Dynamic contrast-enhanced MRI, diffusion-weighted MRI and 18F-FDG PET/CT for the prediction of survival in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiation

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma

RATIONALE AND OBJECTIVES

To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients with head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

Radiomics features derived from T2-weighted, pre- and post-contrast-enhanced T1-weighted MRI sequences, clinical data, and RNA sequencing data of 150 patients with HNSCC were included in the study. Analysis of variance or recursive feature elimination was used to reduce radiomics features. Three RBML classifiers were developed to distinguish non-responders from responders. Weighted correlation network analysis (WGCNA) was performed to identify the correlation between clinical data or radiomics features and molecular features; subsequently, protein interaction and functional enrichment analyses were performed. The predictive performance of the radiogenomics model integrating significant clinical variables, RBML classifiers, and molecular features was evaluated using receiver operating characteristic curve analysis.

RESULTS

Five radiomics features and two conventional MRI findings significantly stratified HNSCC patients into responders and non-responders. On WGCNA analysis, 809 genes showed a significant correlation with two radiomics features. Functional enrichment analysis suggested that our proposed radiomics features could reflect the T cell-mediated immune response and immune infiltration of HNSCC. The radiogenomics model showed the highest area under the curve (0.88[95%CI 0.75-0.96]) for predicting IC response, which was better than MRI findings(p = 0.0407) or molecular features(p = 0.004) alone, but showed no significant difference with that of RBML model (p = 0.2254) in test cohort.

CONCLUSION

Merging imaging phenotypes with transcriptomic data improved the prediction of IC response in HNSCC.

Baseline and interim [18F]FDG-PET/MRI to assess treatment response and survival in patients with M0 esophageal squamous cell carcinoma treated by curative-intent therapy

BACKGROUND

To investigate the value of [18F]FDG-PET/MRI in predicting treatment response and survival in patients with primary M0 esophageal squamous cell carcinoma.

METHODS

Patients with esophageal squamous cell carcinoma received [18F]FDG-PET/MRI at baseline and during neoadjuvant or definitive chemoradiotherapy. The treatment response was classified according to the Response Evaluation Criteria for Solid Tumors 1.1. We used Kaplan-Meier and Cox regression analyses to assess the association between PET/MRI parameters and overall survival (OS) or progression-free survival (PFS).

RESULTS

We included 40 M0 patients in the final analysis. The volume transfer constant (Ktrans) from baseline PET/MRI (area under the curve (AUC) = 0.688, P = 0.034) and total lesion glycolysis (TLG) from baseline PET/MRI (AUC = 0.723, P = 0.006) or interim PET/MRI (AUC = 0.853, P < 0.001) showed acceptable AUC for predicting treatment response. The TLG from interim PET/MRI (interim TLG, P < 0.001) and extracellular volume fraction (Ve) on interim PET/MRI (interim Ve, P = 0.001) were identified as independent prognostic factors for OS. Baseline Ve (P = 0.044) and interim TLG (P = 0.004) were significant predictors of PFS. The c-indices of the prognostic models combining interim TLG with Ve for predicting OS, and baseline Ve and interim TLG for predicting PFS were 0.784 and 0.699, respectively. These values were significantly higher than the corresponding c-indices of the TNM staging system (P = 0.002 and P = 0.047, respectively).

CONCLUSIONS

Combining the baseline and interim [18F]FDG-PET/MRI qualitative imaging parameters aids in predicting the prognosis of patients with M0 esophageal squamous cell carcinoma.

TRIAL REGISTRATION

The study was registered at Clinicaltrials.gov (identifier: NCT05855291 and NCT05855278).

Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Parameters Could Predict International Society of Urological Pathology Risk Groups of Prostate Cancers on Radical Prostatectomy

BACKGROUND

The International Society of Urological Pathology (ISUP) grade and positive surgical margins (PSMs) after radical prostatectomy (RP) may reflect the prognosis of prostate cancer (PCa) patients. This study aimed to investigate whether DCE-MRI parameters (i.e., Ktrans, kep, and IAUC) could predict ISUP grade and PSMs after RP.

METHOD

Forty-five PCa patients underwent preoperative DCE-MRI. The clinical characteristics and DCE-MRI parameters of the 45 patients were compared between the low- and high-risk (i.e., ISUP grades III-V) groups and between patients with or without PSMs after RP. Multivariate logistic regression analysis was used to identify the significant predictors of placement in the high-risk group and PSMs.

RESULTS

The DCE parameter Ktrans-max was significantly higher in the high-risk group than in the low-risk group (p = 0.028) and was also a significant predictor of placement in the high-risk group (odds ratio [OR] = 1.032, 95% confidence interval [CI] = 1.005-1.060, p = 0.021). Patients with PSMs had significantly higher prostate-specific antigen (PSA) titers, positive biopsy core percentages, Ktrans-max, kep-median, and kep-max than others (all p < 0.05). Of these, positive biopsy core percentage (OR = 1.035, 95% CI = 1.003-1.068, p = 0.032) and kep-max (OR = 1.078, 95% CI = 1.012-1.148, p = 0.020) were significant predictors of PSMs.

CONCLUSION

Preoperative DCE-MRI parameters, specifically Ktrans-max and kep-max, could potentially serve as preoperative imaging biomarkers for postoperative PCa prognosis based on their predictability of PCa risk group and PSM on RP, respectively.

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.

Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning

OBJECTIVES

To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.

METHODS

MR images were collected from 222 HPC patients, among them 178 patients were used for training, and another 44 patients were recruited for testing. U-Net and DeepLab V3 + architectures were used for training the models. The model performance was evaluated using the dice similarity coefficient (DSC), Jaccard index, and average surface distance. The reliability of radiomics parameters of the tumor extracted by the models was assessed using intraclass correlation coefficient (ICC).

RESULTS

The predicted tumor volumes by DeepLab V3 + model and U-Net model were highly correlated with those delineated manually (p < 0.001). The DSC of DeepLab V3 + model was significantly higher than that of U-Net model (0.77 vs 0.75, p < 0.05), particularly in those small tumor volumes of < 10 cm3 (0.74 vs 0.70, p < 0.001). For radiomics extraction of the first-order features, both models exhibited high agreement (ICC: 0.71-0.91) with manual delineation. The radiomics extracted by DeepLab V3 + model had significantly higher ICCs than those extracted by U-Net model for 7 of 19 first-order features and for 8 of 17 shape-based features (p < 0.05).

CONCLUSION

Both DeepLab V3 + and U-Net models produced reasonable results in automated segmentation and radiomic features extraction of HPC on MR images, whereas DeepLab V3 + had a better performance than U-Net.

CLINICAL RELEVANCE STATEMENT

The deep learning model, DeepLab V3 + , exhibited promising performance in automated tumor segmentation and radiomics extraction for hypopharyngeal cancer on MRI. This approach holds great potential for enhancing the radiotherapy workflow and facilitating prediction of treatment outcomes.

KEY POINTS

• DeepLab V3 + and U-Net models produced reasonable results in automated segmentation and radiomic features extraction of HPC on MR images. • DeepLab V3 + model was more accurate than U-Net in automated segmentation, especially on small tumors. • DeepLab V3 + exhibited higher agreement for about half of the first-order and shape-based radiomics features than U-Net.

Association between maximum standarised uptake value (SUV) and local control in patients with oropharyngeal carcinoma treated with radiotherapy

OBJECTIVE

To analyse the prognostic ability of the maximum standardised uptake value (SUVmax) on local disease control in patients with oropharyngeal carcinoma treated with radiotherapy.

MATERIAL AND METHODS

Retrospective study of 105 patients with oropharyngeal carcinomas treated with radiotherapy, including chemo- and bio-radiotherapy, and who had a PET-CT scan prior to the start of treatment.

RESULT

Patients with a SUVmax value higher than 17.2 at the primary tumour site had a significantly higher risk of local recurrence. The 5-year local recurrence-free survival for patients with SUVmax less than or equal to 17.2 (n = 71) was 86.5% (95% CI 78.2-94.7 %), and for patients with SUVmax greater than 17.2 (n = 34) it was 55.8% (95% CI 36.0-75.6 %) (P = 0.0001). This difference in local control was maintained regardless of patients' HPV status. Specific survival was similarly lower for patients with a SUV greater than 17.2. The 5-year specific survival for patients with SUVmax greater than 17.2 was 39.5% (95% CI: 20.6-58.3 %), significantly shorter than that of patients with SUVmax equal to or less than 17.2, which was 77.3% (95% CI: 66.9-87.6 %) (P = 0.0001).

