Predictive value of quantitative diffusion-weighted imaging and 18-F-FDG-PET in head and neck squamous cell carcinoma treated by (chemo)radiotherapy

Predicting and monitoring response to head and neck cancer radiotherapy using multimodality imaging and radiobiological digital twin simulations

Objective.To predict radiotherapy treatment response for head and neck cancer (HNC) using multimodality imaging and personalized radiobiological modeling.Approach.A mechanistic radiobiological model was combined with multi-modality imaging data from diffusion weighted-magnetic resonance imaging and positron emission tomography scans with [18F]Fluorodeoxyglucose (FDG) and [18F]Fluoromisonidazole (FMISO) tracers to develop personalized treatment response models for human papilloma virus associated HNC patients undergoing chemo-radiotherapy. Models were initialized to incorporate patient-specific imaging and updated to reflect longitudinal measurements of nodal gross tumor volume throughout treatment. Prediction accuracy was assessed based on mean absolute error (MAE) of weekly volume predictions and in predicting locoregional recurrence (LRR) following treatment.Main results.Personalized modeling based on pretreatment imaging significantly improved longitudinal volume prediction accuracy and correlation with measurement compared with a generic population model (MAE = 23.4 ± 10.0% vs 24.9 ± 9.0%,p= 0.002 on pairedt-test,R= 0.82 vs 0.72). Adding volume measurements from weeks 1 and 2 further improved prediction accuracy for subsequent weeks (MAE = 12.5 ± 8.1%, 10.7 ± 9.9%). When incorporating feedback with longitudinal measurements, penalizing large deviations from pretreatment model parameters using a variational regularization method was necessary to maintain model stability. Model-predicted volumes based on baseline + week-1 information significantly improved LRR prediction compared with week-1 volume data alone (area under the curve, AUC = 0.83 vs 0.77,p= 0.03) and was similar to prediction using week-3 volume data (AUC = 0.83 vs 0.85,p= non-significant).Significance.The proposed approach, which integrates clinical imaging and radiobiological principles, could be a basis to guide pretreatment prescription personalization as well as on-treatment adaptations.

Reduced-distortion diffusion weighted imaging for head and neck radiotherapy

Background and purpose

Quantitative Diffusion Weighted Imaging (DWI) has potential value in guiding head and neck (HN) cancer radiotherapy. However, clinical translation has been hindered by severe distortions in standard single-shot Echo-Planar-Imaging (ssEPI) and prolonged scan time and low SNR in Turbo-Spin-Echo (ssTSE) sequences. In this study, we evaluate "multi-shot" (ms) msEPI and msTSE acquisitions in the context of HN radiotherapy.

Materials and methods

ssEPI, ssTSE, msEPI with 2 and 3 shots (2sEPI, 3sEPI), and msTSE DWI were acquired in a phantom, healthy volunteers (N=10), and patients with HN cancer (N=5) on a 3-Tesla wide-bore MRI in radiotherapy simulation RF coil setup, with matched spatial resolution (2x2x5mm) and b = 0, 200, 800 s/mm2.Geometric distortions measured with deformable vector field (DVF) and contour analysis, apparent diffusion coefficient (ADC) values, and signal-to-noise-ratio efficiency (SNReff) were quantified for all scans.

Results

All techniques significantly (P<1x10-3) reduced distortions compared with ssEPI (DVFmean = 3.1 ± 1.3 mm). Distortions were marginally lower for msTSE (DVFmean = 1.5 ± 0.6 mm) than ssTSE (1.8 ± 0.9 mm), but were slightly higher with 2sEPI and 3sEPI (2.6 ± 1.0 mm, 2.2 ± 1.0 mm). SNReff reduced with decreasing distortion with ssEPI=21.9 ± 7.9, 2sEPI=15.1 ± 5.0, 3sEPI=12.1 ± 4.5, ssTSE=6.0 ± 1.6, and msTSE=5.7 ± 1.9 for b = 0 images. Phantom ADC values were consistent across all protocols (errors ≤ 0.03x10-3mm2/s), but in vivo ADC values were ∼ 4 % lower with msEPI and ∼ 12 % lower with ssTSE/msTSE compared with ssEPI.

Conclusions

msEPI and TSE acquisitions exhibited improved geometric distortion at the cost of SNReff and scan time. While msTSE exhibited the least distortion, 3sEPI may offer an appealing middle-ground with improved geometric fidelity but superior efficiency and in vivo ADC quantification.

Multi-modality imaging parameters that predict rapid tumor regression in head and neck radiotherapy

Background and purpose

Volume regression during radiotherapy can indicate patient-specific treatment response. We aimed to identify pre-treatment multimodality imaging (MMI) metrics from positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT) that predict rapid tumor regression during radiotherapy in human papilloma virus (HPV) associated oropharyngeal carcinoma.

Materials and methods

Pre-treatment FDG PET-CT, diffusion-weighted MRI (DW-MRI), and intra-treatment (at 1, 2, and 3 weeks) MRI were acquired in 72 patients undergoing chemoradiation therapy for HPV+ oropharyngeal carcinoma. Nodal gross tumor volumes were delineated on longitudinal images to measure intra-treatment volume changes. Pre-treatment PET standardized uptake value (SUV), CT Hounsfield Unit (HU), and non-gaussian intravoxel incoherent motion DW-MRI metrics were computed and correlated with volume changes. Intercorrelations between MMI metrics were also assessed using network analysis. Validation was carried out on a separate cohort (N = 64) for FDG PET-CT.

Results

Significant correlations with volume loss were observed for baseline FDG SUVmean (Spearman ρ = 0.46, p < 0.001), CT HUmean (ρ = 0.38, p = 0.001), and DW-MRI diffusion coefficient, Dmean (ρ = -0.39, p < 0.001). Network analysis revealed 41 intercorrelations between MMI and volume loss metrics, but SUVmean remained a statistically significant predictor of volume loss in multivariate linear regression (p = 0.01). Significant correlations were also observed for SUVmean in the validation cohort in both primary (ρ = 0.30, p = 0.02) and nodal (ρ = 0.31, p = 0.02) tumors.

Conclusions

Multiple pre-treatment imaging metrics were correlated with rapid nodal gross tumor volume loss during radiotherapy. FDG-PET SUV in particular exhibited significant correlations with volume regression across the two cohorts and in multivariate analysis.

Advances and residual knowledge gaps in the neck management of head and neck squamous cell carcinoma patients with advanced nodal disease undergoing definitive (chemo)radiotherapy for their primary

PURPOSE

Substantial changes have been made in the neck management of patients with head and neck squamous cell carcinomas (HNSCC) in the past century. These have been fostered by changes in cancer epidemiology and technological progress in imaging, surgery, or radiotherapy, as well as disruptive concepts in oncology. We aimed to review changes in nodal management, with a focus on HNSCC patients with nodal involvement (cN+) undergoing (chemo)radiotherapy.

METHODS

A narrative review was conducted to review current advances and address knowledge gaps in the multidisciplinary management of the cN+ neck in the context of (chemo)radiotherapy.

