Wolfgang Freysinger
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Wolfgang Freysinger has a total of 196 co-authors. Here are the top co-authors by number of shared publications:
- Reto Bale
Interventional Oncology-Stereotaxy and Robotics (SIP), Radiology Department, Medical University Innsbruck, Innsbruck, Austria
12 shared publications A. R. Gunkel
Innsbruck Medical Univ. (Austria)
10 shared publicationsW. F. Thumfart
D-Visualisierung, Klinische Abteilung für allgemeine Hals-, Nasen-und Ohrenerkrankungen, Klinik für Hals-, Nasen- und Ohrenheilkunde, Universität Innsbruck
9 shared publicationsAndreas R. Gunkel
Univ. of Innsbruck (Austria)
8 shared publicationsF. Kral
D Visualization Laboratory, University ENT Clinic, Innsbruck Medical University, Anichstr. 35, 6020 Innsbruck, Austria
8 shared publications- Michael Truppe
D Implantat Navigation, Vienna 1080, Austria
8 shared publications
Latest Publications
- Open Access
Image-Level Data Augmentation for Radiomics-Based Classification of Vital Versus Non-Vital Persistent Cervical Lymph Nodes After Chemoradiotherapy in HNSCC
Background: Distinguishing vital from non-vital persistent cervical lymph nodes after chemoradiotherapy in HNSCC remains clinically challenging. We investigated whether image-level data augmentation improves CT-based radiomics classification for this task. Methods: We evaluated eight augmentation strategies and their 28 pairwise combinations in 55 patients, using Bayesian hyperparameter tuning with Optuna for parameter optimization. A radiomics pipeline comprising Radiomics features, five feature selectors, and seven classifiers was assessed using patient-level stratified 5-fold cross-validation. Configurations were ranked using a composite score defined as the mean of AUC, ACC and F1-score. Results: Feature selection improved the composite score from 0.659 to 0.742. The best augmented configuration, Window Contrast Variation, achieved a composite score of 0.803 and an AUC of 0.831, corresponding to an 8.2% relative point-estimate gain over feature selection alone and a 21.9% gain over the no-selection baseline when feature selection and augmentation were combined. Conclusions: These findings suggest that feature selection with optimized augmentation may enhance radiomics-based lymph node classification. However, individual augmentation-versus-baseline differences did not reach statistical significance in this limited sample, requiring confirmation in larger cohorts.
Open AccessImage-Level Data Augmentation for Radiomics-Based Classification of Vital Versus Non-Vital Persistent Cervical Lymph Nodes After Chemoradiotherapy in HNSCC
Background: Distinguishing vital from non-vital persistent cervical lymph nodes after chemoradiotherapy in HNSCC remains clinically challenging. We investigated whether image-level data augmentation improves CT-based radiomics classification for this task. Methods: We evaluated eight augmentation strategies and their 28 pairwise combinations in 55 patients, using Bayesian hyperparameter tuning with Optuna for parameter optimization. A radiomics pipeline comprising Radiomics features, five feature selectors, and seven classifiers was assessed using patient-level stratified 5-fold cross-validation. Configurations were ranked using a composite score defined as the mean of AUC, ACC and F1-score. Results: Feature selection improved the composite score from 0.659 to 0.742. The best augmented configuration, Window Contrast Variation, achieved a composite score of 0.803 and an AUC of 0.831, corresponding to an 8.2% relative point-estimate gain over feature selection alone and a 21.9% gain over the no-selection baseline when feature selection and augmentation were combined. Conclusions: These findings suggest that feature selection with optimized augmentation may enhance radiomics-based lymph node classification. However, individual augmentation-versus-baseline differences did not reach statistical significance in this limited sample, requiring confirmation in larger cohorts.
