Voxel based comparison and texture analysis of 18F-FDG and 18F-FMISO PET of patients with head-and-neck cancer

[18F]FMISO-PET imaging reveals the role of hypoxia severity in checkpoint blockade response

CONTEXT

Hypoxia within the tumor microenvironment is a critical factor influencing the efficacy of immunotherapy, including immune checkpoint inhibition. Insufficient oxygen supply, characteristic of hypoxia, has been recognized as a central determinant in the progression of various cancers. The reemergence of evofosfamide, a hypoxia-activated prodrug, as a potential treatment strategy has sparked interest in addressing the role of hypoxia in immunotherapy response. This investigation sought to understand the kinetics and heterogeneity of tumor hypoxia and their implications in affecting responses to immunotherapeutic interventions with and without evofosfamide.

PURPOSE

This study aimed to investigate the influence of hypoxia on immune checkpoint inhibition, evofosfamide monotherapy, and their combination on colorectal cancer (CRC). Employing positron emission tomography (PET) imaging, we developed novel analytical methods to quantify and characterize tumor hypoxia severity and distribution.

PROCEDURES

Murine CRC models were longitudinally imaged with [18F]-fluoromisonidazole (FMISO)-PET to quantify tumor hypoxia during checkpoint blockade (anti-CTLA-4 + and anti-PD1 +/- evofosfamide). Metrics including maximum tumor [18F]FMISO uptake (FMISOmax) and mean tumor [18F]FMISO uptake (FMISOmean) were quantified and compared with normal muscle tissue (average muscle FMISO uptake (mAvg) and muscle standard deviation (mSD)). Histogram distributions were used to evaluate heterogeneity of tumor hypoxia.

FINDINGS

Severe hypoxia significantly impeded immunotherapy effectiveness consistent with an immunosuppressive microenvironment. Hypoxia-specific PET imaging revealed a striking degree of spatial heterogeneity in tumor hypoxia, with some regions exhibiting significantly more severe hypoxia than others. The study identified FMISOmax as a robust predictor of immunotherapy response, emphasizing the impact of localized severe hypoxia on tumor volume control during therapy. Interestingly, evofosfamide did not directly reduce hypoxia but markedly improved the response to immunotherapy, uncovering an alternative mechanism for its efficacy.

CONCLUSIONS

These results enhance our comprehension of the interplay between hypoxia and immune checkpoint inhibition within the tumor microenvironment, offering crucial insights for the development of personalized cancer treatment strategies. Non-invasive hypoxia quantification through molecular imaging evaluating hypoxia severity may be an effective tool in guiding treatment planning, predicting therapy response, and ultimately improving patient outcomes across diverse cancer types and tumor microenvironments. It sets the stage for the translation of these findings into clinical practice, facilitating the optimization of immunotherapy regimens by addressing tumor hypoxia and thereby enhancing the efficacy of cancer treatments.

A Review of Hypoxia Imaging Using 18F-Fluoromisonidazole Positron Emission Tomography

Tumor hypoxia is an essential factor related to malignancy, prognosis, and resistance to treatment. Positron emission tomography (PET) is a modality that visualizes the distribution of radiopharmaceuticals administered into the body. PET imaging with [18F]fluoromisonidazole ([18F]FMISO) identifies hypoxic tissues. Unlike [18F]fluorodeoxyglucose ([18F]FDG)-PET, fasting is not necessary for [18F]FMISO-PET, but the waiting time from injection to image acquisition needs to be relatively long (e.g., 2-4 h). [18F]FMISO-PET images can be displayed on an ordinary commercial viewer on a personal computer (PC). While visual assessment is fundamental, various quantitative indices such as tumor-to-muscle ratio have also been proposed. Several novel hypoxia tracers have been invented to compensate for the limitations of [18F]FMISO.

From FDG and beyond: the evolving potential of nuclear medicine

The radiopharmaceutical 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG) has been dominantly used in positron emission tomography (PET) scans for over 20 years, and due to its vast utility its applications have expanded and are continuing to expand into oncology, neurology, cardiology, and infectious/inflammatory diseases. More recently, the addition of artificial intelligence (AI) has enhanced nuclear medicine diagnosis and imaging with FDG-PET, and new radiopharmaceuticals such as prostate-specific membrane antigen (PSMA) and fibroblast activation protein inhibitor (FAPI) have emerged. Nuclear medicine therapy using agents such as [177Lu]-dotatate surpasses conventional treatments in terms of efficacy and side effects. This article reviews recently established evidence of FDG and non-FDG drugs and anticipates the future trajectory of nuclear medicine.