RESULTS

Metastatic neck nodes are associated with poorer prognosis and poorer response to radiotherapy, and have therefore been systematically treated by surgery. Radical neck dissection (ND) has gradually evolved toward more personalized and less morbid approaches, i.e., from functional to selective ND. Omission of ND has been made feasible by use of positron-emission tomography/computed tomography to monitor the radiation response in cN+ patients. Human papillomavirus-driven oropharyngeal cancers and their cystic nodes have shown dramatically better prognosis than tobacco-related cancers, justifying a specific prognostic classification (AJCC) creation. Finally, considering the role of lymph nodes in anti-tumor immunity, de-escalation of ND and prophylactic nodal irradiation in combination are intense areas of investigation. However, the management of bulky cN3 disease remains an issue, as aggressive multidisciplinary strategies or innovative combined treatments have not yet significantly improved their prognosis.

CONCLUSION

Personalized neck management is an increasingly important aspect of the overall therapeutic strategies in cN+ HNSCC.

A systematic literature review of the human papillomavirus prevalence in locally and regionally advanced and recurrent/metastatic head and neck cancers through the last decade: The "ALARM" study

AIMS

The aim of this systematic literature review was to provide updated information on human papillomavirus (HPV) prevalence in locally and regionally advanced (LA) and recurrent/metastatic (RM) head and neck cancer (HNC) worldwide.

METHODS

Electronic searches were conducted on clinicaltrials.gov, MEDLINE/PubMed, Embase, and ASCO/ESMO journals of congresses for interventional studies (IS; Phase I-III trials) as well as MEDLINE and Embase for non-interventional studies (NIS) of LA/RM HNC published between January 01, 2010 and December 31, 2020. Criteria for study selection included: availability of HPV prevalence data for LA/RM HNC patients, patient enrollment from January 01, 2010 onward, and oropharyngeal cancer (OPC) included among HNC types. HPV prevalence per study was calculated as proportion of HPV+ over total number of enrolled patients. For overall HPV prevalence across studies, mean of reported HPV prevalence rates across studies and pooled estimate (sum of all HPV+ patients over sum of all patients enrolled) were assessed.

RESULTS

Eighty-one studies (62 IS; 19 NIS) were included, representing 9607 LA/RM HNC cases, with an overall mean (pooled) HPV prevalence of 32.6% (25.1%). HPV prevalence was 44.7% (44.0%) in LA and 24.3% (18.6%) in RM. Among 2714 LA/RM OPC patients from 52 studies with available data, mean (pooled) value was 55.8% (50.7%). The majority of data were derived from Northern America and Europe, with overall HPV prevalence of 46.0% (42.1%) and 24.7% (25.3%) across studies conducted exclusively in these geographic regions, respectively (Northern Europe: 31.9% [63.1%]). A "p16-based" assay was the most frequently reported HPV detection methodology (58.0%).

CONCLUSION

Over the last decade, at least one quarter of LA/RM HNC and half of OPC cases studied in IS and NIS were HPV+. This alarming burden is consistent with a potential implication of HPV in the pathogenesis of at least a subgroup of HNC, underscoring the relevance of HPV testing and prophylaxis to HNC prevention and management.

PET/MR Imaging in Head and Neck Cancer

Head and neck squamous cell carcinoma (HNSCC) can either be examined with hybrid PET/MR imaging systems or sequentially, using PET/CT and MR imaging. Regardless of the acquisition technique, the superiority of MR imaging compared to CT lies in its potential to interrogate tumor and surrounding tissues with different sequences, including perfusion and diffusion. For this reason, PET/MR imaging is preferable for the detection and assessment of locoregional residual/recurrent HNSCC after therapy. In addition, MR imaging interpretation is facilitated when combined with PET. Nevertheless, distant metastases and distant second primary tumors are detected equally well with PET/MR imaging and PET/CT.

The Prediction of Biological Features Using Magnetic Resonance Imaging in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

Magnetic resonance imaging (MRI) is an indispensable, routine technique that provides morphological and functional imaging sequences. MRI can potentially capture tumor biology and allow for longitudinal evaluation of head and neck squamous cell carcinoma (HNSCC). This systematic review and meta-analysis evaluates the ability of MRI to predict tumor biology in primary HNSCC. Studies were screened, selected, and assessed for quality using appropriate tools according to the PRISMA criteria. Fifty-eight articles were analyzed, examining the relationship between (functional) MRI parameters and biological features and genetics. Most studies focused on HPV status associations, revealing that HPV-positive tumors consistently exhibited lower ADCmean (SMD: 0.82; p < 0.001) and ADCminimum (SMD: 0.56; p < 0.001) values. On average, lower ADCmean values are associated with high Ki-67 levels, linking this diffusion restriction to high cellularity. Several perfusion parameters of the vascular compartment were significantly associated with HIF-1α. Analysis of other biological factors (VEGF, EGFR, tumor cell count, p53, and MVD) yielded inconclusive results. Larger datasets with homogenous acquisition are required to develop and test radiomic-based prediction models capable of capturing different aspects of the underlying tumor biology. Overall, our study shows that rapid and non-invasive characterization of tumor biology via MRI is feasible and could enhance clinical outcome predictions and personalized patient management for HNSCC.

Accuracy of magnetic resonance imaging in the assessment of depth of invasion in tongue carcinoma: A systematic review and meta-analysis

Tongue carcinoma constitutes 10.4-46.9% of all oral squamous cell carcinomas (OSCCs) and is notoriously known for invading tissues deeper than the evident gross margins. The deeper the tumor invades, the higher are its chances of future morbidity and mortality due to extensive neck dissection and risk of recurrence. Magnetic resonance imaging (MRI) is a noninvasive diagnostic aid used for measuring a preoperative tumor's depth of invasion (DOI) as it can efficiently outline soft tissue tumors from adjacent normal tissue. To assess various MRI modalities used in measuring DOI in tongue carcinoma and their reliability compared with other DOI measuring modalities. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42022330866), and the following Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) Diagnostic Test Accuracy guidelines were performed. PubMed electronic database was searched using a combination of keywords for relevant articles in the English language since 2016. Critical appraisal was carried out using the Quality Assessment of Diagnostic Accuracy Studies-Comparative (QUADAS-C) risk-of-bias (RoB) assessment tool. A weighted mean difference (WMD) was calculated between MRI and histopathological DOI along with pooled correlation and subgroup analysis, where possible. A total of 795 records were retrieved of which 17 were included in the final review with 13 included for meta-analysis. A high RoB was found for most studies for all parameters except flow and timing. WMD showed a statistically significant MRI overestimation of 1.90 mm compared with histopathology. Subgroup analysis showed the 1.5 Tesla machine to be superior to the 3.0 Tesla machine, while imaging sequence subgroup analysis could not be performed. MRI is a viable preoperative DOI measurement modality that can help in efficient treatment planning to decrease surgical morbidity and mortality.

Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models

PURPOSE

Tumor hypoxia and other microenvironmental factors are key determinants of treatment resistance. Hypoxia positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are established prognostic imaging modalities to identify radiation resistance in head-and-neck cancer (HNC). The aim of this preclinical study was to develop a multi-parametric imaging parameter specifically for focal radiotherapy (RT) dose escalation using HNC xenografts of different radiation sensitivities.