- Open Access
- 28 September 2025
- Published by Springer Nature
- Vol. 15 (4) , 65-74
Ablate Them All: A Trajectory Planning for Concurrent Percutaneous Ablation of Multiple Tumors
Radiofrequency ablation is a minimally invasive technique widely used for treating liver tumors, yet planning optimal probe trajectories for multiple tumors remains a significant challenge due to the complexity of avoiding critical structures and ensuring adequate tumor coverage. However, it is crucial to treat as many tumors as possible in one intervention to decrease patients’ hospitalization time. Furthermore, utilizing a single probe for ablating multiple tumors on the same trajectory reduces the number of probes used, and consequently, the risk of complications, such as crossing critical structures or trajectory collisions. In this scenario, probes are advanced to the most distant tumor, and subsequent to conducting ablation, the probes are retracted to the proximal tumor for an additional ablation. We propose a novel trajectory planning algorithm for ablation procedures, introducing an innovative multi-tumor planning strategy and force field-based navigation. Our genetic optimization algorithm is guided by a field derived from abdominal structures to enable efficient and safe navigation through complex anatomy. A retrospective analysis, performed on 18 patients from our in-house dataset, with 1 to 4 tumors each, shows its usability in clinical scenarios. Our algorithm produces safe, non-colliding, and clinically compliant solutions for all cases in 5.7 min on average and achieves a mean coverage of $$93.5\%$$ of tumors with 5 mm safety margin. Comparison on single-tumor cases with existing automated methods demonstrates the competitiveness of our algorithm. Furthermore, the method’s ability to handle complex multi-tumor scenarios is a significant step toward clinical implementation.- 28 September 2025
- Published by Springer Nature
- Vol. 15 (4) , 65-74
Open AccessAblate Them All: A Trajectory Planning for Concurrent Percutaneous Ablation of Multiple Tumors
Radiofrequency ablation is a minimally invasive technique widely used for treating liver tumors, yet planning optimal probe trajectories for multiple tumors remains a significant challenge due to the complexity of avoiding critical structures and ensuring adequate tumor coverage. However, it is crucial to treat as many tumors as possible in one intervention to decrease patients’ hospitalization time. Furthermore, utilizing a single probe for ablating multiple tumors on the same trajectory reduces the number of probes used, and consequently, the risk of complications, such as crossing critical structures or trajectory collisions. In this scenario, probes are advanced to the most distant tumor, and subsequent to conducting ablation, the probes are retracted to the proximal tumor for an additional ablation. We propose a novel trajectory planning algorithm for ablation procedures, introducing an innovative multi-tumor planning strategy and force field-based navigation. Our genetic optimization algorithm is guided by a field derived from abdominal structures to enable efficient and safe navigation through complex anatomy. A retrospective analysis, performed on 18 patients from our in-house dataset, with 1 to 4 tumors each, shows its usability in clinical scenarios. Our algorithm produces safe, non-colliding, and clinically compliant solutions for all cases in 5.7 min on average and achieves a mean coverage of $$93.5\%$$ of tumors with 5 mm safety margin. Comparison on single-tumor cases with existing automated methods demonstrates the competitiveness of our algorithm. Furthermore, the method’s ability to handle complex multi-tumor scenarios is a significant step toward clinical implementation. - Open Access
Machine Learning-Based Classification of Cervical Lymph Nodes in HNSCC: A Radiomics Approach with Feature Selection Optimization
Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) diagnosis and treatment rely heavily on computed tomography (CT) imaging to evaluate tumor characteristics and lymph node (LN) involvement, crucial for staging, prognosis, and therapy planning. Conventional LN evaluation methods based on morphological criteria such as size, shape, and anatomical location often lack sensitivity for early metastasis detection. This study leverages radiomics to extract quantitative features from CT images, addressing the limitations of subjective assessment and aiming to enhance LN classification accuracy while potentially reducing reliance on invasive histopathology. Methods: We analyzed 234 LNs from 27 HNSCC patients, deriving 120 features per node, resulting in over 25,000 data points classified into reactive, pathologic, and pathologic with extracapsular spread classes. Considering the challenges of high dimensionality and limited dataset size, more than 44,000 experiments systematically optimized machine learning models, feature selection methods, and hyperparameters, including ensemble approaches to strengthen classification robustness. A Pareto front strategy was employed to balance diagnostic accuracy with significant feature reduction. Results: The optimal model, validated via 5-fold cross-validation, achieved a balanced accuracy of 0.90, an area under the curve (AUC) of 0.93, and an F1-score of 0.88 using only five radiomics features. Conclusions: This interpretable approach aligns well with clinical radiology practice, demonstrating strong potential for clinical application in noninvasive LN classification in HNSCC.