CONCLUSIONS

Patients with oropharyngeal carcinomas treated with radiotherapy with a SUVmax greater than 17.2 at the level of the primary tumour site had a significantly higher risk of local recurrence.

The clinical value of DCE-MRI for differentiating secondary laryngeal cartilage lesions

To explore the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the assessment of laryngeal cartilage lesions. In this study, 3 groups of cases were selected, including 16 cases benign lesions of the laryngopharynx as the benign group, 17 cases malignant lesions of laryngopharynx as the malignant group and 23 healthy adults as the control group. Conventional magnetic resonance imaging and DCE-MRI were performed with a 3.0 T MR scanner. cutoff, sensitivity, specificity and area under the curve values were calculated via receiver operating characteristic curve analysis based on the pathologic findings of surgically resected specimens. There were significant differences in the values of the volume transfer constant (Ktrans), the rate constant between the extravascular extracellular space and blood plasma (Kep) and The extravascular extracellular space fractional volume (Ve) between the control, benign and malignant groups (P < .005). Among the 3 groups, the malignant group had the highest Ktrans and Ve values (0.8681 ± 0.3034 and 0.6186 ± 0.2405, respectively), and the benign group had the highest Kep value (2.445 ± 0.7346). The cutoff points of the Ktrans, Kep, and Ve values of the control, benign and malignant groups were 0.39, 1.261, and 0.195; 0.471, 0.964, and 0.235; and 0.706, 2.005, and 0.659, respectively. The Ktrans, Kep, and Ve values obtained via DCE-MRI may enable differentiating laryngeal cartilage lesions. DCE-MRI can be used to evaluate laryngeal cartilage lesions accurately and quantitatively.

Radiomics in Hypopharyngeal Cancer Management: A State-of-the-Art Review

(1) Background: Hypopharyngeal squamous cell carcinomas usually present with locally advanced disease and a correspondingly poor prognosis. Currently, efforts are being made to improve tumor characterization and provide insightful information for outcome prediction. Radiomics is an emerging area of study that involves the conversion of medical images into mineable data; these data are then used to extract quantitative features based on shape, intensity, texture, and other parameters; (2) Methods: A systematic review of the peer-reviewed literature was conducted; (3) Results: A total of 437 manuscripts were identified. Fifteen manuscripts met the inclusion criteria. The main targets described were the evaluation of textural features to determine tumor-programmed death-ligand 1 expression; a surrogate for microvessel density and heterogeneity of perfusion; patient stratification into groups at high and low risk of progression; prediction of early recurrence, 1-year locoregional failure and survival outcome, including progression-free survival and overall survival, in patients with locally advanced HPSCC; thyroid cartilage invasion, early disease progression, recurrence, induction chemotherapy response, treatment response, and prognosis; and (4) Conclusions: our findings suggest that radiomics represents a potentially useful tool in the diagnostic workup as well as during the treatment and follow-up of patients with HPSCC. Large prospective studies are essential to validate this technology in these patients.

Efficacy evaluation of different measurement methods for target lesions after neoadjuvant chemotherapy and radical radiotherapy in locally advanced hypopharyngeal carcinoma

AIM

To assess the diagnostic efficacy in response evaluation of hypopharyngeal carcinoma (HPC) using different CT measurement methods.

METHODS AND MATERIALS

One hundred and three patients with locally advanced HPC receiving neoadjuvant chemotherapy (NACT) and radical radiotherapy (RT) were retrospectively enrolled. The long diameter, short diameter and largest axial area of the tumors and the largest metastatic cervical lymph node (LN) were measured before and after NACT, at the end of RT and 1 month after RT. Tumor regression ratios of the sum of the tumor's long diameter and LN's short diameter (LDTSDL), the sum of tumor and LN's short diameter (TTSDL), the sum of tumor and LN's largest axial area (AATML) were calculated. Analysis was conducted for overall survival (OS), metastasis-free survival, regional recurrence-free survival (RRFS), and local recurrence-free survival (LRFS).

RESULTS

Note that 35, 28, 23, and 16 patients suffered death, local recurrence, regional recurrence and distant metastasis, respectively. TTSDL-defined effective group demonstrated better LRFS (p = .039) and RRFS (p = .047) after NACT and better OS since the end of RT (p = .037); AATML-defined effective groups demonstrated better OS, LRFS, and RRFS since the end of RT (p = .015, .008, and .005). While LDTSDL-defined groups showed differences in OS and LRFS until 1 month after RT (p = .013 and .014).

CONCLUSIONS

The regression rate of TTSDL and AATML can distinguish prognosis at an earlier time and demonstrated better reliability compared with LDTSDL. They were recommended for response evaluation in HPC.

Prospective Investigation of 18FDG-PET/MRI with Intravoxel Incoherent Motion Diffusion-Weighted Imaging to Assess Survival in Patients with Oropharyngeal or Hypopharyngeal Carcinoma

To prospectively investigate the prognostic value of 18F-FDG PET/MRI in patients with oropharyngeal or hypopharyngeal squamous cell carcinomas (OHSCC) treated by chemoradiotherapy. The study cohort consisted of patients with OHSCC who had undergone integrated PET/MRI prior to chemoradiotherapy or radiotherapy. Imaging parameters derived from intravoxel incoherent motion (IVIM), dynamic contrast-enhanced MRI (DCE-MRI), and 18F-FDG PET were analyzed in relation to overall survival (OS) and recurrence-free survival (RFS). In multivariable analysis, T classification (p < 0.001), metabolic tumor volume (p = 0.013), and pseudo-diffusion coefficient (p = 0.008) were identified as independent risk factors for OS. The volume transfer rate constant (p = 0.015), initial area under the curve (p = 0.043), T classification (p = 0.018), and N classification (p = 0.018) were significant predictors for RFS. The Harrell’s c-indices of OS and RFS obtained from prognostic models incorporating clinical and PET/MRI predictors were significantly higher than those derived from the traditional TNM staging system (p = 0.001). The combination of clinical risk factors with functional parameters derived from IVIM and DCE-MRI plus metabolic PET parameters derived from 18F-FDG PET in integrated PET/MRI outperformed the information provided by traditional TNM staging in predicting the survival of patients with OHSCC.

Dynamic contrast enhanced MRI of pulmonary adenocarcinomas for early risk stratification: higher contrast uptake associated with response and better prognosis

BACKGROUND

To explore the prognostic value of serial dynamic contrast-enhanced (DCE) MRI in patients with advanced pulmonary adenocarcinoma undergoing first-line therapy with either tyrosine-kinase inhibitors (TKI) or platinum-based chemotherapy (PBC).

METHODS

Patients underwent baseline (day 0, n = 98), and post-therapeutic DCE MRI (PBC: day + 1, n = 52); TKI: day + 7, n = 46) at 1.5T. Perfusion curves were acquired at 10, 40, and 70 s after contrast application and analysed semiquantitatively. Treatment response was evaluated at 6 weeks by CT (RECIST 1.1); progression-free survival (PFS) and overall survival  were analysed with respect to clinical and perfusion parameters. Relative uptake was defined as signal difference between contrast and non-contrast images, divided by the non-contrast signal. Predictors of survival were selected using Cox regression analysis. Median follow-up was 825 days.

RESULTS

In pre-therapeutic and early post-therapeutic MRI, treatment responders (n = 27) showed significantly higher relative contrast uptake within the tumor at 70 s after application as compared to non-responders (n = 71, p ≤ 0.02), response defined as PR by RECIST 1.1 at 6 weeks. There was no significant change of perfusion at early MRI after treatment. In multivariate regression analysis of selected parameters, the strongest association with PFS were relative uptake at 40 s in the early post-treatment MRI and pre-treatment clinical data (presence of liver metastases, ECOG performance status).

CONCLUSION

Higher contrast uptake within the tumor at pre-treatment and early post-treatment MRI was associated with treatment response and better prognosis. DCE MRI of pulmonary adenocarcinoma may provide important prognostic information.

CT-based radiomics signature analysis for evaluation of response to induction chemotherapy and progression-free survival in locally advanced hypopharyngeal carcinoma

OBJECTIVES

To establish and validate a CT radiomics model for prediction of induction chemotherapy (IC) response and progression-free survival (PFS) among patients with locally advanced hypopharyngeal carcinoma (LAHC).