METHODS

A total of eight human HNC xenograft models were implanted into 68 immunodeficient mice. Combined PET/MRI using dynamic [18F]-fluoromisonidazole (FMISO) hypoxia PET, diffusion-weighted (DW), and dynamic contrast-enhanced MRI was carried out before and after fractionated RT (10 × 2 Gy). Imaging data were analyzed on voxel-basis using principal component (PC) analysis for dynamic data and apparent diffusion coefficients (ADCs) for DW-MRI. A data- and hypothesis-driven machine learning model was trained to identify clusters of high-risk subvolumes (HRSs) from multi-dimensional (1-5D) pre-clinical imaging data before and after RT. The stratification potential of each 1D to 5D model with respect to radiation sensitivity was evaluated using Cohen's d-score and compared to classical features such as mean/peak/maximum standardized uptake values (SUVmean/peak/max) and tumor-to-muscle-ratios (TMRpeak/max) as well as minimum/valley/maximum/mean ADC.

RESULTS

Complete 5D imaging data were available for 42 animals. The final preclinical model for HRS identification at baseline yielding the highest stratification potential was defined in 3D imaging space based on ADC and two FMISO PCs ([Formula: see text]). In 1D imaging space, only clusters of ADC revealed significant stratification potential ([Formula: see text]). Among all classical features, only ADCvalley showed significant correlation to radiation resistance ([Formula: see text]). After 2 weeks of RT, FMISO_c1 showed significant correlation to radiation resistance ([Formula: see text]).

CONCLUSION

A quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.

External validation of an MR-based radiomic model predictive of locoregional control in oropharyngeal cancer

OBJECTIVES

To externally validate a pre-treatment MR-based radiomics model predictive of locoregional control in oropharyngeal squamous cell carcinoma (OPSCC) and to assess the impact of differences between datasets on the predictive performance.

METHODS

Radiomic features, as defined in our previously published radiomics model, were extracted from the primary tumor volumes of 157 OPSCC patients in a different institute. The developed radiomics model was validated using this cohort. Additionally, parameters influencing performance, such as patient subgroups, MRI acquisition, and post-processing steps on prediction performance will be investigated. For this analysis, matched subgroups (based on human papillomavirus (HPV) status of the tumor, T-stage, and tumor subsite) and a subgroup with only patients with 4-mm slice thickness were studied. Also the influence of harmonization techniques (ComBat harmonization, quantile normalization) and the impact of feature stability across observers and centers were studied. Model performances were assessed by area under the curve (AUC), sensitivity, and specificity.

RESULTS

Performance of the published model (AUC/sensitivity/specificity: 0.74/0.75/0.60) drops when applied on the validation cohort (AUC/sensitivity/specificity: 0.64/0.68/0.60). The performance of the full validation cohort improves slightly when the model is validated using a patient group with comparable HPV status of the tumor (AUC/sensitivity/specificity: 0.68/0.74/0.60), using patients acquired with a slice thickness of 4 mm (AUC/sensitivity/specificity: 0.67/0.73/0.57), or when quantile harmonization was performed (AUC/sensitivity/specificity: 0.66/0.69/0.60).

CONCLUSION

The previously published model shows its generalizability and can be applied on data acquired from different vendors and protocols. Harmonization techniques and subgroup definition influence performance of predictive radiomics models.

KEY POINTS

• Radiomics, a noninvasive quantitative image analysis technique, can support the radiologist by enhancing diagnostic accuracy and/or treatment decision-making. • A previously published model shows its generalizability and could be applied on data acquired from different vendors and protocols.

Magnetic resonance imaging based radiomics prediction of Human Papillomavirus infection status and overall survival in oropharyngeal squamous cell carcinoma

OBJECTIVES

Human papillomavirus- (HPV) positive oropharyngeal squamous cell carcinoma (OPSCC) differs biologically and clinically from HPV-negative OPSCC and has a better prognosis. This study aims to analyze the value of magnetic resonance imaging (MRI)-based radiomics in predicting HPV status in OPSCC and aims to develop a prognostic model in OPSCC including HPV status and MRI-based radiomics.

MATERIALS AND METHODS

Manual delineation of 249 primary OPSCCs (91 HPV-positive and 159 HPV-negative) on pretreatment native T1-weighted MRIs was performed and used to extract 498 radiomic features per delineation. A logistic regression (LR) and random forest (RF) model were developed using univariate feature selection. Additionally, factor analysis was performed, and the derived factors were combined with clinical data in a predictive model to assess the performance on predicting HPV status. Additionally, factors were combined with clinical parameters in a multivariable survival regression analysis.

RESULTS

Both feature-based LR and RF models performed with an AUC of 0.79 in prediction of HPV status. Fourteen of the twenty most significant features were similar in both models, mainly concerning tumor sphericity, intensity variation, compactness, and tumor diameter. The model combining clinical data and radiomic factors (AUC = 0.89) outperformed the radiomics-only model in predicting OPSCC HPV status. Overall survival prediction was most accurate using the combination of clinical parameters and radiomic factors (C-index = 0.72).

CONCLUSION

Predictive models based on MR-radiomic features were able to predict HPV status with sufficient performance, supporting the role of MRI-based radiomics as potential imaging biomarker. Survival prediction improved by combining clinical features with MRI-based radiomics.

Repeatability of metabolic tumor burden and lesion glycolysis between clinical readers

The Metabolic Tumor Volume (MTV) and Tumor Lesion Glycolysis (TLG) has been shown to be independent prognostic predictors for clinical outcome in Diffuse Large B-cell Lymphoma (DLBCL). However, definitions of these measurements have not been standardized, leading to many sources of variation, operator evaluation continues to be one major source. In this study, we propose a reader reproducibility study to evaluate computation of TMV (& TLG) metrics based on differences in lesion delineation. In the first approach, reader manually corrected regional boundaries after automated detection performed across the lesions in a body scan (Reader M using a manual process, or manual). The other reader used a semi-automated method of lesion identification, without any boundary modification (Reader A using a semi- automated process, or auto). Parameters for active lesion were kept the same, derived from standard uptake values (SUVs) over a 41% threshold. We systematically contrasted MTV & TLG differences between expert readers (Reader M & A). We find that MTVs computed by Readers M and A were both concordant between them (concordant correlation coefficient of 0.96) and independently prognostic with a P-value of 0.0001 and 0.0002 respectively for overall survival after treatment. Additionally, we find TLG for these reader approaches showed concordance (CCC of 0.96) and was prognostic for over -all survival (p ≤ 0.0001 for both). In conclusion, the semi-automated approach (Reader A) provides acceptable quantification & prognosis of tumor burden (MTV) and TLG in comparison to expert reader assisted measurement (Reader M) on PET/CT scans.

Diffusion‐Weighted MR Imaging of the Optic Nerve Can Improve the Detection of Post‐Laminar Optic Nerve Invasion from Retinoblastoma

BACKGROUND

Post-laminar optic nerve invasion (PLONI) is a high-risk factor for the metastasis of retinoblastoma (RB). Unlike conventional MRI, diffusion-weighted imaging (DWI) reflects histopathological features, and may aid the assessment of PLONI.

PURPOSE

To determine the value of conventional MRI plus DWI in detecting PLONI in RB patients.