Open AccessMachine Learning-Based Classification of Cervical Lymph Nodes in HNSCC: A Radiomics Approach with Feature Selection Optimization
Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) diagnosis and treatment rely heavily on computed tomography (CT) imaging to evaluate tumor characteristics and lymph node (LN) involvement, crucial for staging, prognosis, and therapy planning. Conventional LN evaluation methods based on morphological criteria such as size, shape, and anatomical location often lack sensitivity for early metastasis detection. This study leverages radiomics to extract quantitative features from CT images, addressing the limitations of subjective assessment and aiming to enhance LN classification accuracy while potentially reducing reliance on invasive histopathology. Methods: We analyzed 234 LNs from 27 HNSCC patients, deriving 120 features per node, resulting in over 25,000 data points classified into reactive, pathologic, and pathologic with extracapsular spread classes. Considering the challenges of high dimensionality and limited dataset size, more than 44,000 experiments systematically optimized machine learning models, feature selection methods, and hyperparameters, including ensemble approaches to strengthen classification robustness. A Pareto front strategy was employed to balance diagnostic accuracy with significant feature reduction. Results: The optimal model, validated via 5-fold cross-validation, achieved a balanced accuracy of 0.90, an area under the curve (AUC) of 0.93, and an F1-score of 0.88 using only five radiomics features. Conclusions: This interpretable approach aligns well with clinical radiology practice, demonstrating strong potential for clinical application in noninvasive LN classification in HNSCC.
- Open Access
- 11 May 2025
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 20 (7) , 1349-1360
Automatic trajectory planning for stereotactic radiofrequency ablation in non-discrete search space
Purpose: Radiofrequency ablation is a well established minimally invasive procedure to treat tumors in solid organs. During the procedure applicators are inserted into the tumor and cells around their tips are destroyed by heat-induced denaturation. Manual trajectory planning requires a trained interventionalist, and its complexity and planning time rise significantly with an increasing number of trajectories. Methods: We propose a trajectory planning method using a genetic algorithm to accelerate the planning process by automatically generating multiple safe plans. Our method uses a non-discrete search space to find the best entry and target points and does not need any prior calculation of such candidate’s points sets. The method offers multiple plans, allowing the interventionalists to choose the most appropriate one. We tested on an open-source and in-house dataset, comparing with related work and retrospectively with the in-house clinical planning. Results: Our method, tested on 154 liver tumors across all segments using a 10 mm ablation radius, achieves a mean coverage of over 99% of the tumors including a 5 mm safety margin. The method provides safe trajectories for all solutions and is on average 4 $$\times $$ faster than related approaches. Conclusion: To the best of our knowledge, we are the first to propose a fast and accurate planning technique using multiple applicators with 10 mm ablation radius. Our algorithm can deliver solutions optimizing more than ten trajectories, approaching the clinical practice at our institution, where large tumors are treated with multiple overlapping ablation zones rather than resection.- 11 May 2025
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 20 (7) , 1349-1360
Open AccessAutomatic trajectory planning for stereotactic radiofrequency ablation in non-discrete search space
Purpose: Radiofrequency ablation is a well established minimally invasive procedure to treat tumors in solid organs. During the procedure applicators are inserted into the tumor and cells around their tips are destroyed by heat-induced denaturation. Manual trajectory planning requires a trained interventionalist, and its complexity and planning time rise significantly with an increasing number of trajectories. Methods: We propose a trajectory planning method using a genetic algorithm to accelerate the planning process by automatically generating multiple safe plans. Our method uses a non-discrete search space to find the best entry and target points and does not need any prior calculation of such candidate’s points sets. The method offers multiple plans, allowing the interventionalists to choose the most appropriate one. We tested on an open-source and in-house