METHODS

One hundred twelve patients with LAHC (78 in training cohort and 34 in validation cohort) who underwent contrast-enhanced CT (CECT) scans prior to IC were enrolled. Least absolute shrinkage and selection operator (LASSO) was used to select the crucial radiomic features in the training cohort. Radiomics signature and clinical data were used to build a radiomics nomogram to predict individual response to IC. Kaplan-Meier analysis and log-rank test were used to evaluate ability of radiomics signature in progression-free survival risk stratification.

RESULTS

The radiomics signature consisted of 6 selected features from the arterial and venous phases of CECT images and demonstrated good performance in predicting the IC response in both two cohorts. The radiomics nomogram showed good discriminative performance, and the C-index of nomogram was 0.899 (95% confidence interval (CI), 0.831-0.967) and 0.775 (95% CI, 0.591-0.959) in the training and validation cohorts, respectively. Survival analysis indicated that low-risk and high-risk groups defined by the value of radiomics signature had significant difference in PFS (3-year PFS 66.4% vs 29.7%, p < 0.001).

CONCLUSIONS

Multiparametric CT-based radiomics model could be useful for predicting treatment response and PFS in patients with LAHC who underwent IC.

KEY POINTS

• CT radiomics can predict IC response and progression-free survival in hypopharyngeal carcinoma. • We combined significant radiomics signature with clinical predictors to establish a nomogram to predict individual response to IC. • Radiomics signature could divide patients into the high-risk and low-risk groups based on the PFS.

Quantitative Dynamic-Enhanced MRI and Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Prediction of the Pathological Response to Neoadjuvant Chemotherapy and the Prognosis in Locally Advanced Gastric Cancer

Background

This study aimed to explore the predictive value of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters for the response to neoadjuvant chemotherapy (NCT) in locally advanced gastric cancer (LAGC) patients, and the relationship between the prediction results and patients’ prognosis, so as to provide a basis for clinical individualized precision treatment.

Methods

One hundred twenty-nine newly diagnosed LAGC patients who underwent IVIM-DWI and DCE-MRI pretreatment were enrolled in this study. Pathological tumor regression grade (TRG) served as the reference standard of NCT response evaluation. The differences in DCE-MRI and IVIM-DWI parameters between pathological responders (pR) and pathological non-responders (pNR) groups were analyzed. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCT response. Prediction models were built with statistically significant quantitative parameters and their combinations. The performance of these quantitative parameters and models was evaluated using receiver operating characteristic (ROC) analysis. Clinicopathological variables, DCE-MRI and IVIM-DWI derived parameters, as well as the prediction model were analyzed in relation to 2-year recurrence-free survival (RFS) by using Cox proportional hazards model. RFS was compared using the Kaplan–Meier method and the log-rank test.

Results

Sixty-nine patients were classified as pR and 60 were pNR. K^trans, k_ep, and v_e values in the pR group were significantly higher, while ADC_standard and D values were significantly lower than those in the pNR group. Multivariate logistic regression analysis demonstrated that K^trans, k_ep, v_e, and D values were independent predictors for NCT response. The combined predictive model, which consisted of DCE-MRI and IVIM-DWI, showed the best prediction performance with an area under the curve (AUC) of 0.922. Multivariate Cox regression analysis showed that ypStage III and NCT response predicted by the IVIM-DWI model were independent predictors of poor RFS. The IVIM-DWI model could significantly stratify median RFS (52 vs. 15 months) and 2-year RFS rate (72.3% vs. 21.8%) of LAGC.

Conclusion

Pretreatment DCE-MRI quantitative parameters K^trans, k_ep, v_e, and IVIM-DWI parameter D value were independent predictors of NCT response for LAGC patients. The regression model based on baseline DCE-MRI, IVIM-DWI, and their combination could help RFS stratification of LAGC patients.

Computed tomography-based radiomics signature as a pretreatment predictor of progression-free survival in locally advanced hypopharyngeal carcinoma with a different response to induction chemotherapy

PURPOSE

To establish and validate a radiomics signature for stratifying the risk of progression-free survival (PFS) in patients with locally advanced hypopharyngeal carcinoma (LAHC) undergoing induction chemotherapy (IC).

METHODS

We extracted radiomics features from baseline contrast-enhanced computed tomography (CECT) images. We enrolled 112 LAHC patients (78 in the training cohort and 34 in the validation cohort). We used cox regression model and random survival forests variable hunting (RSFVH) algorithm for feature selection and radiomics signature building. The radiomics signature was established in the training cohort and tested in the validation cohort. We used the Kaplan-Meier analysis and log-rank test to evaluate the ability of radiomics signature in PFS risk stratification among patients with different IC responses and constructed a radiomics nomogram to predict individual PFS risk.

RESULTS

The radiomics signature performed well in stratifying patients into highrisk and low-risk groups of progression in both the training and validation cohorts. The radiomics nomogram showed good discriminative ability for predicting PFS. Survival outcome analysis of subsets indicated that the radiomics signature performed well in stratifying the risk of PFS in patients with LAHC with different IC responses.

CONCLUSIONS

The radiomics signature was a pretreatment predictor for PFS in patients with LAHC who exhibited different responses to IC.

Multiparametric MRI Radiomics for the Early Prediction of Response to Chemoradiotherapy in Patients With Postoperative Residual Gliomas: An Initial Study

Purpose

To evaluate whether multiparametric magnetic resonance imaging (MRI)-based logistic regression models can facilitate the early prediction of chemoradiotherapy response in patients with residual brain gliomas after surgery.

Patients and Methods

A total of 84 patients with residual gliomas after surgery from January 2015 to September 2020 who were treated with chemoradiotherapy were retrospectively enrolled and classified as treatment-sensitive or treatment-insensitive. These patients were divided into a training group (from institution 1, 57 patients) and a validation group (from institutions 2 and 3, 27 patients). All preoperative and postoperative MR images were obtained, including T1-weighted (T1-w), T2-weighted (T2-w), and contrast-enhanced T1-weighted (CET1-w) images. A total of 851 radiomics features were extracted from every imaging series. Feature selection was performed with univariate analysis or in combination with multivariate analysis. Then, four multivariable logistic regression models derived from T1-w, T2-w, CET1-w and Joint series (T1+T2+CET1-w) were constructed to predict the response of postoperative residual gliomas to chemoradiotherapy (sensitive or insensitive). These models were validated in the validation group. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were applied to compare the predictive performances of these models.

Results

Four models were created and showed the following areas under the ROC curves (AUCs) in the training and validation groups: Model-Joint series (AUC, 0.923 and 0.852), Model-T1 (AUC, 0.835 and 0.809), Model-T2 (AUC, 0.784 and 0.605), and Model-CET1 (AUC, 0.805 and 0.537). These results indicated that the Model-Joint series had the best performance in the validation group, followed by Model-T1, Model-T2 and finally Model-CET1. The calibration curves indicated good agreement between the Model-Joint series predictions and actual probabilities. Additionally, the DCA curves demonstrated that the Model-Joint series was clinically useful.

Conclusion

Multiparametric MRI-based radiomics models can potentially predict tumor response after chemoradiotherapy in patients with postoperative residual gliomas, which may aid clinical decision making, especially to help patients initially predicted to be treatment-insensitive avoid the toxicity of chemoradiotherapy.

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.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Correlations between DW-MRI and 18 F-FDG PET/CT parameters in head and neck squamous cell carcinoma following definitive chemo-radiotherapy

BACKGROUND

Posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) and 18F-fluorodeoxygluocose (18 F-FDG) positron emission tomography (PET) with computed tomography (PET/CT) have potential prognostic value following chemo-radiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC). Correlations between these PET/CT (standardized uptake value or SUV) and DW-MRI (apparent diffusion coefficient or ADC) parameters have only been previously explored in the pretreatment setting.

AIM

To evaluate stage III and IV HNSCC at 12-weeks post-CRT for the correlation between SUVmax and ADC values and their interval changes from pretreatment imaging.

METHODS

Fifty-six patients (45 male, 11 female, mean age 59.9 + - 7.38) with stage 3 and 4 HNSCC patients underwent 12-week posttreatment DW-MRI and 18 F-FDG PET/CT studies in this prospective study. There were 41/56 patients in the cohort with human papilloma virus-related oropharyngeal cancer (HPV OPC). DW-MRI (ADCmax and ADCmin) and 18 F-FDG PET/CT (SUVmax and SUVmax ratio to liver) parameters were measured at the site of primary tumors (n = 48) and the largest lymph nodes (n = 52). Kendall's tau evaluated the correlation between DW-MRI and 18 F-FDG PET/CT parameters. Mann-Whitney test compared the post-CRT PET/CT and DW-MRI parameters between those participants with and without 2-year disease-free survival (DFS).