STUDY TYPE

Retrospective.

POPULATION

Eighty-three RB patients, including 28 with histopathologically proven PLONI and 55 without PLONI.

FIELD STRENGTH/SEQUENCE

3.0 T, precontrast axial T1-weighted and T2-weighted imaging, DWI, and postcontrast axial, coronal, and oblique-sagittal T1-weighted imaging.

ASSESSMENT

PLONI was assessed using post-enucleation histology and preoperative MRI features (optic nerve signal intensity, enlargement, and enhancement on conventional MRI, and apparent diffusion coefficient [ADC] of the optic nerve on DWI) evaluated by three observers.

STATISTICAL TESTS

MRI features suggesting the presence of PLONI were identified using univariable and multivariable analyses. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to analyze diagnostic performance.

RESULTS

Optic nerve enhancement and low ADC of the optic nerve were significant indicators of PLONI. ROC curve analysis showed that the AUC of the combination of these two features for detecting PLONI was 0.87 (95% confidence interval [CI]: 0.78-0.93). The diagnostic performance of this model was significantly superior to that of optic nerve enhancement alone (0.76, 95% CI: 0.65-0.85) and marginally superior to that of the ADC of the affected optic nerve (0.78, 95% CI: 0.68-0.87, P = 0.051).

DATA CONCLUSION

Conventional MRI combined with DWI can improve the detection of PLONI in RB patients over conventional MRI alone.

EVIDENCE LEVEL

3 Technical Efficacy: Stage 2.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Predicting and Monitoring the Response of Anti-Angiogenic Treatment in the Orthotopic Nude Mouse Model of Lung Adenocarcinoma

BACKGROUND

The treatment efficacy of angiogenesis inhibitor could be underestimated at an early stage based on tumor volume changes. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can quantitatively assess tumors at the cellular level, but it is unclear whether it can provide useful information for assessing treatment response of anti-angiogenic treatment for lung adenocarcinoma.

PURPOSE

To determine the use of IVIM-DWI for non-invasive monitoring of the early response to anti-angiogenic treatment in the orthotopic transplantation of lung adenocarcinoma model.

STUDY TYPE

Prospective.

POPULATION

Thirty-seven nude mice were randomized into two groups: treatment group (received bevacizumab + cisplatin, N = 20) and control group (received saline, N = 17).

FIELD STRENGTH/SEQUENCE

Single-shot turbo spin-echo (TSE) IVIM-DWI, TSE T2-weighted imaging at 3.0 T.

ASSESSMENT

Tumor volume, IVIM parameters (apparent diffusion coefficient [ADC], diffusivity [D], perfusion fraction [f], and pseudo-diffusion coefficient [D*]) were measured before and 2 hours, 3, 7, 10 and 14 days after treatment. Regions of interest were manually drawn along the inner edge of the tumor by two radiologists with 5 and 10-year experience in magnetic resonance imaging. Pathological examinations (hematoxylin and eosin stain, cluster of differentiation 34) were performed.

STATISTICAL TESTS

Kolmogorov-Smirnov test, repeated-measure two-way analysis of variance test, Mann-Whitney U test, Pearson correlation analysis, receiver operating characteristic curve. P < 0.05 was considered statistically significant.

RESULTS

The tumor volume of the two groups was significantly different only on day 14 (control group vs. treatment group, 43.15 ± 18.28 mm3 vs. 28.41 ± 1.71 mm3 ). ADC2h , ADC10d , D2h , D7d , D10d , and D14d were significantly higher, while f10d and f14d were significantly lower in the treatment group compared to those of the control group. Both the △ADC2h (r = -0.631) and △D2h (r = -0.700) showed moderate correlations with the relative tumor volume on day 14.

DATA CONCLUSION

IVIM has the potential to predict and monitor the early response to anti-angiogenic treatment, earlier than size changes, for lung adenocarcinoma.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 4.

Associations Between ADC and Tumor Infiltrating Lymphocytes, Tumor-Stroma Ratio and Vimentin Expression in Head and Neck Squamous Cell Cancer

RATIONALE AND OBJECTIVES

The present study used diffusion-weighted imaging (DWI) to elucidate possible associations with tumor-infiltrating lymphocytes (TIL), tumor-stroma ratio and vimentin expression in head and neck squamous cell cancer (HNSCC).

MATERIALS AND METHODS

30 patients with primary HNSCC of different localizations were involved in the study. DWI was obtained on a 3 T scanner. Apparent diffusion coefficients (ADC) images were analyzed with a whole lesion measurement using a histogram approach. TIL- and vimentin-expression was calculated on biopsy samples before any form of treatment.

RESULTS

Tumor-stroma ratio correlated with ADC kurtosis (r = 0.46, p = 0.01) and ADC skewness (r = 0.42, p = 0.02). Several ADC parameters were significantly different between stroma rich und tumor rich tumors. ADC entropy correlated significantly with the expression of TIL within the tumor compartment (r = 0.44, p = 0.01). No associations were identified between ADC parameters and vimentin expression.

CONCLUSION

ADC skewness and kurtosis histogram parameters can reflect tumor compartments in HNSCC. ADC entropy was associated with TIL of the tumor compartment but not with those of the stroma compartment, which emphasizes the ability of ADC histogram parameters to reflect distinctive differences of tumors.

Automatic segmentation of head and neck primary tumors on MRI using a multi-view CNN

Background 

Accurate segmentation of head and neck squamous cell cancer (HNSCC) is important for radiotherapy treatment planning. Manual segmentation of these tumors is time-consuming and vulnerable to inconsistencies between experts, especially in the complex head and neck region. The aim of this study is to introduce and evaluate an automatic segmentation pipeline for HNSCC using a multi-view CNN (MV-CNN).

Methods

The dataset included 220 patients with primary HNSCC and availability of T1-weighted, STIR and optionally contrast-enhanced T1-weighted MR images together with a manual reference segmentation of the primary tumor by an expert. A T1-weighted standard space of the head and neck region was created to register all MRI sequences to. An MV-CNN was trained with these three MRI sequences and evaluated in terms of volumetric and spatial performance in a cross-validation by measuring intra-class correlation (ICC) and dice similarity score (DSC), respectively.

Results

The average manual segmented primary tumor volume was 11.8±6.70 cm³ with a median [IQR] of 13.9 [3.22-15.9] cm³. The tumor volume measured by MV-CNN was 22.8±21.1 cm³ with a median [IQR] of 16.0 [8.24-31.1] cm³. Compared to the manual segmentations, the MV-CNN scored an average ICC of 0.64±0.06 and a DSC of 0.49±0.19. Improved segmentation performance was observed with increasing primary tumor volume: the smallest tumor volume group (<3 cm³) scored a DSC of 0.26±0.16 and the largest group (>15 cm³) a DSC of 0.63±0.11 (p<0.001). The automated segmentation tended to overestimate compared to the manual reference, both around the actual primary tumor and in false positively classified healthy structures and pathologically enlarged lymph nodes.

Conclusion

An automatic segmentation pipeline was evaluated for primary HNSCC on MRI. The MV-CNN produced reasonable segmentation results, especially on large tumors, but overestimation decreased overall performance. In further research, the focus should be on decreasing false positives and make it valuable in treatment planning.

