A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling

Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome. For the development of radiomics risk models, a variety of different algorithms is available and it is not clear which one gives optimal results. Therefore, we assessed the performance of 11 machine learning algorithms combined with 12 feature selection methods by the concordance index (C-Index), to predict loco- regional tumour control (LRC) and overall survival for patients with head and neck squamous cell carcinoma. The considered algorithms are able to deal with continuous time-to-event survival data. Feature selection and model building were performed on a multicentre cohort (213 patients) and validated using an independent cohort (80 patients). We found several combinations of machine learning algorithms and feature selection methods which achieve similar results, e.g., MSR-RF: C-Index = 0.71 and BT-COX: C-Index = 0.70 in combination with Spearman feature selection. Using the best performing models, patients were stratified into groups of low and high risk of recurrence. Significant differences in LRC were obtained between both groups on the validation cohort. Based on the presented analysis, we identified a subset of algorithms which should be considered in future radiomics studies to develop stable and clinically relevant predictive models for time-to-event endpoints

PSMA-PET based radiotherapy: a review of initial experiences, survey on current practice and future perspectives

Gallium prostate specific membrane antigen (PSMA) ligand positron emission tomography (PET) is an increasingly used imaging modality in prostate cancer, especially in cases of tumor recurrence after curative intended therapy. Owed to the novelty of the PSMA-targeting tracers, clinical evidence on the value of PSMA-PET is moderate but rapidly increasing. State of the art imaging is pivotal for radiotherapy treatment planning as it may affect dose prescription, target delineation and use of concomitant therapy. This review summarizes the evidence on PSMA-PET imaging from a radiation oncologist’s point of view. Additionally a short survey containing twelve examples of patients and 6 additional questions was performed in seven mayor academic centers with experience in PSMA ligand imaging and the findings are reported here

Definition and validation of a radiomics signature for loco-regional tumour control in patients with locally advanced head and neck squamous cell carcinoma

Purpose: To develop and validate a CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG). Material and methods: Pre-treatment CT images of 318 patients with locally advanced HNSCC were col-lected. Four-hundred forty-six features were extracted from each primary tumour volume and then fil-tered through stability analysis and clustering. First, a baseline signature was developed from demographic and tumour-associated clinical parameters. This signature was then supplemented by CT imaging features. A final signature was derived using repeated 3-fold cross-validation on the discovery cohort. Performance in external validation was assessed by the concordance index (C-Index). Furthermore, calibration and patient stratification in groups with low and high risk for loco-regional recurrence were analysed. Results: For the clinical baseline signature, only the primary tumour volume was selected. The final sig-nature combined the tumour volume with two independent radiomics features. It achieved moderatel

DNA-Methylome based Tumor Hypoxia Classifier Identifies HPV-negative Head & Neck Cancer Patients at Risk for Locoregional Recurrence After Primary Radiochemotherapy

BACKGROUND Tumor hypoxia is a paradigmatic negative prognosticator of treatment resistance in Head and Neck Squamous Cell Carcinoma (HNSCC). The lack of robust and reliable hypoxia classifiers limits the adaptation of stratified therapies. We hypothesized that the tumor DNA methylation landscape might indicate epigenetic reprogramming induced by chronic intratumoral hypoxia. METHODS A DNA methylome-based tumor hypoxia classifier (Hypoxia-M) was trained in the TCGA-HNSCC cohort based on matched assignments using gene expression-based signatures of hypoxia (Hypoxia-GES). Hypoxia-M was validated in a multicenter DKTK-ROG trial consisting of Human Papilloma Virus (HPV)-negative HNSCC patients treated with primary radiochemotherapy (RCHT). RESULTS While hypoxia-GSEs failed to stratify patients in the DKTK-ROG, Hypoxia-M was independently prognostic for local recurrence (LR, HR=4.3, p=0.001) and overall survival (OS, HR=2.34, p=0.03) but not distant metastasis (DM) after RCHT in the both cohorts. Hypoxia-M status was inversely associated with CD8 T-cells infiltration in both cohorts. Hypoxia-M was further prognostic in the TCGA-PanCancer cohort (HR=1.83, p=0.04), underscoring the breadth of this classifier for predicting tumor hypoxia status. CONCLUSIONS Our findings highlight an unexplored avenue for DNA Methylation-based classifiers as biomarkers of tumoral hypoxia for identifying high-risk features in patients with HNSCC tumors. TRIAL REGISTRATION Retrospective observational study from the German Cancer Consortium (DKTK-ROG), not interventional

