognostic factors.

RESULTS

High-intensity run emphasis (HIR) of PET and run-length nonuniformity (RLNU) of CT extracted from gray-level run-length matrix (GLRM) in high-frequency wavelets were independent predictive factors for the treatment response (odds ratio [OR] = 36.4, p = 0.014; OR = 30.4, p = 0.020). Intensity nonuniformity (INU) of PET and wavelet short run emphasis (SRE) of CT from GLRM and Ann Arbor stage were independently related to PFS (hazard ratio [HR] = 9.29, p = 0.023; HR = 18.40, p = 0.012; HR = 7.46, p = 0.049). Zone-size nonuniformity (ZSNU) of PET from gray-level size zone matrix (GLSZM) was independently associated with OS (HR = 41.02, p = 0.001). Based on these factors, a prognostic stratification model was devised for the risk stratification of patients. The proposed model allowed the identification of four risk groups for PFS and OS (p < 0.001 and p < 0.001).

CONCLUSION

HIR_{_}GLRM_PET and RLNU_{_}GLRM_CT in high-frequency wavelets serve as independent predictive factors for treatment response. ZSNU_{_}GLSZM_PET, INU_{_}GLRM_PET, and wavelet SRE_{_}GLRM_CT serve as independent prognostic factors for survival outcomes. The present study proposes a prognostic stratification model that may be clinically beneficial in guiding risk-adapted treatment strategies for patients with HL.

Development and validation of a prognostic model incorporating [18F]FDG PET/CT radiomics for patients with minor salivary gland carcinoma

OBJECTIVES

The aim of this study was to develop and validate a prognostic model incorporating [¹⁸F]FDG PET/CT radiomics for patients of minor salivary gland carcinoma (MSGC).

METHODS

We retrospectively reviewed the pretreatment [¹⁸F]FDG PET/CT images of 75 MSGC patients treated with curative intent. Using a 1.5:1 ratio, the patients were randomly divided into a training and validation group. The main outcome measurements were overall survival (OS) and relapse-free survival (RFS). All of the patients were followed up for at least 30 months or until death. Following segmentation of tumors and lymph nodes on PET images, radiomic features were extracted. The prognostic significance of PET radiomics and clinical parameters in the training group was examined using receiver operating characteristic curve analysis. Variables showing a significant impact on OS and RFS were entered into multivariable Cox regression models. Recursive partitioning analysis was subsequently implemented to devise a prognostic index, whose performance was examined in the validation group. Finally, the performance of the index was compared with clinical variables in the entire cohort and nomograms for surgically treated cases.

RESULTS

The training and validation groups consisted of 45 and 30 patients, respectively. The median follow-up time in the entire cohort was 59.5 months. Eighteen relapse, 19 dead, and thirteen relapse, eight dead events were found in the training and validation cohorts, respectively. In the training group, two factors were identified as independently associated with poor OS, i.e., (1) tumors with both high maximum standardized uptake value (SUV_max) and discretized intensity entropy and (2) poor performance status or N2c-N3 stage. A prognostic model based on the above factors was devised and showed significant higher concordance index (C-index) for OS than those of AJCC stage and high-risk histology (C-index: 0.83 vs. 0.65, P = 0.005; 0.83 vs. 0.54, P < 0.001, respectively). This index also demonstrated superior performance than nomogram for OS (C-index: 0.88 vs. 0.70, P = 0.017) and that for RFS (C-index: 0.87 vs. 0.72, P = 0.004).

CONCLUSIONS

We devised a novel prognostic model that incorporates [¹⁸F]FDG PET/CT radiomics and may help refine outcome prediction in patients with MSGC.

Recent advances of PET imaging in clinical radiation oncology

Radiotherapy and radiation oncology play a key role in the clinical management of patients suffering from oncological diseases. In clinical routine, anatomic imaging such as contrast-enhanced CT and MRI are widely available and are usually used to improve the target volume delineation for subsequent radiotherapy. Moreover, these modalities are also used for treatment monitoring after radiotherapy. However, some diagnostic questions cannot be sufficiently addressed by the mere use standard morphological imaging. Therefore, positron emission tomography (PET) imaging gains increasing clinical significance in the management of oncological patients undergoing radiotherapy, as PET allows the visualization and quantification of tumoral features on a molecular level beyond the mere morphological extent shown by conventional imaging, such as tumor metabolism or receptor expression. The tumor metabolism or receptor expression information derived from PET can be used as tool for visualization of tumor extent, for assessing response during and after therapy, for prediction of patterns of failure and for definition of the volume in need of dose-escalation. This review focuses on recent and current advances of PET imaging within the field of clinical radiotherapy / radiation oncology in several oncological entities (neuro-oncology, head & neck cancer, lung cancer, gastrointestinal tumors and prostate cancer) with particular emphasis on radiotherapy planning, response assessment after radiotherapy and prognostication.