dataset, comparing with related work and retrospectively with the in-house clinical planning. Results: Our method, tested on 154 liver tumors across all segments using a 10 mm ablation radius, achieves a mean coverage of over 99% of the tumors including a 5 mm safety margin. The method provides safe trajectories for all solutions and is on average 4 $$\times $$ faster than related approaches. Conclusion: To the best of our knowledge, we are the first to propose a fast and accurate planning technique using multiple applicators with 10 mm ablation radius. Our algorithm can deliver solutions optimizing more than ten trajectories, approaching the clinical practice at our institution, where large tumors are treated with multiple overlapping ablation zones rather than resection. - Open Access
- 9 October 2024
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 19 (12) , 2311-2319
Adaptive infrared patterns for microscopic surface reconstructions
Purpose: Multi-zoom microscopic surface reconstructions of operating sites, especially in ENT surgeries, would allow multimodal image fusion for determining the amount of resected tissue, for recognizing critical structures, and novel tools for intraoperative quality assurance. State-of-the-art three-dimensional model creation of the surgical scene is challenged by the surgical environment, illumination, and the homogeneous structures of skin, muscle, bones, etc., that lack invariant features for stereo reconstruction. Methods: An adaptive near-infrared pattern projector illuminates the surgical scene with optimized patterns to yield accurate dense multi-zoom stereoscopic surface reconstructions. The approach does not impact the clinical workflow. The new method is compared to state-of-the-art approaches and is validated by determining its reconstruction errors relative to a high-resolution 3D-reconstruction of CT data. Results: 200 surface reconstructions were generated for 5 zoom levels with 10 reconstructions for each object illumination method (standard operating room light, microscope light, random pattern and adaptive NIR pattern). For the adaptive pattern, the surface reconstruction errors ranged from 0.5 to 0.7 mm, as compared to 1–1.9 mm for the other approaches. The local reconstruction differences are visualized in heat maps. Conclusion: Adaptive near-infrared (NIR) pattern projection in microscopic surgery allows dense and accurate microscopic surface reconstructions for variable zoom levels of small and homogeneous surfaces. This could potentially aid in microscopic interventions at the lateral skull base and potentially open up new possibilities for combining quantitative intraoperative surface reconstructions with preoperative radiologic imagery.
- 9 October 2024
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 19 (12) , 2311-2319
Open AccessAdaptive infrared patterns for microscopic surface reconstructions
Purpose: Multi-zoom microscopic surface reconstructions of operating sites, especially in ENT surgeries, would allow multimodal image fusion for determining the amount of resected tissue, for recognizing critical structures, and novel tools for intraoperative quality assurance. State-of-the-art three-dimensional model creation of the surgical scene is challenged by the surgical environment, illumination, and the homogeneous structures of skin, muscle, bones, etc., that lack invariant features for stereo reconstruction. Methods: An adaptive near-infrared pattern projector illuminates the surgical scene with optimized patterns to yield accurate dense multi-zoom stereoscopic surface reconstructions. The approach does not impact the clinical workflow. The new method is compared to state-of-the-art approaches and is validated by determining its reconstruction errors relative to a high-resolution 3D-reconstruction of CT data. Results: 200 surface reconstructions were generated for 5 zoom levels with 10 reconstructions for each object illumination method (standard operating room light, microscope light, random pattern and adaptive NIR pattern). For the adaptive pattern, the surface reconstruction errors ranged from 0.5 to 0.7 mm, as compared to 1–1.9 mm for the other approaches. The local reconstruction differences are visualized in heat maps. Conclusion: Adaptive near-infrared (NIR) pattern projection in microscopic surgery allows dense and accurate microscopic surface reconstructions for variable zoom levels of small and homogeneous surfaces. This could potentially aid in microscopic interventions at the lateral skull base and potentially open up new possibilities for combining quantitative intraoperative surface reconstructions with preoperative radiologic imagery.