Veränderte Emotionsverarbeitung bei Tinnitus: Eine funktionelle Magnetresonanztomographie-Studie

Die Phantomwahrnehmung Tinnitus ist eine relativ häufige Störung des auditorischen Systems, die bei einigen Betroffenen zu Stress, Arbeitsunfähigkeit, Angststörungen und Depressionen führen kann. Die genauen pathophysiologischen Mechanismen, die an der Entstehung der Ohrgeräusche beteiligt sind, sind Gegenstand der Forschung. In verschiedenen funktionellen und strukturellen Bildgebungsstudien konnte gezeigt werden, dass Tinnitus zu funktionellen Veränderungen im auditorischen System führt. Es zeigten sich aber auch Veränderungen in ZNS-Regionen, die nicht primär am Hören beteiligt sind, zum Beispiel im limbischen System. Um der Frage nachzugehen, ob diese beobachteten Veränderungen auch zu einer veränderten Prozessierung emotionaler Reize bei Tinnituspatienten führen, untersuchten wir mittels funktioneller Magnetresonanztomographie die neuronale Antwort auf emotionale Reize. Es wurden zwölf Tinnituspatienten und zwölf gesunde Freiwillige untersucht. Hinsichtlich Alter und Hörschädigung unterschieden sich die Gruppen nicht. Es zeigte sich jedoch ein Unterschied in einem Cluster, das Amygdala, Hippocampus und Gyrus parahippocampalis umfasste. Während die Betrachtung von Gesichtern, die Gefühlsregungen ausdrückten, bei den Kontrollprobanden zu einer verstärkten Aktivierung in diesem Areal führte, wurde bei den Tinnituspatienten eine Deaktivierung beobachtet. Weiterhin zeigte sich eine signifikante Korrelation zwischen dem Ausmaß der Deaktivierung und dem Tinnitus-Schweregrad. Diese Ergebnisse belegen, dass Tinnituspatienten Veränderungen bei der Verarbeitung emotionaler Reize aufweisen. Weiter weisen sie darauf hin, dass Areale im medialen Temporallappen an der Pathophysiologie des Tinnitus beteiligt sind und dass die beobachteten Veränderungen mit dem Tinnitus-Schweregrad zusammenhängen können

Virtual Monoenergetic Images of Dual-Energy CT-Impact on Repeatability, Reproducibility, and Classification in Radiomics

The purpose of this study was to (i) evaluate the test-retest repeatability and reproducibility of radiomic features in virtual monoenergetic images (VMI) from dual-energy CT (DECT) depending on VMI energy (40, 50, 75, 120, 190 keV), radiation dose (5 and 15 mGy), and DECT approach (dual-source and split-filter DECT) in a phantom (ex vivo), and (ii) to assess the impact of VMI energy and feature repeatability on machine-learning-based classification in vivo in 72 patients with 72 hypodense liver lesions. Feature repeatability and reproducibility were determined by concordance-correlation-coefficient (CCC) and dynamic range (DR) ≥0.9. Test-retest repeatability was high within the same VMI energies and scan conditions (percentage of repeatable features ranging from 74% for SFDE mode at 40 keV and 15 mGy to 86% for DSDE at 190 keV and 15 mGy), while reproducibility varied substantially across different VMI energies and DECTs (percentage of reproducible features ranging from 32.8% for SFDE at 5 mGy comparing 40 with 190 keV to 99.2% for DSDE at 15 mGy comparing 40 with 50 keV). No major differences were observed between the two radiation doses (<10%) in all pair-wise comparisons. In vivo, machine learning classification using penalized regression and random forests resulted in the best discrimination of hemangiomas and metastases at low-energy VMI (40 keV), and for cysts at high-energy VMI (120 keV). Feature selection based on feature repeatability did not improve classification performance. Our results demonstrate the high repeatability of radiomics features when keeping scan and reconstruction conditions constant. Reproducibility diminished when using different VMI energies or DECT approaches. The choice of optimal VMI energy improved lesion classification in vivo and should hence be adapted to the specific task