Quantitative MRI to Characterize Hypoxic Tumors in Comparison to FMISO PET/CT for Radiotherapy in Oropharynx Cancers

Intratumoral hypoxia is associated with a poor prognosis and poor response to treatment in head and neck cancers. Its identification would allow for increasing the radiation dose to hypoxic tumor subvolumes. 18F-FMISO PET imaging is the gold standard; however, quantitative multiparametric MRI could show the presence of intratumoral hypoxia. Thus, 16 patients were prospectively included and underwent 18F-FDG PET/CT, 18F-FMISO PET/CT, and multiparametric quantitative MRI (DCE, diffusion and relaxometry T1 and T2 techniques) in the same position before treatment. PET and MRI sub-volumes were segmented and classified as hypoxic or non-hypoxic volumes to compare quantitative MRI parameters between normoxic and hypoxic volumes. In total, 13 patients had hypoxic lesions. The Dice, Jaccard, and overlap fraction similarity indices were 0.43, 0.28, and 0.71, respectively, between the FDG PET and MRI-measured lesion volumes, showing that the FDG PET tumor volume is partially contained within the MRI tumor volume. The results showed significant differences in the parameters of SUV in FDG and FMISO PET between patients with and without measurable hypoxic lesions. The quantitative MRI parameters of ADC, T1 max mapping and T2 max mapping were different between hypoxic and normoxic subvolumes. Quantitative MRI, based on free water diffusion and T1 and T2 mapping, seems to be able to identify intra-tumoral hypoxic sub-volumes for additional radiotherapy doses.

Advances in PET and MRI imaging of tumor hypoxia

Tumor hypoxia is a complex and evolving phenomenon both in time and space. Molecular imaging allows to approach these variations, but the tracers used have their own limitations. PET imaging has the disadvantage of low resolution and must take into account molecular biodistribution, but has the advantage of high targeting accuracy. The relationship between the signal in MRI imaging and oxygen is complex but hopefully it would lead to the detection of truly oxygen-depleted tissue. Different ways of imaging hypoxia are discussed in this review, with nuclear medicine tracers such as [¹⁸F]-FMISO, [¹⁸F]-FAZA, or [⁶⁴Cu]-ATSM but also with MRI techniques such as perfusion imaging, diffusion MRI or oxygen-enhanced MRI. Hypoxia is a pejorative factor regarding aggressiveness, tumor dissemination and resistance to treatments. Therefore, having accurate tools is particularly important.

The value of plasma hypoxia markers for predicting imaging-based hypoxia in patients with head-and-neck cancers undergoing definitive chemoradiation

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Higher osteopontin plasma levels correlate with more hypoxic tumors at baseline.

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Increased baseline osteopontin levels are associated with residual tumor hypoxia.

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Absent early hypoxia response is linked with higher VEGF and CTGF levels in week 5.

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Plasma hypoxic markers may serve as biomarkers favoring radiotherapy personalization.

Background

Methods

Results

Conclusion

18F-FDG PET cannot predict expression of clinically relevant histopathological biomarkers in head and neck squamous cell carcinoma: a meta-analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a common cancer. Positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) is a widely used imaging modality in HNSCC.

PURPOSE

To provide evident data about associations between 18F-FDG PET and histopathology in HNSCC.

MATERIAL AND METHODS

The MEDLINE database was screened for associations between maximum standard uptake values (SUV_max) derived from 18F-FDG PET and histopathological features in HNSCC up to May 2020. Only papers containing correlation coefficients between SUV_max and histopathology were acquired. Overall, 23 publications were collected.

RESULTS

The following correlations were calculated: KI 67: 12 studies (345 patients), pooled correlation coefficient (PCC): 0.23 (95% confidence interval [CI] 0.06-0.40); hypoxia-inducible factor-1α: eight studies (240 patients), PCC: 0.24 (95% CI 0.06-0.42); microvessel density: three studies (64 patients), PCC: 0.33 (95% CI 0.02-0.65); vascular endothelial growth factor: two studies (59 cases), PCC: 0.27 (95% CI 0.02-0.51); tumor suppressor protein p53: four studies (159 patients), PCC: 0.05 (95% CI -0.41 to 0.51); epidermal growth factor receptor: two studies (124 patients), PCC: 0.21 (95% CI 0.05-0.37); tumor cell count: three studies (67 patients), PCC: 0.18 (95% CI -0.06 to 0.42); tumor cell apoptosis: two studies (40 patients), PCC: 0.07 (95% CI = -0.85 to 0.99); B-cell lymphoma-2 protein: two studies (118 patients); PCC: 0.04 (95% CI -0.65 to 0.74); glucose-transporter 1: 10 studies (317 patients), PCC: 0.20 (95% CI 0.10-0.30).