Treatment-related changes in neuroendocrine tumors as assessed by textural features derived from 68Ga-DOTATOC PET/MRI with simultaneous acquisition of apparent diffusion coefficient

Background

Neuroendocrine tumors (NETs) frequently overexpress somatostatin receptors (SSTRs), which is the molecular basis for ⁶⁸Ga-DOTATOC positron-emission tomography (PET) and radiopeptide therapy (PRRT). However, SSTR expression fluctuates and can be subject to treatment-related changes. The aim of this retrospective study was to assess, which changes in PET and apparent diffusion coefficient (ADC) occur for different treatments and if pre-therapeutic ⁶⁸Ga-DOTATOC-PET/MRI was able to predict treatment response to PRRT.

Methods

Patients with histopathologically confirmed NET, at least one liver metastasis > 1 cm and at least two ⁶⁸Ga-DOTATOC-PET/MRI including ADC maps were eligible. ⁶⁸Ga-DOTATOC-PET/MRI of up to 5 liver lesions per patients was subsequently analyzed. Extracted features comprise conventional PET parameters, such as maximum and mean standardized uptake value (SUVmax and SUVmean) and ADC values. Furthermore, textural features (TFs) from both modalities were extracted. In patients with multiple ⁶⁸Ga-DOTATOC-PET/MRI a pair of 2 scans each was analyzed separately and the parameter changes between both scans calculated. The same image analysis was performed in patients with ⁶⁸Ga-DOTATOC-PET/MRI before PRRT. Differences in PET and ADC maps parameters between PRRT-responders and non-responders were compared using Mann-Whitney test to test differences among groups for statistical significance.

Results

29 pairs of ⁶⁸Ga-DOTATOC-PET/MRI scans of 18 patients were eligible for the assessment of treatment-related changes. In 12 cases patients were treated with somatostatin analogues between scans, in 9 cases with PRRT and in 2 cases each patients received local treatment, chemotherapy and sunitinib. Treatment responders showed a statistically significant decrease in lesion volume and a borderline significant decrease in entropy on ADC maps when compared to non-responders. Patients treated with standalone SSA showed a borderline significant decrease in mean and maximum ADC, compared to patients treated with PRRT. No parameters were able to predict treatment response to PRRT on pre-therapeutic ⁶⁸Ga-DOTATOC-PET/MRI.

Conclusions

Patients responding to current treatment showed a statistically significant decrease in lesion volume on ADC maps and a borderline significant decrease in entropy. No statistically significant changes in PET parameters were observed. No PET or ADC maps parameters predicted treatment response to PRRT. However, the sample size of this preliminary study is small and further research needed.

Texture analysis of pretreatment [18F]FDG PET/CT for the prognostic prediction of locally advanced salivary gland carcinoma treated with interstitial brachytherapy

Background

The aim of this study was to evaluate the prognostic value of positron emission tomography (PET) parameters and the PET texture features of fluorine 18-fluorodeoxyglucose ([¹⁸F]FDG) uptake on pretreatment PET/computed tomography (CT) in patients with locally advanced salivary gland carcinoma treated with interstitial brachytherapy.

Methods

Forty-three patients with locally advanced salivary gland carcinoma of the head and neck were treated with ¹²⁵I interstitial brachytherapy as the sole modality and underwent [¹⁸F]FDG PET/CT scanning before treatment. Tumor segmentation and texture analysis were performed using the 3D slicer software. In total, 54 features were extracted and categorized as first-order statistics, morphology and shape, gray-level co-occurrence matrix, and gray-level run length matrix. Up to November 2018, the follow-up time ranged from 6 to 120 months (median 18 months). Cumulative survival was calculated by the Kaplan-Meier method. Factors between groups were compared by the log-rank test. Multivariate Cox regression analysis with a backward conditional method was used to predict progression-free survival (PFS).

Results

The 3- and 5-year locoregional control (LC) rates were 55.4% and 37.0%, respectively. The 3- and 5-year PFS rates were 51.2% and 34.1%, respectively. The 3- and 5-year overall survival (OS) rates were 77.0% and 77.0%, respectively. Univariate analysis revealed that minimum intensity, mean intensity, median intensity, root mean square, and long run emphasis (LRE) were significant predictors of PFS, whereas clinicopathological factors, conventional PET parameters, and PET texture features failed to show significance. Multivariate Cox regression analysis showed that minimum intensity and LRE were significant predictors of PFS.

Conclusions

The texture analysis of pretreatment [¹⁸F]FDG PET/CT provided more information than conventional PET parameters for predicting patient prognosis of locally advanced salivary gland carcinoma treated with interstitial brachytherapy. The minimum intensity was a risk factor for PFS, and LRE was a favorable factor in prognostic prediction according to the primary results.