- Open Access
- 23 August 2024
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 20 (10) , 1
Correction to: Noctopus: a novel device and method for patient registration and navigation in image-guided cranial surgery
- 23 August 2024
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 20 (10) , 1
Open AccessCorrection to: Noctopus: a novel device and method for patient registration and navigation in image-guided cranial surgery
- Open Access
- 30 July 2024
- Published by Springer Nature in European Archives of Oto-Rhino-Laryngology
- Vol. 281 (11) , 5971-5982
The Neck-Persistency-Net: a three-dimensional, convolution, deep neural network aids in distinguishing vital from non-vital persistent cervical lymph nodes in advanced head and neck squamous cell carcinoma after primary concurrent radiochemotherapy
Purpose: To evaluate the diagnostic performance (DP) of the high-resolution contrast computed tomography (HR-contrast-CT) based Neck-Persistency-Net in distinguishing vital from non-vital persistent cervical lymph nodes (pcLNs) in patients with advanced head and neck squamous cell carcinoma (HNSCC) following primary concurrent chemoradiotherapy (CRT) with [18F]-fluorodeoxyglucose positron emission tomography and high-resolution contrast-enhanced computed tomography ([18F]FDG-PET-CT). Furthermore, the Neck-Persistency-Net’s potential to justify omitting post-CRT neck dissection (ND) without risking treatment delays or preventing unnecessary surgery was explored. Methods: All HNSCC patients undergoing primary CRT followed by post-CRT-ND for pcLNs recorded in the institutional HNSCC registry were analyzed. The Neck-Persistency-Net DP was explored for three scenarios: balanced performance (BalPerf), optimized sensitivity (OptSens), and optimized specificity (OptSpec). Histopathology of post-CRT-ND served as a reference. Results: Among 68 included patients, 11 were female and 32 had vital pcLNs. The Neck-Persistency-Net demonstrated good DP with an area under the curve of 0.82. For BalPerf, both sensitivity and specificity were 78%; for OptSens (90%), specificity was 62%; for OptSpec (95%), sensitivity was 54%. Limiting post-CRT-ND to negative results would have delayed treatment in 27%, 40%, and 7% for BalPerf, OptSens and OptSpec, respectively, versus 23% for [18F]FDG-PET-CT. Conversely, restricting post-CRT-ND to positive results would have prevented unnecessary post-CRT-ND in 78%, 60%, and 95% for BalPerf, OptSens and OptSpec, respectively, versus 55% for [18F]FDG-PET-CT. Conclusion: The DP of the Neck-Persistency-Net was comparable to [18F]-FDG-PET-CT. Depending on the chosen decision boundary, the potential to justify the omission of post-CRT-ND without risking treatment delays in false negative findings or reliably prevent unnecessary surgery in false positive findings outperforms the [18F]-FDG-PET-CT.
- 30 July 2024
- Published by Springer Nature in European Archives of Oto-Rhino-Laryngology
- Vol. 281 (11) , 5971-5982
Open AccessThe Neck-Persistency-Net: a three-dimensional, convolution, deep neural network aids in distinguishing vital from non-vital persistent cervical lymph nodes in advanced head and neck squamous cell carcinoma after primary concurrent radiochemotherapy
Purpose: To evaluate the diagnostic performance (DP) of the high-resolution contrast computed tomography (HR-contrast-CT) based Neck-Persistency-Net in distinguishing vital from non-vital persistent cervical lymph nodes (pcLNs) in patients with advanced head and neck squamous cell carcinoma (HNSCC) following primary concurrent chemoradiotherapy (CRT) with [18F]-fluorodeoxyglucose positron emission tomography and high-resolution contrast-enhanced computed tomography ([18F]FDG-PET-CT). Furthermore, the Neck-Persistency-Net’s potential to justify omitting post-CRT neck dissection (ND) without risking treatment delays or preventing unnecessary surgery was explored. Methods: All HNSCC patients undergoing primary CRT followed by post-CRT-ND for pcLNs recorded in the institutional HNSCC registry were analyzed. The Neck-Persistency-Net DP was explored for three scenarios: balanced performance (BalPerf), optimized sensitivity (OptSens), and optimized specificity (OptSpec). Histopathology of post-CRT-ND served as a reference. Results: Among 68 included patients, 11 were female and 32 had vital pcLNs. The Neck-Persistency-Net demonstrated good DP with an area under the curve of 0.82. For BalPerf, both sensitivity and specificity were 78%; for OptSens (90%), specificity was 62%; for OptSpec (95%), sensitivity was 54%. Limiting post-CRT-ND to negative results would have delayed treatment in 27%, 40%, and 7% for BalPerf, OptSens and OptSpec, respectively, versus 23% for [18F]FDG-PET-CT. Conversely, restricting post-CRT-ND to positive results would have prevented unnecessary post-CRT-ND in 78%, 60%, and 95% for BalPerf, OptSens and OptSpec, respectively, versus 55% for [18F]FDG-PET-CT. Conclusion: The DP of the Neck-Persistency-Net was comparable to [18F]-FDG-PET-CT. Depending on the chosen decision boundary, the potential to justify the omission of post-CRT-ND without risking treatment delays in false negative findings or reliably prevent unnecessary surgery in false positive findings outperforms the [18F]-FDG-PET-CT.