CONCLUSION

SUV_max derived from 18F-FDG PET cannot reflect relevant histopathological features in HNSCC.

18F-FMISO PET/CT detects hypoxic lesions of cardiac and extra-cardiac involvement in patients with sarcoidosis

BACKGROUND

18F-fluoromisonidazole (FMISO) is a hypoxia positron emission tomography (PET) tracer. Here, we evaluated cardiac and extra-cardiac sarcoidosis using both FMISO and 18F-fluorodeoxyglucose (FDG) PET/CT in a prospective cohort of patients with sarcoidosis.

METHODS

Ten consecutive sarcoidosis patients with suspected cardiac involvement were prospectively enrolled. Each patient fasted overnight (for ≥ 18 hours) preceded by a low-carbohydrate diet before FDG PET/CT but not given special dietary instructions before the FMISO PET/CT scan. We visually and semiquantitatively assessed the uptakes of FMISO and FDG using the maximal standardized uptake value (SUVmax). The metabolic volume (MV) of FDG was calculated as the volume within the boundary determined by the threshold (mean SUV of blood pool × 1.5).

RESULTS

Nine patients showed focal FDG uptake in the myocardium and were diagnosed with cardiac sarcoidosis. Among the patients with extra-cardiac lesions, FDG uptake was seen in 8 lymph nodes and 3 lung lesions. FMISO uptake was seen in the 7 cardiac (77.8%) and 6 extra-cardiac (54.5%) lesions. None of the patients showed physiological FMISO uptake in the myocardium. The SUVmax values of the lesions with FMISO uptake were higher than those of the lesions without FMISO uptake in both the cardiac (SUVmax: 9.9, IQR: 8.4-10.0 vs 7.3, IQR: 6.3-8.2) and non-cardiac lesions (SUVmax: 17.6, IQR: 14.5-19.3 vs 6.1, IQR: 5.9-6.2; P = 0.006). The MV values of the lesions with FMISO uptake were significantly higher than those of the lesions without FMISO uptake (111.3, IQR: 78.3-135.7 vs 6.4, IQR: 1.9-23.3; P = 0.0009).

CONCLUSIONS

FMISO showed no physiological myocardial uptake and did not require special preparation. FMISO PET has the potential to detect hypoxic lesions in patients with sarcoidosis.

Intrinsic radiomic expression patterns after 20 Gy demonstrate early metabolic response of oropharyngeal cancers

PURPOSE

This study investigated the prognostic potential of intra-treatment PET radiomics data in patients undergoing definitive (chemo) radiation therapy for oropharyngeal cancer (OPC) on a prospective clinical trial. We hypothesized that the radiomic expression of OPC tumors after 20 Gy is associated with recurrence-free survival (RFS).

MATERIALS AND METHODS

Sixty-four patients undergoing definitive (chemo)radiation for OPC were prospectively enrolled on an IRB-approved study. Investigational ¹⁸ F-FDG-PET/CT images were acquired prior to treatment and 2 weeks (20 Gy) into a seven-week course of therapy. Fifty-five quantitative radiomic features were extracted from the primary tumor as potential biomarkers of early metabolic response. An unsupervised data clustering algorithm was used to partition patients into clusters based only on their radiomic expression. Clustering results were naïvely compared to residual disease and/or subsequent recurrence and used to derive Kaplan-Meier estimators of RFS. To test whether radiomic expression provides prognostic value beyond conventional clinical features associated with head and neck cancer, multivariable Cox proportional hazards modeling was used to adjust radiomic clusters for T and N stage, HPV status, and change in tumor volume.

RESULTS

While pre-treatment radiomics were not prognostic, intra-treatment radiomic expression was intrinsically associated with both residual/recurrent disease (P = 0.0256, χ 2 test) and RFS (HR = 7.53, 95% CI = 2.54-22.3; P = 0.0201). On univariate Cox analysis, radiomic cluster was associated with RFS (unadjusted HR = 2.70; 95% CI = 1.26-5.76; P = 0.0104) and maintained significance after adjustment for T, N staging, HPV status, and change in tumor volume after 20 Gy (adjusted HR = 2.69; 95% CI = 1.03-7.04; P = 0.0442). The particular radiomic characteristics associated with outcomes suggest that metabolic spatial heterogeneity after 20 Gy portends complete and durable therapeutic response. This finding is independent of baseline metabolic imaging characteristics and clinical features of head and neck cancer, thus providing prognostic advantages over existing approaches.