RESULTS

There was no correlation between DW-MRI and 18 F-FDG PET/CT parameters on 12-week posttreatment imaging (P = .455-.794; tau = -0.075-0.25) or their interval changes from pretreatment to 12-week posttreatment imaging (P = .1-.946; tau = -0.194-0.044). The primary tumor ADCmean (P = .03) and the interval change in nodal ADCmin (P = .05) predicted 2-year DFS but none of the 18 F-FDG PET/CT parameters were associated with 2-year DFS.

CONCLUSIONS

There is no correlation between the quantitative DWI-MRI and 18 F-FDG PET/CT parameters derived from 12-week post-CRT studies. These parameters may be independent biomarkers however in this HPV OPC dominant cohort, only selected ADC parameters demonstrated prognostic significance. Study was prospectively registered at http://www.controlled-trials.com/ISRCTN58327080.

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.

Targeting Treatment Resistance in Head and Neck Squamous Cell Carcinoma - Proof of Concept for CT Radiomics-Based Identification of Resistant Sub-Volumes

Purpose

Radiomics has already been proposed as a prognostic biomarker in head and neck cancer (HNSCC). However, its predictive power in radiotherapy has not yet been studied. Here, we investigated a local radiomics approach to distinguish between tumor sub-volumes with different levels of radiosensitivity as a possible target for radiation dose intensification.

Materials and Methods

Of 40 patients (n=28 training and n=12 validation) with biopsy confirmed locally recurrent HNSCC, pretreatment contrast-enhanced CT images were registered with follow-up PET/CT imaging allowing identification of controlled (GTVcontrol) vs non-controlled (GTVrec) tumor sub-volumes on pretreatment imaging. A bi-regional model was built using radiomic features extracted from pretreatment CT in the GTVrec and GTVcontrol to differentiate between those regions. Additionally, concept of local radiomics was implemented to perform detection task. The original tumor volume was divided into sub-volumes with no prior information on the location of recurrence. Radiomic features from those sub-volumes were then used to detect recurrent sub-volumes using multivariable logistic regression.

Results

Radiomic features extracted from non-controlled regions differed significantly from those in controlled regions (training AUC = 0.79 CI 95% 0.66 - 0.91 and validation AUC = 0.88 CI 95% 0.72 – 1.00). Local radiomics analysis allowed efficient detection of non-controlled sub-volumes both in the training AUC = 0.66 (CI 95% 0.56 – 0.75) and validation cohort 0.70 (CI 95% 0.53 – 0.86), however performance of this model was inferior to bi-regional model. Both models indicated that sub-volumes characterized by higher heterogeneity were linked to tumor recurrence.

Conclusion

Local radiomics is able to detect sub-volumes with decreased radiosensitivity, associated with location of tumor recurrence in HNSCC in the pre-treatment CT imaging. This proof of concept study, indicates that local CT radiomics can be used as predictive biomarker in radiotherapy and potential target for dose intensification.

Diagnostic Accuracy of Combined PET/CT with MRI, 18F-FDG PET/MRI, and 18F-FDG PET/CT in Patients with Oropharyngeal and Hypopharyngeal Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

Introduction

The aim of this paper is to compare the diagnostic accuracy of PET/CT, PET/MRI, and the combination of PET/CT and MRI for detecting synchronous cancer and distant metastasis in patients with oropharyngeal and hypopharyngeal squamous cell carcinomas (OHSCC).

Method

A large and growing body of literature has been conducted using the Preferred Reporting Items for Systematic Reviews (PRISMA). The researchers collected all accessible literature existing through Cochrane Library (John Wiley & Sons) electronic databases, Embase (Elsevier), PubMed (U.S. National Library of Medicine), Scopus, and Google Scholar up to June 2020. Analyses were conducted using Stata version 12.0 (StataCorp LP).

Results

A total of nine studies consisting of 1166 patients were included. The pooled sensitivity of combined PET/CT with MRI, 18F-FDG PET/MRI, and 18F-FDG PET/CT was 0.92, 0.80, and 0.79, respectively, and the corresponding specificities were 0.93, 0.91, and 0.88. The overall prevalence of distant metastases and synchronous cancer in patients with oropharyngeal and hypopharyngeal squamous cell carcinomas was 9.2% and 11.8%, respectively, with the esophagus (4.6%) being the most common site of synchronous cancer. The most common sites of distant metastases were lung (3%), bone (1.2%), and distant lymph nodes (1.2%), respectively.

Conclusion

Our study showed an approximately similar diagnostic performance for PET/CT, PET/MRI, and the combination of PET/CT and MRI for metastasis assessment in advanced oropharyngeal and hypopharyngeal squamous cell carcinomas.

Improved outcome prediction of oropharyngeal cancer by combining clinical and MRI features in machine learning models

OBJECTIVES

New markers are required to predict chemoradiation response in oropharyngeal squamous cell carcinoma (OPSCC) patients. This study evaluated the ability of magnetic resonance (MR) radiomics to predict locoregional control (LRC) and overall survival (OS) after chemoradiation and aimed to determine whether this has added value to traditional clinical outcome predictors.

METHODS

177 OPSCC patients were eligible for this study. Radiomic features were extracted from the primary tumor region in T1-weighted postcontrast MRI acquired before chemoradiation. Logistic regression models were created using either clinical variables (clinical model), radiomic features (radiomic model) or clinical and radiomic features combined (combined model) to predict LRC and OS 2-years posttreatment. Model performance was evaluated using area under the curve (AUC), 95 % confidence intervals were calculated using 500 iterations of bootstrap. All analyses were performed for the total population and the Human papillomavirus (HPV) negative tumor subgroup.

RESULTS

A combined model predicted treatment outcome with a higher AUC (LRC: 0.745 [0.734-0.757], OS: 0.744 [0.735-0.753]) than the clinical model (LRC: 0.607 [0.594-0.620], OS: 0.708 [0.697-0.719]). Performance of the radiomic model was comparable to the combined model for LRC (AUC: 0.740 [0.729-0.750]), but not for OS prediction (AUC: 0.654 [0.646-0.662]). In HPV negative patients, the performance of all models was not sufficient with AUCs ranging from 0.587 to 0.660 for LRC and 0.559 to 0.600 for OS prediction.

CONCLUSION

Predictive models that include clinical variables and radiomic tumor features derived from MR images of OPSCC better predict LRC after chemoradiation than models based on only clinical variables. Predictive models that include clinical variables perform better than models based on only radiomic features for the prediction of OS.

Combing MRI Perfusion and 18F-FDG PET/CT Metabolic Biomarkers Helps Predict Survival in Advanced Nasopharyngeal Carcinoma: A Prospective Multimodal Imaging Study

We prospectively investigated the prognostic value of imaging parameters for nasopharyngeal carcinoma (NPC) using dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted imaging (DWI), and 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography (¹⁸F-FDG PET)/computed tomography (CT). Patients with stage III-IVb NPC underwent F-FDG PET/CT, DCE-MRI, and DWI before treatment. Kaplan-Meier and Cox-regression analyses were used to assess associations of PET and MRI imaging biomarkers with overall survival (OS) and recurrence-free survival (RFS). We used independent prognosticators to establish prognostic models; model performance was examined using Harrell's concordance index (c-index). Sixty-one patients were available for analysis, as 13 patients died and 20 experienced recurrence. Total lesion glycolysis (TLG) (p = 0.002) from PET/CT and the initial area under the curve (iAUC) (p = 0.036) from DCE-MRI were identified as independent prognosticators of OS; Epstein-Barr virus (EBV) DNA (p = 0.027), the extracellular volume fraction (V_e) (p = 0.027) from DCE-MRI, and TLG/iAUC (p = 0.025) were significant predictors of RFS. The c-indices of the prognostic models incorporating TLG + iAUC in predicting OS and incorporating EBV DNA + V_e + TLG/iAUC in predicting RFS were 0.79 and 0.76, respectively. These were significantly higher than the corresponding c-indices of the TNM staging system (p = 0.047 and 0.025, respectively); they were also higher than those of models with only MRI or PET biomarkers. In conclusion, the combination of pretreatment DCE-MRI and ¹⁸F-FDG PET/CT imaging biomarkers helps survival prediction in advanced NPC. Integrating MRI perfusion with PET metabolism and plasma EBV information may aid clinicians in planning the optimal personalized management strategy.

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.