Relationships Between DCE-MRI, DWI, and 18F-FDG PET/CT Parameters with Tumor Grade and Stage in Patients with Head and Neck Squamous Cell Carcinoma

Objectives

Properties of head and neck squamous cell carcinoma (HNSCC) such as cellularity, vascularity, and glucose metabolism interact with each other. This study aimed to investigate the associations between diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and positron emission tomography/computed tomography (PET/CT) in patients with HNSCC.

Methods

Fourteen patients who were diagnosed with HNSCC were investigated using DCE-MRI, DCE, and ¹⁸fluoride-fluorodeoxyglucose PET/CT and evaluated retrospectively. Ktrans, Kep, Ve, and initial area under the curve (iAUC) parameters from DCE-MRI, ADC_max, ADC_mean, and ADCmin parameters from DWI, and maximum standardized uptake value (SUV_max), SUV_mean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) parameters from PET were obtained. Spearman's correlation coefficient was used to analyze associations between these parameters. In addition, these parameters were grouped according to tumor grade and T and N stages, and the difference between the groups was evaluated using the Mann-Whitney U test.

Results

Correlations at varying degrees were observed in the parameters investigated. ADC_mean moderately correlated with Ve (p=0.035; r=0.566). Ktrans inversely correlated with SUV_max (p=0.017; r=-0.626). iAUC inversely correlated with SUV_max, SUV_mean, TLG, and MTV (p<0.05, r≤-0.700). MTV (40% threshold) was significantly higher in T4 tumors than in T1-3 tumors (p=0.020). No significant difference was found in the grouping made according to tumor grade and N stage in terms of these parameters.

Conclusion

Tumor cellularity, vascular permeability, and glucose metabolism had significant correlations at different degrees. Furthermore, MTV may be useful in predicting T4 tumors.

Prognostic functional MR imaging parameters in head and neck squamous cell carcinoma: A systematic review

OBJECTIVE

Functional MR imaging has demonstrated potential for predicting treatment response. This systematic review gives an extensive overview of the current level of evidence for pre-treatment MR-based perfusion and diffusion imaging parameters that are prognostic for treatment outcome in head and neck squamous cell carcinoma (HNSCC) (PROSPERO registrationCRD42020210689).

MATERIALS AND METHODS

According to the PRISMA statements, Medline, Embase and Scopus were queried for articles with a maximum date of October 19th, 2020. Studies investigating the predictive performance of pre-treatment MR-based perfusion and/or diffusion imaging parameters in HNSCC treatment response were included. All prognosticators were extracted from the primary tumor. Risk of bias was assessed using the QUIPS tool. Results were summarized in tables and forest plots.

RESULTS

31 unique studies met the inclusion criteria; among them, 11 articles described perfusion (n = 529 patients) and 28 described diffusion (n = 1626 patients) MR-imaging, eight studies were included in both categories. Higher K^trans and K_ep were associated with better treatment response for OS and DFS, respectively. Study findings for V_p and V_e were inconsistent or not significant. High-level controversy was observed between studies examining the MR diffusion parameters mean and median ADC.

CONCLUSION

For HNSCC patients, the accurate and consistent results of pre-treatment MR-based perfusion parameters K^trans and K_ep are potential for clinical applicability predictive of OS and DFS and treatment decision guidance. Significant heterogeneity in study designs might affect high discrepancy in study results for parameters extracted from diffusion imaging. Furthermore, recommendations for future research were summarized.

Advances in Imaging for HPV-Related Oropharyngeal Cancer: Applications to Radiation Oncology

While there has been an overall decline of tobacco and alcohol-related head and neck cancer in recent decades, there has been an increased incidence of HPV-associated oropharyngeal cancer (OPC). Recent research studies and clinical trials have revealed that the cancer biology and clinical progression of HPV-positive OPC is unique relative to its HPV-negative counterparts. HPV-positive OPC is associated with higher rates of disease control following definitive treatment when compared to HPV-negative OPC. Thus, these conditions should be considered unique diseases with regards to treatment strategies and survival. In order to sufficiently characterize HPV-positive OPC and guide treatment strategies, there has been a considerable effort to diagnose, prognose, and track the treatment response of HPV-associated OPC through advanced imaging research. Furthermore, HPV-positive OPC patients are prime candidates for radiation de-escalation protocols, which will ideally reduce toxicities associated with radiation therapy and has prompted additional imaging research to detect radiation-induced changes in organs at risk. This manuscript reviews the various imaging modalities and current strategies for tackling these challenges as well as provides commentary on the potential successes and suggested improvements for the optimal treatment of these tumors.

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.

Clinical Applications of PET/MR Imaging

PET/MR imaging is in routine clinical use and is at least as effective as PET/CT for oncologic and neurologic studies with advantages with certain PET radiopharmaceuticals and applications. In addition, whole body PET/MR imaging substantially reduces radiation dosages compared with PET/CT which is particularly relevant to pediatric and young adult population. For cancer imaging, assessment of hepatic, pelvic, and soft-tissue malignancies may benefit from PET/MR imaging. For neurologic imaging, volumetric brain MR imaging can detect regional volume loss relevant to cognitive impairment and epilepsy. In addition, the single-bed position acquisition enables dynamic brain PET imaging without extending the total study length which has the potential to enhance the diagnostic information from PET.

Multi-view convolutional neural networks for automated ocular structure and tumor segmentation in retinoblastoma

In retinoblastoma, accurate segmentation of ocular structure and tumor tissue is important when working towards personalized treatment. This retrospective study serves to evaluate the performance of multi-view convolutional neural networks (MV-CNNs) for automated eye and tumor segmentation on MRI in retinoblastoma patients. Forty retinoblastoma and 20 healthy-eyes from 30 patients were included in a train/test (N = 29 retinoblastoma-, 17 healthy-eyes) and independent validation (N = 11 retinoblastoma-, 3 healthy-eyes) set. Imaging was done using 3.0 T Fast Imaging Employing Steady-state Acquisition (FIESTA), T2-weighted and contrast-enhanced T1-weighted sequences. Sclera, vitreous humour, lens, retinal detachment and tumor were manually delineated on FIESTA images to serve as a reference standard. Volumetric and spatial performance were assessed by calculating intra-class correlation (ICC) and dice similarity coefficient (DSC). Additionally, the effects of multi-scale, sequences and data augmentation were explored. Optimal performance was obtained by using a three-level pyramid MV-CNN with FIESTA, T2 and T1c sequences and data augmentation. Eye and tumor volumetric ICC were 0.997 and 0.996, respectively. Median [Interquartile range] DSC for eye, sclera, vitreous, lens, retinal detachment and tumor were 0.965 [0.950-0.975], 0.847 [0.782-0.893], 0.975 [0.930-0.986], 0.909 [0.847-0.951], 0.828 [0.458-0.962] and 0.914 [0.852-0.958], respectively. MV-CNN can be used to obtain accurate ocular structure and tumor segmentations in retinoblastoma.