CONCLUSIONS

Our data illustrate the prognostic value of intra-treatment metabolic image interrogation, which may potentially guide adaptive therapy strategies for OPC patients and serve as a blueprint for other disease sites. The quality of our study was strengthened by its prospective image acquisition protocol, homogenous patient cohort, relatively long patient follow-up times, and unsupervised clustering formalism that is less prone to hyper-parameter tuning and over-fitting compared to supervised learning.

Prediction of the treatment outcome using machine learning with FDG-PET image-based multiparametric approach in patients with oral cavity squamous cell carcinoma

AIM

To investigate the value of machine learning-based multiparametric analysis using 2-[¹⁸F]-fluoro-2-deoxy-d-glucose positron-emission tomography (FDG-PET) images to predict treatment outcome in patients with oral cavity squamous cell carcinoma (OCSCC).

MATERIALS AND METHODS

Ninety-nine patients with OCSCC who received pretreatment integrated FDG-PET/computed tomography (CT) were included. They were divided into the training (66 patients) and validation (33 patients) cohorts. The diagnosis of local control or local failure was obtained from patient's medical records. Conventional FDG-PET parameters, including the maximum and mean standardised uptake values (SUVmax and SUVmean), metabolic tumour volume (MTV), and total lesion glycolysis (TLG), quantitative tumour morphological parameters, intratumoural histogram, and texture parameters, as well as T-stage and clinical stage, were evaluated by a machine learning analysis. The diagnostic ability of T-stage, clinical stage, and conventional FDG-PET parameters (SUVmax, SUVmean, MTV, and TLG) was also assessed separately.

RESULTS

In support-vector machine analysis of the training dataset, the final selected parameters were T-stage, SUVmax, TLG, morphological irregularity, entropy, and run-length non-uniformity. In the validation dataset, the diagnostic performance of the created algorithm was as follows: sensitivity 0.82, specificity 0.7, positive predictive value 0.86, negative predictive value 0.64, and accuracy 0.79. In a univariate analysis using conventional FDG-PET parameters, T-stage and clinical stage, diagnostic accuracy of each variable was revealed as follows: 0.61 in T-stage, 0.61 in clinical stage, 0.64 in SUVmax, 0.61 in SUVmean, 0.64 in MTV, and 0.7 in TLG.

CONCLUSION

A machine-learning-based approach to analysing FDG-PET images by multiparametric analysis might help predict local control or failure in patients with OCSCC.

PET Imaging of Tumor Hypoxia in Head and Neck Cancer: A Primer for Neuroradiologists

Tumor hypoxia is a known independent prognostic factor for adverse patient outcomes in those with head and neck cancer. Areas of tumor hypoxia have been found to be more radiation resistant than areas of tumor with normal oxygenation levels. Hypoxia imaging may serve to help identify the best initial treatment option and to assess intratreatment monitoring of tumor response in case treatment changes can be made. PET imaging is the gold standard method for imaging tumor hypoxia, with 18F-fluoromisonidazole the most extensively studied hypoxic imaging tracer. Newer tracers also show promise.

3D CNN with Visual Insights for Early Detection of Lung Cancer Using Gradient-Weighted Class Activation

The 3D convolutional neural network is able to make use of the full nonlinear 3D context information of lung nodule detection from the DICOM (Digital Imaging and Communications in Medicine) images, and the Gradient Class Activation has shown to be useful for tailoring classification tasks and localization interpretation for fine-grained features and visual explanation for the internal working. Gradient-weighted class activation plays a crucial role for clinicians and radiologists in terms of trusting and adopting the model. Practitioners not only rely on a model that can provide high precision but also really want to gain the respect of radiologists. So, in this paper, we explored the lung nodule classification using the improvised 3D AlexNet with lightweight architecture. Our network employed the full nature of the multiview network strategy. We have conducted the binary classification (benign and malignant) on computed tomography (CT) images from the LUNA 16 database conglomerate and database image resource initiative. The results obtained are through the 10-fold cross-validation. Experimental results have shown that the proposed lightweight architecture achieved a superior classification accuracy of 97.17% on LUNA 16 dataset when compared with existing classification algorithms and low-dose CT scan images as well.

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.

Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma

BACKGROUND

Positron emission tomography with ¹¹C-methionine (MET) is well established in the diagnostic work-up of malignant brain tumors. Texture analysis is a novel technique for extracting information regarding relationships among surrounding voxels, in order to quantify their inhomogeneity. This study evaluated whether the texture analysis of MET uptake has prognostic value for patients with glioma.

METHODS

We retrospectively analyzed adults with glioma who had undergone preoperative metabolic imaging at a single center. Tumors were delineated using a threshold of 1.3-fold of the mean standardized uptake value for the contralateral cortex, and then processed to calculate the texture features in glioma.

RESULTS

The study included 42 patients (median age: 56 years). The World Health Organization classifications were grade II (7 patients), grade III (17 patients), and grade IV (18 patients). Sixteen (16.1%) all-cause deaths were recorded during the median follow-up of 18.8 months. The univariate analyses revealed that overall survival (OS) was associated with age (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.01-1.08, p = 0.0093), tumor grade (HR 3.64, 95% CI 1.63-9.63, p = 0.0010), genetic status (p < 0.0001), low gray-level run emphasis (LGRE, calculated from the gray-level run-length matrix) (HR 2.30 × 10¹¹, 95% CI 737.11-4.23 × 10¹⁹, p = 0.0096), and correlation (calculated from the gray-level co-occurrence matrix) (HR 5.17, 95% CI 1.07-20.93, p = 0.041). The multivariate analyses revealed OS was independently associated with LGRE and correlation. The survival curves were also significantly different (both log-rank p < 0.05).

CONCLUSION

Textural features obtained using preoperative MET positron emission tomography may compliment the semi-quantitative assessment for prognostication in glioma cases.

Spatial heterogeneity of radiolabeled choline positron emission tomography in tumors of patients with non-small cell lung cancer: first-in-patient evaluation of [18F]fluoromethyl-(1,2-2H4)-choline

Purpose: The spatio-molecular distribution of choline and its metabolites in tumors is highly heterogeneous. Due to regulation of choline metabolism by hypoxic transcriptional signaling and other survival factors, we envisage that detection of such heterogeneity in patient tumors could provide the basis for advanced localized therapy. However, non-invasive methods to assess this phenomenon in patients are limited. We investigated such heterogeneity in Non-Small Cell Lung Cancer (NSCLC) with [18F]fluoromethyl-(1,2-2H4) choline ([18F]D4-FCH) and positron emission tomography/computed tomography (PET/CT). Experimental design: [18F]D4-FCH (300.5±72.9MBq [147.60-363.6MBq]) was administered intravenously to 17 newly diagnosed NSCLC patients. PET/CT scans were acquired concurrently with radioactive blood sampling to permit mathematical modelling of blood-tissue transcellular rate constants. Comparisons were made with biopsy-derived choline kinase-α (CHKα) expression and diagnostic [18F]fluorodeoxyglucose ([18F]FDG) scans. Results: Oxidation of [18F]D4-FCH to [18F]D4-fluorobetaine was suppressed (48.58±0.31% parent at 60 min) likely due to the deuterium isotope effect embodied within the design of the radiotracer. Early (5 min) and late (60 min) images showed specific uptake of tracer in all 51 lesions (tumors, lymph nodes and metastases) from 17 patients analyzed. [18F]D4-FCH-derived uptake (SUV60max) in index primary lesions (n=17) ranged between 2.87-10.13; lower than that of [18F]FDG PET [6.89-22.64]. Mathematical modelling demonstrated net irreversible uptake of [18F]D4-FCH at steady-state, and parametric mapping of the entire tumor showed large intratumorally heterogeneity in radiotracer retention, which is likely to have influenced correlations with biopsy-derived CHKα expression. Conclusions: [18F]D4-FCH is detectable in NSCLC with large intratumorally heterogeneity, which could be exploited in the future for targeting localized therapy.