- Open Access
- 15 May 2024
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 19 (12) , 2371-2380
Noctopus: a novel device and method for patient registration and navigation in image-guided cranial surgery
Purpose: A patient registration and real-time surgical navigation system and a novel device and method (Noctopus) is presented. With any tracking system technology and a patient/target-specific registration marker configuration, submillimetric target registration error (TRE), high-precise application accuracy for single or multiple anatomical targets in image-guided neurosurgery or ENT surgery is realized. Methods: The system utilizes the advantages of marker-based registration technique and allows to perform automatized patient registration using on the device attached and with patient scanned four fiducial markers. The best possible sensor/marker positions around the patient’s head are determined for single or multiple region(s) of interest (target/s) in the anatomy. Once brought at the predetermined positions the device can be operated with any tracking system for registration purposes. Results: Targeting accuracy was evaluated quantitatively at various target positions on a phantom skull. The target registration error (TRE) was measured on individual targets using an electromagnetic tracking system. The overall averaged TRE was 0.22 ± 0.08 mm for intraoperative measurements. Conclusion: An automatized patient registration system using optimized patient-/target-specific marker configurations is proposed. High-precision and user-error-free intraoperative surgical navigation with minimum number of registration markers and sensors is realized. The targeting accuracy is significantly improved in minimally invasive neurosurgical and ENT interventions.
- 15 May 2024
- Published by Springer Nature in International Journal of Computer Assisted Radiology and Surgery
- Vol. 19 (12) , 2371-2380
Open AccessNoctopus: a novel device and method for patient registration and navigation in image-guided cranial surgery
Purpose: A patient registration and real-time surgical navigation system and a novel device and method (Noctopus) is presented. With any tracking system technology and a patient/target-specific registration marker configuration, submillimetric target registration error (TRE), high-precise application accuracy for single or multiple anatomical targets in image-guided neurosurgery or ENT surgery is realized. Methods: The system utilizes the advantages of marker-based registration technique and allows to perform automatized patient registration using on the device attached and with patient scanned four fiducial markers. The best possible sensor/marker positions around the patient’s head are determined for single or multiple region(s) of interest (target/s) in the anatomy. Once brought at the predetermined positions the device can be operated with any tracking system for registration purposes. Results: Targeting accuracy was evaluated quantitatively at various target positions on a phantom skull. The target registration error (TRE) was measured on individual targets using an electromagnetic tracking system. The overall averaged TRE was 0.22 ± 0.08 mm for intraoperative measurements. Conclusion: An automatized patient registration system using optimized patient-/target-specific marker configurations is proposed. High-precision and user-error-free intraoperative surgical navigation with minimum number of registration markers and sensors is realized. The targeting accuracy is significantly improved in minimally invasive neurosurgical and ENT interventions.
- Open Access
Radiomic Assessment of Radiation-Induced Alterations of Skeletal Muscle Composition in Head and Neck Squamous Cell Carcinoma within the Currently Clinically Defined Optimal Time Window for Salvage Surgery—A Pilot Study
Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity modulation, the desired radiation-induced effects observed in HNSCC may also be observed as side effects in healthy tissue, e.g., the sternocleidomastoid muscle (SCM). These side effects (e.g., tissue fibrosis) depend on the interval between the completion of RCT and restaging CT. For salvage surgery, the optimal time window for surgery is currently clinically postulated at between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on clinical studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC patients are sparse. The present study quantified tissue alterations in the SCM and paravertebral musculature (PVM) after RCT, applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters, (1) volume, (2) mean positivity of pixels (MPP), and (3) uniformity, were extracted with mint LesionTM in the staging CTs and restaging CTs of 98 HNSCC patients. Of these, 25 were female, the mean age was 62 (±9.6) years, and 80.9% were UICC Stage IV. The mean restaging interval was 55 (±28; range 29–229) days. Only the mean volume significantly decreased after RCT, from 9.0 to 8.4 and 96.5 to 91.9 mL for the SCM and PVM, respectively (both p = 0.007, both Cohen’s d = 0.28). In addition, the mean body mass index (BMI) decreased from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p < 0.001; Cohen’s d = 0.9). The mean BMI decreased significantly and was correlated with the volume decrease for the SCM (r = 0.27; p = 0.007) and PVM (r = 0.41; p < 0.001). If t-test p-values were adjusted for the BMI decrease, no significant change in volumes for the SCM and PVM was observed (both p > 0.05). The present data support the clinically postulated optimal interval for salvage surgery of 6 to 12 weeks.