Correlation between 18F-FDG PET/CT and diffusion-weighted MRI parameters in head and neck squamous cell carcinoma at baseline and after chemo-radiotherapy. A retrospective single institutional study

OBJECTIVES

The relationship between glucose metabolism and tumor cellularity before chemo-radiotherapy in patients with head and neck squamous cell carcinoma (SCC) has never been compared with that of patients evaluated after treatment. This retrospective study analyzed the correlation between glucose metabolism parameters expressed by standardized uptake value (SUV) derived from 18F-fluorodeoxyglucose (18F-FDG) PET/CT and cellularity tumor parameters expressed by apparent diffusion coefficients (ADC) derived from diffusion-weighted (DW) MRI in untreated and treated patients with head and neck SCC.

METHODS

In 19 patients with no previous exposure to any treatment and 17 different chemo-radiotreated patients with head and neck SCC, we correlated the semi-quantitative uptake values (SUVmax, SUVpeak, and SUVmean) with the ADC functional parameters (ADCmin, ADCmean) including the standard deviation of ADC values (ADCsd).

RESULTS

No significant correlation was found between glucose metabolism parameters and ADCmin or ADCmean in untreated and treated patient groups. However, in untreated patients, significant inverse correlations were found between ADCsd and SUVmax (P = 0.039, r = -0.476), SUVpeak (P = 0.003, r = -0.652) and SUVmean (P = 0.039, r = -0.477). Analyses after chemo-radiotherapy in 17 patients showed no significant correlation between glucose metabolism parameters and DW MRI values, excluding a persistent significant (but lower intensity) inverse correlation between SUVpeak and ADCsd (P = 0.033, r = -0.519).

CONCLUSIONS

The demonstrated relationships suggest complex interactions especially between metabolic activity and heterogeneity of tumoral tissue, which might play a complementary role in the assessment of head and neck SCC.

TRIAL DATE OF REGISTRATION AND REGISTRATION NUMBER

Our retrospective study was registered on April 9th, 2020 by the Ethics Committee of the Coordinating Center "Area Vasta Nord Ovest" (CEAVNO) with Registration Number CEAVNO09042020.

The impact of human papilloma virus status on the prediction of head and neck cancer chemoradiotherapy outcomes using the pre-treatment apparent diffusion coefficient

Objective:

To determine the impact of Human Papilloma Virus (HPV) oropharyngeal cancer (OPC) status on the prediction of head and neck squamous cell cancer (HNSCC) chemoradiotherapy (CRT) outcomes with pre-treatment quantitative diffusion-weighted magnetic resonance imaging (DW-MRI).

Methods:

Following ethical approval, 65 participants (53 male, age 59.9 ± 7.86) underwent pre-treatment DW-MRI in this prospective cohort observational study. There were 46 HPV OPC and 19 other HNSCC cases with Stage III/IV HNSCC. Regions of interest (ROIs) (volume, largest area, core) at the primary tumour (n = 57) and largest pathological node (n = 59) were placed to analyse ADC_mean and ADC_min. Unpaired t-test or Mann–Whitney test evaluated the impact of HPV OPC status and clinical parameters on their prediction of post-CRT 2 year locoregional and disease-free survival (LRFS and DFS). Multivariate logistic regression compared significant variables with 2 year outcomes.

Results:

On univariate analysis of all participants, the primary tumour area ADC_mean was predictive of 2 year LRFS (p = 0.04). However, only the HPV OPC diagnosis (LFRS p = 0.03; DFS p = 0.02) predicted outcomes on multivariate analysis. None of the pre-treatment ADC values were predictive of 2 year DFS in the HPV OPC subgroup (p = 0.21–0.68). Amongst participants without 2 year disease-free survival, HPV-OPC was found to have much lower primary tumour ADC_mean values than other HNSCC.

Conclusion:

Knowledge of HPV OPC status is required in order to determine the impact of the pre-treatment ADC values on post-CRT outcomes in HNSCC.

Advances in knowledge:

Pre-treatment ADC_mean and ADC_min values acquired using different ROI methods are not predictive of 2 year survival outcomes in HPV OPC.

Diffusion-Weighted Imaging of the Head and Neck (Including Temporal Bone)

Diffusion techniques provide valuable information when performing head and neck imaging. This information can be used to detect the presence or absence of pathology, refine differential diagnosis, determine the location for biopsy, assess response to treatment, and prognosticate outcomes. For example, when certain technical factors are taken into consideration, diffusion techniques prove indispensable in assessing for residual cholesteatoma following middle ear surgery. In other scenarios, pretreatment apparent diffusion coefficient values may assist in prognosticating outcomes in laryngeal cancer and likelihood of response to radiation therapy. As diffusion techniques continue to advance, so too will its clinical utility.

Pre-treatment PET/MRI based FDG and DWI imaging parameters for predicting HPV status and tumor response to chemoradiotherapy in primary oropharyngeal squamous cell carcinoma (OPSCC)

OBJECTIVES

To determine the feasibility of pre-treatment primary tumor FDG-PET and DWI-MR imaging parameters in predicting HPV status and the second aim was to assess the feasibility of those imaging parameters to predict response to therapy.

MATERIAL AND METHODS

We retrospectively analyzed primary tumors in 33 patients with proven OPSCC. PET/MRI was performed before and 6 months after chemo-radiotherapy for assessing treatment response. PET Standardized uptake value (SUVmax), total lesion glycolysis (TLG), metabolic tumor volume (MTV), and apparent diffusion coefficient (ADC) from pre-treatment measurements were assessed and compared to the clinicopathological characteristics (T stages, N stages, tumor grades, HPV and post-treatment follow up). HPV was correlated to the clinicopathological characteristics.

RESULTS

ADCmean was significantly lower in patients with HPV^+ve than HPV^-ev, (P = 0.001), cut off value of (800 ± 0.44*10^-3mm²/s) with 76.9% sensitivity, and 72.2% specificity is able to differentiate between the two groups. No significant differences were found between FDG parameters (SUVmax, TLG, and MTV), and HPV status, (P = 0.873, P = 0.958, and P = 0.817), respectively. Comparison between CR and NCR groups; ADCmean, TLG, and MTV were predictive parameters of treatment response, (P = 0.017, P = 0.013, and P = 0.014), respectively. HPV^+ve group shows a higher probability of lymph nodes involvement, (P = 0.006) CONCLUSION: Our study found that pretreatment ADC of the primary tumor can predict HPV status and treatment response. On the other hand, metabolic PET parameters (TLG, and MTV) were able to predict primary tumor response to therapy.

Prognostic value of 18F-FDG PET/MRI in patients with advanced oropharyngeal and hypopharyngeal squamous cell carcinoma

OBJECTIVE

The aim of this study was to evaluate the prognostic value of combined positron emission tomography (PET)/magnetic resonance imaging (MRI) parameters provided by simultaneous 18F-fluorodeoxyglucose (FDG) PET/MRI in patients with locally advanced oropharyngeal and hypopharyngeal squamous cell carcinomas (OHSCC).