Imaging of Tumor Hypoxia for Radiotherapy: Current Status and Future Directions

Tumor regions that are transiently or chronically undersupplied with oxygen (hypoxia) and nutrients, and enriched with acidic waste products, are common due to an abnormal and inefficient tumor vasculature, and a deviant highly glycolytic energy metabolism. There is compelling evidence that tumor hypoxia is strongly linked to poor prognosis since oxygen-deprived cells are highly resistant to therapy including radio- and chemotherapy, and survival of such cells is a primary cause of disease relapse. Despite a general improvement in cancer survival rates, hypoxia remains a formidable challenge. Recent progress in radiation delivery systems with improved spatial accuracy that allows dose escalation to hypoxic tumors or even tumor subvolumes, and the development of hypoxia-selective drugs, including bioreductive prodrugs, holds great promise for overcoming this obstacle. However, apart from one notable exception, translation of promising preclinical therapies to the clinic have largely been disappointing. A major obstacle in clinical trials on hypoxia-targeting strategies has been the lack of reliable information on tumor hypoxia, which is crucial for patient stratification into groups of those that are likely to benefit from intervention and those who are not. Further, in many newer trials on hypoxia-selective drugs the choice of cancer disease and combination therapy has not always been ideal, especially not for clinical proof of principle trials. Clearly, there is a pending need for clinical applicable methodologies that may allow us to quantify, map and monitor hypoxia. Molecular imaging may provide the information required for narrowing the gap between potential and actual patient benefit of hypoxia-targeting strategies. The grand majority of preclinical and clinical work has focused on the usefulness of PET-based assessment of hypoxia-selective tracers. Since hypoxia PET has profound inherent weaknesses, the use of other methodologies, including more indirect methods that quantifies blood flow or oxygenation-dependent flux changes through ATP-generating pathways (eg, anaerobic glycolysis) is being extensively studied. In this review, we briefly discuss established and emerging hypoxia-targeting strategies, followed by a more thorough evaluation of strengths and weaknesses of clinical applicable imaging methodologies that may guide timely treatment intensification to overcome hypoxia-driven resistance. Historically, most evidence for the linkage between hypoxia and poor outcome is based on work in the field of radiotherapy. Therefore, main emphasis in this review is on targeting and imaging of hypoxia for improved radiotherapy.

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.

Correlation between histogram-based DCE-MRI parameters and 18F-FDG PET values in oropharyngeal squamous cell carcinoma: Evaluation in primary tumors and metastatic nodes

OBJECTIVES

To investigate the correlation between histogram-based Dynamic Contrast-Enhanced magnetic resonance imaging (DCE-MRI) parameters and positron emission tomography with 18F-fluorodeoxyglucose (18F-FDG-PET) values in oropharyngeal squamous cell carcinoma (OPSCC), both in primary tumors (PTs) and in metastatic lymph nodes (LNs).

METHODS

52 patients with a new pathologically-confirmed OPSCC were included in the present retrospective cohort study. Imaging including DCE-MRI and 18F-FDG PET/CT scans were acquired in all patients. Both PTs and the largest LN, if present, were volumetrically contoured. Quantitative parameters, including the transfer constants, Ktrans and Kep, and the volume of extravascular extracellular space, ve, were calculated from DCE-MRI. The percentiles (P), P10, P25, P50, P75, P90, and skewness, kurtosis and entropy were obtained from the histogram-based analysis of each perfusion parameter. Standardized uptake values (SUV), SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated applying a SUV threshold of 40%. The correlations between all variables were investigated with the Spearman-rank correlation test. To exclude false positive results under multiple testing, the Benjamini-Hockberg procedure was applied.

RESULTS

No significant correlations were found between any parameters in PTs, while significant associations emerged between Ktrans and 18F-FDG PET parameters in LNs.

CONCLUSIONS

Evident relationships emerged between DCE-MRI and 18F-FDG PET parameters in OPSCC LNs, while no association was found in PTs. The complex relationships between perfusion and metabolic biomarkers should be interpreted separately for primary tumors and lymph-nodes. A multiparametric approach to analyze PTs and LNs before treatment is advisable in head and neck squamous cell carcinoma (HNSCC).

The Roles of Hypoxia Imaging Using 18F-Fluoromisonidazole Positron Emission Tomography in Glioma Treatment

Glioma is the most common malignant brain tumor. Hypoxia is closely related to the malignancy of gliomas, and positron emission tomography (PET) can noninvasively visualize the degree and the expansion of hypoxia. Currently, ¹⁸F-fluoromisonidazole (FMISO) is the most common radiotracer for hypoxia imaging. The clinical usefulness of FMISO PET has been established; it can distinguish glioblastomas from lower-grade gliomas and can predict the microenvironment of a tumor, including necrosis, vascularization, and permeability. FMISO PET provides prognostic information, including survival and treatment response information. Because hypoxia decreases a tumor’s sensitivity to radiation therapy, dose escalation to an FMISO-positive volume is an attractive strategy. Although this idea is not new, an insufficient amount of evidence has been obtained regarding this concept. New tracers for hypoxia imaging such as ¹⁸F-DiFA are being tested. In the future, hypoxia imaging will play an important role in glioma management.