Value of quantitative dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging in predicting extramural venous invasion in locally advanced gastric cancer and prognostic significance

Background

Extramural venous invasion (EMVI) has been found to be related to poor prognosis in gastric cancer. Preoperative diagnosis of EMVI is challenging, as it can only be detected by surgical pathology. The present study aimed to investigate the value of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in predicting EMVI preoperatively, and to determine the relationship between prediction results and prognosis in patients with locally advanced gastric cancer (LAGC).

Methods

Between January, 2015, and June, 2017, 79 LAGC patients underwent MRI preoperatively were enrolled in this study. Pathological EMVI (pEMVI) was used as the gold standard for diagnosis. The differences in quantitative DCE-MRI and DWI parameters between groups with different pEMVI status were analyzed. Multivariate logistic regression was used to build the combined prediction model for pEMVI with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) analysis. Patients were grouped based on MRI-predicted EMVI (mrEMVI). Kaplan-Meier analysis was used to investigate the relationship between mrEMVI and 2-year recurrence-free survival (RFS).

Results

Of the 79 LAGC patients who underwent MRI, 29 were pEMVI positive and 50 were pEMVI negative. Among the patients' clinical and pathological characteristics, only postoperative staging showed a significant difference between the 2 groups (P=0.015). The pEMVI-positive group had higher volume transfer constant (K^trans) and rate constant (k_ep), and lower apparent diffusion coefficient (ADC) values than the negative group (0.189 vs. 0.082 min^-1, 0.687 vs. 0.475 min^-1, and 1.230×10^-3 vs. 1.463×10^-3 mm²/s, respectively; P<0.05). Quantitative parameters, K^trans and k_ep, and ADC values, were independently associated with pEMVI which odds ratio values were 3.66, 2.65, and 0.30 (P<0.05), respectively, using multivariate logistic regression. ROC analysis showed that the area under the curve, sensitivity, specificity, positive predictive value, and negative predictive value in predicting pEMVI using combined K^trans, k_ep, and ADC values were 0.879, 72.4%, 96%, 91.3%, and 85.7%, respectively. A total of 23 cases were considered to be mrEMVI positive, and 56 cases were considered to be mrEMVI negative, according to the predictive results. The median RFS of the mrEMVI-positive group was significant lower than the negative group (21.7 vs. 31.2 months), and the 2-year RFS rate in the mrEMVI-positive group was significantly lower than that of the negative group (43.6% vs. 72.5%, P=0.010).

Conclusions

The quantitative DCE-MRI parameters, K^trans and k_ep, and DWI parameter, ADC, are independent predictors of pEMVI in LAGC; mrEMVI was confirmed to be a poor prognostic predictor for RFS.

Multiple Testing, Cut-Point Optimization, and Signs of Publication Bias in Prognostic FDG-PET Imaging Studies of Head and Neck and Lung Cancer: A Review and Meta-Analysis

Positron emission tomography (PET) imaging with 2-deoxy-2-[¹⁸F]-fluorodeoxyglucose (FDG) was proposed as prognostic marker in radiotherapy. Various uptake metrics and cut points were used, potentially leading to inflated effect estimates. Here, we performed a meta-analysis and systematic review of the prognostic value of pretreatment FDG–PET in head and neck squamous cell carcinoma (HNSCC) and non-small cell lung cancer (NSCLC), with tests for publication bias. Hazard ratio (HR) for overall survival (OS), disease free survival (DFS), and local control was extracted or derived from the 57 studies included. Test for publication bias was performed, and the number of statistical tests and cut-point optimizations were registered. Eggers regression related to correlation of SUVmax with OS/DFS yielded p = 0.08/p = 0.02 for HNSCC and p < 0.001/p = 0.014 for NSCLC. No outcomes showed significant correlation with SUVmax, when adjusting for publication bias effect, whereas all four showed a correlation in the conventional meta-analysis. The number of statistical tests and cut points were high with no indication of improvement over time. Our analysis showed significant evidence of publication bias leading to inflated estimates of the prognostic value of SUVmax. We suggest that improved management of these complexities, including predefined statistical analysis plans, are critical for a reliable assessment of FDG–PET.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for pretreatment prediction of neoadjuvant chemotherapy response in locally advanced hypopharyngeal cancer

Objective:The aim of this study was to predict response to neoadjuvant chemotherapy (NAC) in patients with locally advanced hypopharyngeal cancer by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Methods:A retrospective study enrolled 46 diagnosed locally advanced hypopharyngeal cancer. DCE-MRI were performed prior to and after two cycles of NAC. The volume transfer constant (K^trans), extracellular extravascular volume fraction (V_e), and plasma volume fraction (K_ep) were computed from primary tumors. DCE-MRI parameters were used to measure tumor response according to the Response Evaluation Criteria in Solid Tumors criteria (RECIST).Results：After 2 NAC cycles, 30 out of 46 patients were categorized into the responder group, whereas the other 16 were categorized into non-responder group. Compared with the pretreatment value, the post-treatment K^trans and K_ep was significantly lower (P < 0.05), but no significant change in V_e (P > 0.05). Compared with non-responders, a notably higher pretreatment K^trans, K_ep, lower post-treatment K^trans, higher ΔK^trans and ΔK_ep were observed in responders (all P < 0.05). While the pretreatment V_e, post-treatment V_e, and ΔV_e did not differ significantly (P>0.05) between the two groups. The receiver operating characteristic curve analysis revealed that pretreatment K^trans of 0.202/min is the most optimal cut-off in predicting response to chemotherapy, resulting in an AUC of 0.837 and corresponding sensitivity and specificity of 76.7%, and 81.1%, respectively.Conclusion:DCE-MRI especially pretreatment K^trans can potentially predict the treatment response to neoadjuvant chemotherapy for hypopharyngeal cancer.Advances in knowledge:Few studies of DCE-MRI on hypopharyngeal cancer treated with chemoradiation reported. The results demonstrate that DCE-MRI especially pretreatment K^trans may be more potential value in predicting the treatment response to neoadjuvant chemotherapy for hypopharyngeal cancer.

Quantitative dynamic contrast-enhanced MR imaging can be used to predict the pathologic stages of oral tongue squamous cell carcinoma

Background

To investigate whether quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) pharmacokinetic parameters can be used to predict the pathologic stages of oral tongue squamous cell carcinoma (OTSCC).

Methods

For this prospective study, DCE-MRI was performed in participants with OTSCC from May 2016 to June 2017. The pharmacokinetic parameters, including K^trans, K_ep, V_e, and V_p, were derived from DCE-MRI by utilizing a two-compartment extended Tofts model and a three-dimensional volume of interest. The postoperative pathologic stage was determined in each patient based on the 8th AJCC cancer staging manual. The quantitative DCE-MRI parameters were compared between stage I–II and stage III–IV lesions. Logistic regression analysis was used to determine independent predictors of tumor stages, followed by receiver operating characteristic (ROC) analysis to evaluate the predictive performance.

Results

The mean K^trans, K_ep and V_p values were significantly lower in stage III–IV lesions compared with stage I–II lesions (p = 0.013, 0.005 and 0.011, respectively). K_ep was an independent predictor for the advanced stages as determined by univariate and multivariate logistic analysis. ROC analysis showed that K_ep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a positive predictive value of 81.8%, a negative predictive value of 65.5%, and an accuracy of 72.5%.

Conclusion

The quantitative DCE-MRI parameter K_ep can be used as a biomarker for predicting pathologic stages of OTSCC.

Multiparametric functional MRI and 18F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation

Objectives

To assess (I) correlations between diffusion-weighted (DWI), intravoxel incoherent motion (IVIM), dynamic contrast-enhanced (DCE) MRI, and ¹⁸F-FDG-PET/CT imaging parameters capturing tumor characteristics and (II) their predictive value of locoregional recurrence-free survival (LRFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy.

Methods

Between 2014 and 2018, patients with histopathologically proven HNSCC, planned for curative (chemo) radiotherapy, were prospectively included. Pretreatment clinical, anatomical, and functional imaging parameters (obtained by DWI/IVIM, DCE-MRI, and ¹⁸F-FDG-PET/CT) were extracted for primary tumors (PT) and lymph node metastases. Correlations and differences between parameters were assessed. The predictive value of LRFS and OS was assessed, performing univariable, multivariable Cox and CoxBoost regression analyses.