Virtual Monoenergetic Images of Dual-Energy CT-Impact on Repeatability, Reproducibility, and Classification in Radiomics

Simple Summary Virtual monoenergetic images from dual-energy CT are incrementally used in routine clinical practice. Thus, radiomic analysis will be more often performed on these images in the future. This study characterized the test-retest repeatability and reproducibility of radiomic features from virtual monoenergetic images and their impact on machine-learning-based lesion classification. The results of this study provide a basis to improve radiomic analyses and identify the role of feature stability in classification tasks when using virtual monoenergetic imaging with different scan or reconstruction parameters in multicenter clinical studies. The purpose of this study was to (i) evaluate the test-retest repeatability and reproducibility of radiomic features in virtual monoenergetic images (VMI) from dual-energy CT (DECT) depending on VMI energy (40, 50, 75, 120, 190 keV), radiation dose (5 and 15 mGy), and DECT approach (dual-source and split-filter DECT) in a phantom (ex vivo), and (ii) to assess the impact of VMI energy and feature repeatability on machine-learning-based classification in vivo in 72 patients with 72 hypodense liver lesions. Feature repeatability and reproducibility were determined by concordance-correlation-coefficient (CCC) and dynamic range (DR) >= 0.9. Test-retest repeatability was high within the same VMI energies and scan conditions (percentage of repeatable features ranging from 74% for SFDE mode at 40 keV and 15 mGy to 86% for DSDE at 190 keV and 15 mGy), while reproducibility varied substantially across different VMI energies and DECTs (percentage of reproducible features ranging from 32.8% for SFDE at 5 mGy comparing 40 with 190 keV to 99.2% for DSDE at 15 mGy comparing 40 with 50 keV). No major differences were observed between the two radiation doses (<10%) in all pair-wise comparisons. In vivo, machine learning classification using penalized regression and random forests resulted in the best discrimination of hemangiomas and metastases at low-energy VMI (40 keV), and for cysts at high-energy VMI (120 keV). Feature selection based on feature repeatability did not improve classification performance. Our results demonstrate the high repeatability of radiomics features when keeping scan and reconstruction conditions constant. Reproducibility diminished when using different VMI energies or DECT approaches. The choice of optimal VMI energy improved lesion classification in vivo and should hence be adapted to the specific task

Altered brain responses to emotional facial expressions in tinnitus patients

Tinnitus, the phantom perception of sound, is a frequent disorder that can lead to severe distress and stress-related comorbidity. The pathophysiological mechanisms involved in the etiology of tinnitus are still under exploration. Electrophysiological and functional neuroimaging studies provide increasing evidence for abnormal functioning in auditory but also in non-auditory, e.g., emotional, brain areas. In order to elucidate alterations of affective processing in patients with chronic tinnitus, we used functional magnetic resonance imaging (fMRI) to measure neural responses to emotionally expressive and neutral faces. Twelve patients with chronic tinnitus and a group of 11 healthy controls, matched for age, sex, hearing loss and depressive symptoms were investigated. While viewing emotionally expressive faces compared to neutral faces brain activations in the tinnitus patients differed from those of the controls in a cluster that encompasses the amygdala, the hippocampus and the parahippocampal gyrus bilaterally. Whereas in controls affective faces induced higher brain activation in these regions than neutral faces, these regions in tinnitus patients were deactivated. Our results (1) provide evidence for alterations of affective processing of facial expressions in tinnitus patients indicating general domain-unspecific dysfunctions in emotion processing and (2) indicate the involvement of medial temporal areas in the pathophysiology of tinnitus