METHODS

Forty-five patients with locally advanced OHSCC who underwent simultaneous FDG PET/MRI before (chemo)radiotherapy were retrospectively enrolled. Peak standardized uptake value (SULpeak), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary lesion were obtained on PET data. On MRI scans, primary tumor size, diffusion and perfusion parameters were assessed using pre-contrast and high-resolution post-contrast images. Ratios between metabolic/metabolo-volumetric parameters and ADC were calculated. Comparisons between groups were performed by Student's t test. Survival analysis was performed by univariate Cox proportional hazard regression analysis. Overall survival curves were obtained by the Kaplan-Meier method and compared with the log-rank test. Survivors were censored at the time of the last clinical control. p < 0.05 was considered statistically significant RESULTS: During follow-up (mean 31.4 ± 21 months), there were 15 deaths. Univariate analysis shows that SULpeak and SULpeak/ADCmean were significant predictors of overall survival (OS). At multivariate analysis, only SULpeak remained a significant predictor of OS. Kaplan-Meier survival analyses showed that patients with higher SULpeak had poorer outcome compared to those with lower values (HR: 3.7, p = 0.007).

CONCLUSION

Pre-therapy SULpeak of the primary site was predictive of overall survival in patients with oropharyngeal or hypopharyngeal cancer treated with (chemo)radiotherapy.

Diffusion-weighted magnetic resonance imaging (DWMRI) of head and neck squamous cell carcinoma: could it be an imaging biomarker for prediction of response to chemoradiation therapy

Background

Chemoradiation therapy (CRT) has become a primary definitive treatment modality for head and neck squamous cell carcinoma (HNSCC); however, not all patients respond completely to treatment. Ability to identify those patients, who would not achieve complete response, before or early during the course of CRT will allow treatment modifications to improve outcome and overall survival. The aim of this prospective study was to assess the usefulness of diffusion-weighted imaging (DWI) in prediction of early therapeutic response of HNSCC after CRT.

Results

Local control was achieved in 22 patients out of 46 patients with pathologically proven HNSCC treated by chemoradiation therapy and local failure was detected in 24 patients out of 46 patients. Pretreatment mean apparent diffusion coefficient (ADCpre) was significantly higher in local failure group (1.1 ± 0.2 × 10−3 mm2/s) than local control group (0.89 ± 0.1 × 10−3 mm2/s). An optimal cut-off value of more than 0.94 × 10−3 mm2/s was predictive of local failure with sensitivity 83.33%, specificity 59.9%, PPV 69%, NPV 76.5%. Early intra-treatment percentage change of ADC (ΔADC) was significantly lower in local failure group (21.8% ± 21.3) than in local control group (45.2% ± 27.8). An optimal cut-off value of ≤ 33% was predictive of local failure after CRT with sensitivity of 71.34%, specificity of 60%, PPV of 62.5%, and NPV of 69.2%.

Conclusions

Diffusion-weighted MRI could be a potential predictive biomarker for therapeutic response of HNSCC to CRT. Primary tumors with higher pretreatment mean ADC, and a smaller early intratreatment percentage increase of mean ADC would be more likely to fail treatment.

Initial and Delayed Metabolic Activity of Palatine Tonsils Measured with the PET/CT-Dedicated Parameters

One of the most critical elements in the palatine tonsils (PT) patients' management is to distinguish chronic tonsillitis and malignant tumor. The single-time-point (STP) 2-deoxy-2-[¹⁸ F]fluoro-D-glucose positron emission tomography/computed tomography (¹⁸ F-FDG PET/CT) examination offers the most significant sensitivity and specificity in the head and neck (H&N) region evaluation among commonly used methods of imaging. However, introducing dual-time-point (DTP) scanning might improve the specificity and sensitivity of the technique, limited by the ¹⁸ F-FDG non-tumor-specific patterns, especially when comparing different metabolic parameters. The study aims to compare several surrogates of the maximal standardized uptake value (SUVmax), obtained in 36 subjects, divided into confirmed by pathologic study PT cancer and tonsillitis in patients who underwent DTP ¹⁸ F-FDG PET/CT scanning. In this study, we observed the increased sensitivity and the specificity of the DTP ¹⁸ F-FDG PET/CT when compared with the standard PET/CT protocol. It could be concluded that DTP ¹⁸ F-FDG PET/CT improves the PT cancer and chronic tonsillitis differential diagnosis.

Quantitative magnetic resonance imaging on hybrid magnetic resonance linear accelerators: Perspective on technical and clinical validation

Many preclinical and clinical observations support that functional magnetic resonance imaging (MRI), such as diffusion weighted (DW) and dynamic contrast enhanced (DCE) MRI, might have a predictive value for radiotherapy. The aim of this review was to assess the current status of quantitative MRI on hybrid MR-Linacs. In a literature research, four publications were identified, investigating technical feasibility, accuracy, repeatability and reproducibility of DW and DCE-MRI in phantoms and first patients. Accuracy and short term repeatability was < 5% for DW-MRI in current MR-Linac systems. Consequently, quantitative imaging providing accurate and reproducible functional information seems possible in MR-Linacs.

Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma

BACKGROUND

Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (¹⁸F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.

METHODS

Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent ¹⁸F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order ¹⁸F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with ¹⁸F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome.

RESULTS

Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764).

CONCLUSIONS

Combining HPV-status, first-order ¹⁸F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care.

TRIAL REGISTRATION

Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.

Predictive Value of Diffusion, Glucose Metabolism Parameters of PET/MR in Patients With Head and Neck Squamous Cell Carcinoma Treated With Chemoradiotherapy

Purpose: This study aims to evaluate the predictive value of the pretreatment, metabolic, and diffusion parameters of a primary tumor assessed with PET/MR on patient clinical outcomes.

Methods: Retrospective evaluation was performed using PET/MR image data sets acquired using the single tracer injection dual imaging of 68 histologically proven head and neck cancer patients 4 weeks before receiving definitive chemoradiotherapy (CRT). PET/MR was performed before the CRT and 12 weeks after the CRT for response evaluation. Image data (PET and MRI diffusion-weighted imaging [DWI]) was used to specify the maximum standard uptake value, the peak lean body mass corrected, SUV_max, the metabolic tumor volume, the total lesion glycolysis (SUV_max, SUL_peak, MTV, and TLG), and the mean apparent diffusion coefficient (ADC_mean) of the primary tumor. Based on the results of the therapeutic response evaluation, two patient subgroups were created: one with a viable tumor and another without. Metabolic and diffusion data, from the pretreatment PET/MR and the therapeutic response, were correlated using Spearman's correlation coefficient and Wilcoxon's test.

Results: After completing the CRT, a viable residual tumor was detected in 36/68 (53%) cases, and 32/68 (47%) patients showed complete remission. However, no significant correlation was found between the pretreatment parameter, ADC_mean (p = 0.88), and the therapeutic success. The PET parameters, SUV_max and SUL_peak, MTV, and TLG (p = 0.032, p = 0.01, p < 0.0001, p = 0.0004) were statistically significantly different between the two patient subgroups.

Conclusion: This study found that MRI-based (ADC_mean) data from FDG PET/MR pretreatment could not be used to predict therapeutic response although the PET parameters SUV_max, SUL_peak, MTV, and TLG proved to be more useful; thus, their inclusion in risk stratification may also be of additional value.