Results

In total, 70 patients were included. Significant correlations between ¹⁸F-FDG-PET parameters and DWI-/DCE volume parameters were found (r > 0.442, p < 0.002). The combination of HPV (HR = 0.903), intoxications (HR = 1.065), PT ADC_GTV (HR = 1.252), K^trans (HR = 1.223), and V_e (HR = 1.215) was predictive for LRFS (C-index = 0.546; p = 0.023). N-stage (HR = 1.058), HPV positivity (HR = 0.886), hypopharyngeal tumor location (HR = 1.111), ADC_GTV (HR = 1.102), ADC_mean (HR = 1.137), D* (HR = 0.862), K^trans (HR = 1.106), V_e (HR = 1.195), SUV_max (HR = 1.094), and TLG (HR = 1.433) were predictive for OS (C-index = 0.664; p = 0.046).

Conclusions

Functional imaging parameters, performing DWI/IVIM, DCE-MRI, and ¹⁸F-FDG-PET/CT, yielded complementary value in capturing tumor characteristics. More specific, intoxications, HPV-negative status, large tumor volume-related parameters, high permeability (K^trans), and high extravascular extracellular space (V_e) parameters were predictive for adverse locoregional recurrence-free survival and adverse overall survival. Low cellularity (high ADC) and high metabolism (high SUV) were additionally predictive for decreased overall survival. These different predictive factors added to estimated locoregional and overall survival.

Key Points

• Parameters of DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT were able to capture complementary tumor characteristics.

• Multivariable analysis revealed that intoxications, HPV negativity, large tumor volume and high vascular permeability (K^trans), and extravascular extracellular space (Ve) were complementary predictive for locoregional recurrence.

• In addition to predictive parameters for locoregional recurrence, also high cellularity (low ADC) and high metabolism (high SUV) were complementary predictive for overall survival.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07163-3) contains supplementary material, which is available to authorized users.

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.

Multiparametric positron emission tomography/magnetic resonance imaging in nasopharyngeal carcinoma: Correlations between magnetic resonance imaging functional parameters and 18F-fluorodeoxyglucose positron emission tomography imaging biomarkers and their predictive value for treatment failure

Objectives:

The clinical significance of positron emission tomography/magnetic resonance imaging (PET/MRI) functional parameters in nasopharyngealcarcinoma (NPC) remains unclear. The purpose of this prospective study was two-fold: (1) to investigate the associations between simultaneously acquired PET/MRI perfusion, diffusion, and glucose metabolism parameters in patients with NPC and (2) to analyze their predictive value with respect to treatment failure.

Materials and Methods:

We enrolled 85 patients with primary NPC who simultaneously underwent¹⁸F-fluorodeoxyglucose PET/CT and PET/MRI before definitive treatment. The following variables were determined: (1) functional parameters from the MRI component, including perfusion values (K^trans,k_ep,v_e, and initial area under the enhancement curve) and apparent diffusion coefficient (ADC) values, and (2) PET parameters, including metabolic tumor volume (MTV). The reciprocal interrelationships between these parameters and their correlations with treatment failure were examined.

Results:

We observed significant negative associations between K^trans and ADC (r = −0.215, P = 0.049) as well as between v_e and ADC (r = −0.22, P = 0.04). Correlations between PET and MRI functional parameters were not statistically significant. Treatment failures were observed in 21.2% of patients without distant metastases. Multivariate analysis identified v_e as a significant independent predictor for treatment failure (P = 0.022), whereas MTV showed a borderline significance (P = 0.095). Patients in whom both v_e and MTV values were increased had a significantly higher rate of treatment failure (62.5%) than those with either one (21.9%) or no (7.7%) increased parameter (P = 0.004).

Conclusion:

Correlation analyses revealed complex interrelationships among PET and MRI indices measured in patients with NPC. These parameters may have a complementary role in predicting treatment failure in this clinical setting.

Prognostic value of the radiomics-based model in progression-free survival of hypopharyngeal cancer treated with chemoradiation

PURPOSE

To develop a radiomics-based model to stratify the risk of early progression (local/regional recurrence or metastasis) among patients with hypopharyngeal cancer undergoing chemoradiotherapy and modify their pretreatment plans.

MATERIALS AND METHODS

We randomly assigned 113 patients into two cohorts: training (n = 80) and validation (n = 33). The radiomic significant features were selected in the training cohort using least absolute shrinkage and selection operator and Akaike information criterion methods, and they were used to build the radiomic model. The concordance index (C-index) was applied to evaluate the model's prognostic performance. A Kaplan-Meier analysis and the log-rank test were used to assess risk stratification ability of models in predicting progression. A nomogram was plotted to predict individual risk of progression.

RESULTS

Composed of four significant features, the radiomic model showed good performance in stratifying patients into high- and low-risk groups of progression in both the training and validation cohorts (log-rank test, p = 0.00016, p = 0.0063, respectively). Peripheral invasion and metastasis were selected as significant clinical variables. The combined radiomic-clinical model showed good discriminative performance, with C-indices 0.804 (95% confidence interval (CI), 0.688-0.920) and 0.756 (95% CI, 0.605-0.907) in the training and validation cohorts, respectively. The median progression-free survival (PFS) in the high-risk group was significantly shorter than that in the low-risk group in the training (median PFS, 9.5 m and 19.0 m, respectively; p [log-rank] < 0.0001) and validation (median PFS, 11.3 m and 22.5 m, respectively; p [log-rank] = 0.0063) cohorts.

CONCLUSIONS

A radiomics-based model was established to predict the risk of progression in hypopharyngeal cancer with chemoradiotherapy.

KEY POINTS

• Clinical information showed limited performance in stratifying the risk of progression among patients with hypopharyngeal cancer. • Imaging features extracted from CECT and NCCT images were independent predictors of PFS. • We combined significant features and valuable clinical variables to establish a nomogram to predict individual risk of progression.

Diagnosis of spinal lesions using perfusion parameters measured by DCE-MRI and metabolism parameters measured by PET/CT

PURPOSE

To investigate the correlation of parameters measured by dynamic-contrast-enhanced MRI (DCE-MRI) and ¹⁸F-FDG PET/CT in spinal tumors, and their role in differential diagnosis.

METHODS

A total of 49 patients with pathologically confirmed spinal tumors, including 38 malignant, six benign and five borderline tumors, were analyzed. The MRI and PET/CT were done within 3 days, before biopsy. On MRI, the ROI was manually placed on area showing the strongest enhancement to measure pharmacokinetic parameters K^trans and k_ep. On PET, the maximum standardized uptake value SUV_max was measured. The parameters in different histological groups were compared. ROC was performed to differentiate between the two largest subtypes, metastases and plasmacytomas. Spearman rank correlation was performed to compare DCE-MRI and PET/CT parameters.

RESULTS

The K^trans, k_ep and SUV_max were not statistically different among malignant, benign and borderline groups (P = 0.95, 0.50, 0.11). There was no significant correlation between K^trans and SUV_max (r = - 0.20, P = 0.18), or between k_ep and SUV_max (r = - 0.16, P = 0.28). The k_ep was significantly higher in plasmacytoma than in metastasis (0.78 ± 0.17 vs. 0.61 ± 0.18, P = 0.02); in contrast, the SUV_max was significantly lower in plasmacytoma than in metastasis (5.58 ± 2.16 vs. 9.37 ± 4.26, P = 0.03). In differential diagnosis, the AUC of k_ep and SUV_max was 0.79 and 0.78, respectively.

CONCLUSIONS

The vascular parameters measured by DCE-MRI and glucose metabolism measured by PET/CT from the most aggressive tumor area did not show a significant correlation. The results suggest they provide complementary information reflecting different aspects of the tumor, which may aid in diagnosis of spinal lesions. These slides can be retrieved under Electronic Supplementary Material.

Textural features on 18F-FDG PET/CT and dynamic contrast-enhanced MR imaging for predicting treatment response and survival of patients with hypopharyngeal carcinoma

The utility of multimodality molecular imaging for predicting treatment response and survival of patients with hypopharyngeal carcinoma remains unclear. Here, we sought to investigate whether the combination of different molecular imaging parameters may improve outcome prediction in this patient group.Patients with pathologically proven hypopharyngeal carcinoma scheduled to undergo chemoradiotherapy (CRT) were deemed eligible. Besides clinical data, parameters obtained from pretreatment 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT), dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and diffusion-weighted MRI were analyzed in relation to treatment response, recurrence-free survival (RFS), and overall survival (OS).A total of 61 patients with advanced-stage disease were examined. After CRT, 36% of the patients did not achieve a complete response. Total lesion glycolysis (TLG) and texture feature entropy were found to predict treatment response. The transfer constant (K), TLG, and entropy were associated with RFS, whereas K, blood plasma volume (Vp), standardized uptake value (SUV), and entropy were predictors of OS. Different scoring systems based on the sum of PET- or MRI-derived prognosticators enabled patient stratification into distinct prognostic groups (P <.0001). The complete response rate of patients with a score of 2 was significantly lower than those of patients with a score 1 or 0 (14.7% vs 58.9% vs 75.7%, respectively, P = .007, respectively). The combination of PET- and DCE-MRI-derived independent risk factors allowed a better survival stratification than the TNM staging system (P <.0001 vs .691, respectively).Texture features on F-FDG PET/CT and DCE-MRI are clinically useful to predict treatment response and survival in patients with hypopharyngeal carcinoma. Their combined use in prognostic scoring systems may help these patients benefit from tailored treatment and obtain better oncological results.

Prognostic role of diffusion weighted and dynamic contrast-enhanced MRI in loco-regionally advanced head and neck cancer treated with concomitant chemoradiotherapy

Background In the study, the value of pre-treatment dynamic contrast-enhanced (DCE) and diffusion weighted (DW) MRI-derived parameters as well as their changes early during treatment was evaluated for predicting disease-free survival (DFS) and overall survival (OS) in patients with locoregionally advanced head and neck squamous carcinoma (HNSCC) treated with concomitant chemoradiotherapy (cCRT) with cisplatin. Patients and methods MRI scans were performed in 20 patients with locoregionally advanced HNSCC at baseline and after 10 Grays (Gy) of cCRT. Tumour apparent diffusion coefficient (ADC) and DCE parameters (volume transfer constant [Ktrans], extracellular extravascular volume fraction [ve], and plasma volume fraction [Vp]) were measured. Relative changes in parameters from baseline to 10 Gy were calculated. Univariate and multivariate Cox regression analysis were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify parameters with the best diagnostic performance. Results None of the parameters was identified to predict for DFS. On univariate analysis of OS, lower pre-treatment ADC (p = 0.012), higher pre-treatment Ktrans (p = 0.026), and higher reduction in Ktrans (p = 0.014) from baseline to 10 Gy were identified as significant predictors. Multivariate analysis identified only higher pre-treatment Ktrans (p = 0.026; 95% CI: 0.000-0.132) as an independent predictor of OS. At ROC curve analysis, pre-treatment Ktrans yielded an excellent diagnostic accuracy (area under curve [AUC] = 0.95, sensitivity 93.3%; specificity 80 %). Conclusions In our group of HNSCC patients treated with cisplatin-based cCRT, pre-treatment Ktrans was found to be a good predictor of OS.

Differential diagnostic value of diffusion-weighted and dynamic contrast-enhanced MR imaging in non-cystic lesions in floor of the mouth

METHODS:

A total of 82 patients were included in this study. The apparent diffusion coefficient (ADC) values and time-signal intensity curves (TICs) were measured. Clinical characteristics, ADC value, and TIC pattern were compared between benign and malignant FOM lesions. Receiver operating characteristic curve and logistic regression analyses were performed to evaluate respective and combined value of ADC value and TIC pattern for differential diagnosis. The retrospective study was approved by our institutional review board, and the need for informed consent was waived.

RESULTS:

The area under the curve ADC value and TIC pattern were 0.71 and 0.73, respectively. The combined use of ADC value and TIC pattern increased the area under the curve value to 0.81 [95% confidence interval (CI), (0.66-0.97)]. ADC < 1.23 × 10^-3 mm² s^-1 (odds ratio, 45.8; 95% CI, 2.8-737.9) and both the plateau and washout TIC patterns (OR, 6.8; 95% CI, 1.8-24.8) were significantly associated with malignancy of FOM lesions.

CONCLUSIONS:

Our results suggest that both diffusion-weighted imaging and DCE-MRI could contribute to the differential diagnosis of non-cystic FOM lesions, especially when used in combination.

Associations between Histogram Analysis Parameters Derived from DCE-MRI and Histopathological Features including Expression of EGFR, p16, VEGF, Hif1-alpha, and p53 in HNSCC

Background

Our purpose was to elucidate possible correlations between histogram parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) with several histopathological features in head and neck squamous cell carcinomas (HNSCC).

Methods

Thirty patients with primary HNSCC were prospectively acquired. Histogram analysis was derived from the DCE-MRI parameters: K_trans, K_ep, and V_e. Additionally, in all cases, expression of human papilloma virus (p16) hypoxia-inducible factor-1-alpha (Hif1-alpha), vascular endothelial growth factor (VEGF), epidermal growth factor receptor (EGFR), and tumor suppressor protein p53 were estimated.

Results

K_ep kurtosis was significantly higher in p16 tumors, and V_e min was significantly lower in p16 tumors compared to the p16 negative tumors. In the overall sample, K_ep entropy correlated well with EGFR expression (p=0.38, P=0.04). In p16 positive carcinomas, K_trans max correlated with VEGF expression (p=0.46, P=0.04), K_trans kurtosis correlated with Hif1-alpha expression (p=0.46, P=0.04), and K_trans entropy correlated with EGFR expression (p=0.50, P=0.03). Regarding K_ep parameters, mode correlated with VEGF expression (p=0.51, P=0.02), and entropy correlated with Hif1-alpha expression (p=0.47, P=0.04). In p16 negative carcinomas, K_ep mode correlated with Her2 expression (p=−0.72, P=0.03), V_e max correlated with p53 expression (p=−0.80, P=0.009), and V_e p10 correlated with EGFR expression (p=0.68, P=0.04).

Conclusion

DCE-MRI can reflect several histopathological features in HNSCC. Associations between DCE-MRI and histopathology in HNSCC depend on p16 status. K_ep kurtosis and V_e min can differentiate p16 positive and p16 negative carcinomas.

What is the prognostic impact of FDG PET in locally advanced head and neck squamous cell carcinoma treated with concomitant chemo-radiotherapy? A systematic review and meta-analysis

PURPOSE

Evidence is conflicting on the prognostic value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in head and neck squamous cell carcinoma. The aim of our study was to determine the impact of semiquantitative and qualitative metabolic parameters on the outcome in patients managed with standard treatment for locally advanced disease.

METHODS

A systematic review of the literature was conducted. A meta-analysis was performed of studies providing estimates of relative risk (RR) for the association between semiquantitative metabolic parameters and efficacy outcome measures.

RESULTS

The analysis included 25 studies, for a total of 2,223 subjects. The most frequent primary tumour site was the oropharynx (1,150/2,223 patients, 51.7%). According to the available data, the majority of patients had stage III/IV disease (1,709/1,799, 94.9%; no information available in four studies) and were treated with standard concurrent chemoradiotherapy (1,562/2,009 patients, 77.7%; only one study without available information). A total of 11, 8 and 4 independent studies provided RR estimates for the association between baseline FDG PET metrics and overall survival (OS), progression-free survival (PFS) and locoregional control (LRC), respectively. High pretreatment metabolic tumour volume (MTV) was significantly associated with a worse OS (summary RR 1.86, 95% CI 1.08-3.21), PFS (summary RR 1.81, 95% CI 1.14-2.89) and LRC (summary RR 3.49, 95% CI 1.65-7.35). Given the large heterogeneity (I2 > 50%) affecting the summary measures, no cumulative threshold for an unfavourable prognosis could be defined. No statistically significant association was found between SUVmax and any of the outcome measures.

CONCLUSION

FDG PET has prognostic relevance in the context of locally advanced head and neck squamous cell carcinoma. Pretreatment MTV is the only metabolic variable with a significant impact on patient outcome. Because of the heterogeneity and the lack of standardized methodology, no definitive conclusions on optimal cut-off values can be drawn.

Adaptive Boost Target Definition in High-Risk Head and Neck Cancer Based on Multi-imaging Risk Biomarkers

PURPOSE

Positron emission tomography with ¹⁸F-deoxyglucose (FDG), dynamic contrast-enhanced magnetic resonance imaging (MRI), and diffusion-weighted MRI each identify unique risk factors for treatment outcomes in head and neck cancer (HNC). Clinical trials in HNC largely rely on a single imaging modality to define targets for boosting. This study aimed to investigate the spatial correspondence of FDG uptake, perfusion, and the apparent diffusion coefficient (ADC) in HNC and their response to chemoradiation therapy (CRT) and to determine the implications of this overlap or lack thereof for adaptive boosting.