Pretreatment DWI with Histogram Analysis of the ADC in Predicting the Outcome of Advanced Oropharyngeal Cancer with Known Human Papillomavirus Status Treated with Chemoradiation

BACKGROUND AND PURPOSE

The incidence of oropharyngeal squamous cell carcinoma (OPSCC) has increased in the period from the 1970s to 2004, due to increase of infection with human papilloma virus (HPV). This study aimed to examine the role of histogram analysis of the ADC in treatment response and survival prediction of patients with oropharyngeal squamous cell carcinoma and known human papillomavirus status.

MATERIALS AND METHODS

This was a retrospective single-center study. Following inclusion and exclusion criteria, data for 59 patients affected by T2-T4 (according to the 8th edition of the AJCC Cancer Staging Manual) oropharyngeal squamous cell carcinoma were retrieved. Twenty-eight had human papillomavirus-positive oropharyngeal squamous cell carcinoma, while 31 had human papillomavirus-negative oropharyngeal squamous cell carcinoma. All patients underwent a pretreatment MR imaging. Histogram analysis of ADC maps obtained by DWI (b = 0-1000 mm/s²) was performed on the central section of all of tumors. The minimum follow-up period was 2 years. Histogram ADC parameters were associated with progression-free survival and overall survival. Univariable and multivariable Cox models were applied to the data; P values were corrected using the Benjamini-Hochberg method.

RESULTS

At univariable analysis, both human papillomavirus status and mean ADC were associated with progression-free survival (hazard ratio = 0.267, P < .05, and hazard ratio  = 1.0028, P ≤ .05, respectively), while only human papillomavirus status was associated with overall survival (hazard ratio  = 0.213, P ≤ .05) before correction. At multivariable analysis, no parameter was included (in fact, human papillomavirus status lost significance after correction). If we separated the patients into 2 subgroups according to human papillomavirus status, ADC entropy was associated with overall survival in the human papillomavirus-negative group (hazard ratio  = 4.846, P = .01).

CONCLUSIONS

ADC and human papillomavirus status are related to progression-free survival in patients treated with chemoradiation for advanced oropharyngeal squamous cell carcinoma; however, this association seems to result from the strong association between ADC and human papillomavirus status.

Comparison of diffusion-weighted MR imaging and 18F Fluorodeoxyglucose PET/CT in detection of residual or recurrent tumors and delineation of their local spread after (chemo) radiotherapy for head and neck squamous cell carcinoma

PURPOSE

To compare the diagnostic accuracy of diffusion-weighted magnetic resonance imaging (DW-MRI) and fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in detection of residual or recurrent tumors and their local extension in patients with head and neck squamous cell carcinoma after treatment with (chemo) radiotherapy (CRT).

METHOD

Twenty-five patients (17 men, 8 women, median age 64 years, range 49-79) who underwent surgical salvage for residual or recurrent tumors after CRT were included. The histopathologic analysis after the surgical salvage served as the gold standard.

RESULTS

Both DW-MRI and ¹⁸F-FDG PET/CT had a sensitivity of 92 % (23/25) in the detection of residual or recurrent tumors. MRI had a sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for detecting perineural spread of 62 % (5/8), 88 % (15/17), 71 % (5/7) and 83 % (15/18), respectively; in comparison, PET/CT did not detect any cases of perineural spread. The sensitivity, specificity, PPV and NPV of MRI in detecting muscle infiltration was 75 % (9/12), 77 % (10/13), 75 % (9/12) and 77 % (10/13) respectively, while the values for ¹⁸F-FDG PET/CT were 58 % (7/12), 69 % (9/13), 64 % (7/11) and 64 % (9/14).

CONCLUSIONS

DW-MRI- and ¹⁸F-FDG PET/CT-imaging have an identical detection rate of residual or recurrent tumors after (chemo) radiotherapy. MRI has a higher sensitivity in detecting local perineural spread, has a better accuracy in the detection of muscle infiltration and more accurately correlates the lesion size to the histopathologic specimen.

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.

Sequential delayed [18 F]FDG PET/CT examinations in the pharynx

This study aimed to evaluate the usefulness of the biphasic 2-deoxy-2-[18 F]fluoro-D-glucose positron emission tomography/computed tomography ([18 F]FDG PET/CT) examinations in terms of distinguishing benign and malignant lesions within the pharynx. 139 patients underwent sequential biphasic [18 F]FDG PET/CT examinations at 60 and 90 minutes (min) post intravenous injection (p.i.) of the [18 F]FDG. We evaluated the metabolic activity of 93 malignant lesions and 59 benign findings within pharynx as well as 70 normal blood vessels. We evaluated the maximal and mean standardized uptake value (SUVmax, SUVmean) and the retention index (RI-SUVmax). We used the receiver operating characteristics (ROC) analysis to obtain the prognostic metabolic indices cut-off which may differentiate between benign and malignant lesions. The SUVmax value cut-off at 60 and 90 min p.i. differentiating between normal and abnormal metabolic activity in the pharynx was 1.9 and 2.0, respectively. When compared benign and malignant lesions, the SUVmax on initial and delayed scans were 3.1 and 3.6, respectively. In this material, the increase of the SUVmax value over time of 1.7% suggested abnormality, while RI-SUVmax of 5.7% indicated malignant etiology. The biphasic [18 F]FDG PET/CT study protocol is useful in better stratification of normal and abnormal glucose metabolism activity in the pharynx.

Predictive Values of MRI and PET Derived Quantitative Parameters for Patterns of Failure in Both p16+ and p16- High Risk Head and Neck Cancer

Purpose: FDG-PET adds to clinical factors, such tumor stage and p16 status, in predicting local (LF), regional (RF), and distant failure (DF) in poor prognosis locally advanced head and neck cancer (HNC) treated with chemoradiation. We hypothesized that MRI-based quantitative imaging (QI) metrics could add to clinical predictors of treatment failure more significantly than FDG-PET metrics. Materials and methods: Fifty four patients with poor prognosis HNCs who were enrolled in an IRB approved prospective adaptive chemoradiotherapy trial were analyzed. MRI-derived gross tumor volume (GTV), blood volume (BV), and apparent diffusion coefficient (ADC) pre-treatment and mid-treatment (fraction 10), as well as pre-treatment FDG PET metrics, were analyzed in primary and individual nodal tumors. Cox proportional hazards models for prediction of LRF and DF free survival were used to test the additional value of QI metrics over dominant clinical predictors. Results: The mean ADC pre-RT and its change rate mid-treatment were significantly higher and lower in p16- than p16+ primary tumors, respectively. A Cox model identified that high mean ADC pre-RT had a high hazard for LF and RF in p16- but not p16+ tumors (p = 0.015). Most interesting, persisting subvolumes of low BV (TV_bv) in primary and nodal tumors mid-treatment had high-risk for DF (p < 0.05). Also, total nodal GTV mid-treatment, mean/max SUV of FDG in all nodal tumors, and total nodal TLG were predictive for DF (p < 0.05). When including clinical stage (T4/N3) and total nodal GTV in the model, all nodal PET parameters had a p-value of >0.3, and only TV_bv of primary tumors had a p-value of 0.06. Conclusion: MRI-defined biomarkers, especially persisting subvolumes of low BV, add predictive value to clinical variables and compare favorably with FDG-PET imaging markers. MRI could be well-integrated into the radiation therapy workflow for treatment planning, response assessment, and adaptive therapy.