METHODS AND MATERIALS

Forty patients with HNC enrolled in a clinical trial underwent FDG positron emission tomography-computed tomography before CRT and underwent dynamic contrast-enhanced and diffusion-weighted MRI scans before and during CRT. The gross tumor volume (GTV) of the primary tumor was contoured on post-gadolinium T1-weighted images. Tumor subvolumes with high FDG uptake, low blood volume (BV), and low ADC were created by using previously established thresholds. Spatial correspondences between subvolumes were analyzed using the Dice coefficient, and those between each pair of image parameters at voxel level were analyzed by Spearman rank correlation coefficients.

RESULTS

Prior to CRT, the median subvolumes of high FDG, low BV, and low ADC relative to the primary GTV were 20%, 21%, and 45%, respectively. Spearman correlation coefficients between BV and ADC varied from -0.47 to 0.22; between BV and FDG, from -0.08 to 0.59; and between ADC and FDG, from -0.68 to 0.25. Dice coefficients between subvolumes of FDG and BV, FDG and ADC, and BV and ADC were 10%, 46%, and 15%, respectively. The union of the 3 parameters was 64% of the GTV. The union of the subvolumes of BV and ADC was 56% of the GTV before CRT but was reduced significantly by 57% after 10 fractions of radiation therapy.

CONCLUSIONS

High FDG uptake, low BV, and low ADC as imaging risk biomarkers of HNC identify largely distinct tumor characteristics. A single imaging modality may not define the boosting target adequately.

CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy

BACKGROUND AND PURPOSE

The accurate prediction of prognosis and failure is crucial for optimizing treatment strategies for patients with cancer. The purpose of this study was to assess the performance of pretreatment CT texture analysis for the prediction of treatment failure in primary head and neck squamous cell carcinoma treated with chemoradiotherapy.

MATERIALS AND METHODS

This retrospective study included 62 patients diagnosed with primary head and neck squamous cell carcinoma who underwent contrast-enhanced CT examinations for staging, followed by chemoradiotherapy. CT texture features of the whole primary tumor were measured using an in-house developed Matlab-based texture analysis program. Histogram, gray-level co-occurrence matrix, gray-level run-length, gray-level gradient matrix, and Laws features were used for texture feature extraction. Receiver operating characteristic analysis was used to identify the optimal threshold of any significant texture parameter. We used multivariate Cox proportional hazards models to examine the association between the CT texture parameter and local failure, adjusting for age, sex, smoking, primary tumor stage, primary tumor volume, and human papillomavirus status.

RESULTS

Twenty-two patients (35.5%) developed local failure, and the remaining 40 (64.5%) showed local control. Multivariate analysis revealed that 3 histogram features (geometric mean [hazard ratio = 4.68, P = .026], harmonic mean [hazard ratio = 8.61, P = .004], and fourth moment [hazard ratio = 4.56, P = .048]) and 4 gray-level run-length features (short-run emphasis [hazard ratio = 3.75, P = .044], gray-level nonuniformity [hazard ratio = 5.72, P = .004], run-length nonuniformity [hazard ratio = 4.15, P = .043], and short-run low gray-level emphasis [hazard ratio = 5.94, P = .035]) were significant predictors of outcome after adjusting for clinical variables.

CONCLUSIONS

Independent primary tumor CT texture analysis parameters are associated with local failure in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.

Biologically adapted radiation therapy

The aim of biologically adapted radiotherapy (RT) is to shape or paint the prescribed radiation dose according to biological properties of the tumor in order to increase local control rates in the future. Human tumors are known to present with an extremely heterogeneous tissue architecture leading to highly variable local cell densities and chaotic vascular structures leading to tumor hypoxia and regions of increased radiation resistance. The goal of biologically adapted RT or dose painting is to individually adapt the radiation dose to biological features of the tumor as non-invasively assessed with functional imaging in order to overcome increased radiation resistance. This article discusses the whole development chain of biologically adapted RT from radio-biologically relevant processes, functional imaging techniques to visualize tumor biology non-invasively and radiation prescription functions to the implementation of biologically adapted RT in clinical practice.

State of the art MRI in head and neck cancer

Head and neck cancer affects more than 11,000 new patients per year in the UK¹ and imaging has an important role in the diagnosis, treatment planning, and assessment, and post-treatment surveillance of these patients. The anatomical detail produced by magnetic resonance imaging (MRI) is ideally suited to staging and follow-up of primary tumours and cervical nodal metastases in the head and neck; however, anatomical images have limitations in cancer imaging and so increasingly functional-based MRI techniques, which provide molecular, metabolic, and physiological information, are being incorporated into MRI protocols. This article reviews the state of the art of these functional MRI techniques with emphasis on those that are most relevant to the current management of patients with head and neck cancer.

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy.

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

Background

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

Methods

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

Results

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

Conclusions

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

Multimodality functional imaging using DW-MRI and 18F-FDG-PET/CT during radiation therapy for human papillomavirus negative head and neck squamous cell carcinoma: Meixoeiro Hospital of Vigo Experience

AIM

To noninvasively investigate tumor cellularity measured using diffusion-weighted magnetic resonance imaging (DW-MRI) and glucose metabolism measured by ¹⁸F-labeled fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) during radiation therapy (RT) for human papillomavirus negative (HPV-) head and neck squamous cell carcinoma (HNSCC).

METHODS

In this prospective study, 6 HPV- HNSCC patients underwent a total of 34 multimodality imaging examinations (DW-MRI at 1.5 T Philips MRI scanner [(n = 24) pre-, during- (2-3 wk), and post-treatment (Tx), and ¹⁸F-FDG PET/CT pre- and post-Tx (n = 10)]. All patients received RT. Monoexponential modeling of the DW-MRI data yielded the imaging metric apparent diffusion coefficient (ADC) and the mean of standardized uptake value (SUV) was measured from ¹⁸F-FDG PET uptake. All patients had a clinical follow-up as the standard of care and survival status was documented at 1 year.

RESULTS

There was a strong negative correlation between the mean of pretreatment ADC (ρ = -0.67, P = 0.01) and the pretreatment ¹⁸F-FDG PET SUV. The percentage (%) change in delta (∆) ADC for primary tumors and neck nodal metastases between pre- and Wk_2-3 Tx were as follows: 75.4% and 61.6%, respectively, for the patient with no evidence of disease, 27.5% and 32.7%, respectively, for those patients who were alive with disease, and 26.9% and 7.31%, respectively, for those who were dead with disease.

CONCLUSION

These results are preliminary in nature and are indicative, and not definitive, trends rendered by the imaging metrics due to the small sample size of HPV- HNSCC patients in a Meixoeiro Hospital of Vigo Experience.

Simultaneous (18)F-FDG-PET/MRI: Associations between diffusion, glucose metabolism and histopathological parameters in patients with head and neck squamous cell carcinoma

OBJECTIVES

To analyze possible associations between functional simultaneous (18)F-FDG-PET/MR imaging parameters and histopathological parameters in head and neck squamous cell carcinoma (HNSCC).

MATERIAL AND METHODS

11 patients (2 female, 9 male; mean age 56.0years) with biopsy-proven primary HNSCC underwent simultaneous (18)F-FDG-PET/MRI with a dedicated head and neck protocol including diffusion weighted imaging. For each tumor, glucose metabolism was estimated with standardized uptake values (SUV) and diffusion restriction was calculated using apparent diffusion coefficients (ADC). The tumor proliferation index was estimated on Ki 67 antigen stained specimens. Cell count, total nucleic area, and average nucleic area were estimated in each case. Pearson's correlation coefficient was used to analyze possible associations between the estimated parameters.

RESULTS

The mean SUVmax value was 24.41±6.51, and SUVmean value 15.01±4.07. Mean values (×10(-3)mm(2)s(-1)) of ADC parameters were as follows: ADCmin: 0.65±0.20; ADCmean: 1.28±0.18; and ADCmax: 2.16±0.35. Histopathological analysis identified the following results: cell count 1069.82±388.66, total nucleic area 150771.09±61177.12μm(2), average nucleic area 142.90±57.27μm(2) and proliferation index 49.09±22.67%. ADCmean correlated with Ki 67 level (r=-0.728, p=0.011) and total nucleic area (r=-0.691, p=0.019) and tended to correlate with average nucleic area (r=-0.527, p=0.096). ADCmax correlated with Ki 67 level (r=-0.633, p=0.036). SUVmax also tended to correlate with average nucleic area (r=0.573, p=0.066). Combined parameter SUVmax/ADCmin correlated with average nucleic area (r=0.627, p=0.039).

CONCLUSION

ADC and SUV values showed significant correlations with different histopathological parameters and can be used as biological markers in HNSCC.