Open AccessRadiomic Assessment of Radiation-Induced Alterations of Skeletal Muscle Composition in Head and Neck Squamous Cell Carcinoma within the Currently Clinically Defined Optimal Time Window for Salvage Surgery—A Pilot Study
Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity modulation, the desired radiation-induced effects observed in HNSCC may also be observed as side effects in healthy tissue, e.g., the sternocleidomastoid muscle (SCM). These side effects (e.g., tissue fibrosis) depend on the interval between the completion of RCT and restaging CT. For salvage surgery, the optimal time window for surgery is currently clinically postulated at between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on clinical studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC patients are sparse. The present study quantified tissue alterations in the SCM and paravertebral musculature (PVM) after RCT, applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters, (1) volume, (2) mean positivity of pixels (MPP), and (3) uniformity, were extracted with mint LesionTM in the staging CTs and restaging CTs of 98 HNSCC patients. Of these, 25 were female, the mean age was 62 (±9.6) years, and 80.9% were UICC Stage IV. The mean restaging interval was 55 (±28; range 29–229) days. Only the mean volume significantly decreased after RCT, from 9.0 to 8.4 and 96.5 to 91.9 mL for the SCM and PVM, respectively (both p = 0.007, both Cohen’s d = 0.28). In addition, the mean body mass index (BMI) decreased from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p < 0.001; Cohen’s d = 0.9). The mean BMI decreased significantly and was correlated with the volume decrease for the SCM (r = 0.27; p = 0.007) and PVM (r = 0.41; p < 0.001). If t-test p-values were adjusted for the BMI decrease, no significant change in volumes for the SCM and PVM was observed (both p > 0.05). The present data support the clinically postulated optimal interval for salvage surgery of 6 to 12 weeks.
- Open Access
- 4 September 2023
- Published by MDPI AG in Preprints.org
Defining an Optimal Time Window for Salvage Surgery: Primary Radiochemotherapy Does Not Induce Radiomically Assessable Short-Term Alterations of Skeletal Muscle Composition in Head and Neck Squamous Cell Carcinoma
Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity-modulation, desired radiation-induced effects observed in HNSCC, may also be observed as side-effects in healthy tissue e.g. the sternocleidomastoideus muscle (SCM). These side-effects (e.g. tissue fibrosis) depend on the interval between completion of RCT and restaging-CT. For salvage surgery, the optimal time window for surgery is currently postulated between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC-patients are sparse. The present study quantifies tissue alterations in SCM and paravertebral musculature (PVM) after RCT applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters 1) volume, 2) mean positivity of pixels (MPP) and 3) uniformity were extracted with mint lesionTM in the staging-CTs and restaging-CTs of 98 HNSCC-patients. Of these, 25 were female, the mean age was 62 (±9.6) years and 80.9% were UICC Stage IV. The mean restaging-interval was 55 (±28; range29-229) days. Only the mean volume significantly decreased after RCT from 9.0 to 8.4 and 96.5 to 91.9 ml for SCM and PVM, respectively (both p=0.007, both Cohen’s d=0.28). In addition, the mean body mass index (BMI) decreases from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p<0.001); Cohen's d = 0.9). The mean BMI-decrease significantly correlated with the volume decrease for SCM (r=0.27; p=0.007) and PVM (r=0.41; p0.05). The present data supports the postulated optimal interval for salvage surgery of 6 to 12 weeks. Irrespective of the remaining risk-benefit ratio of salvage surgery, the risk of additional surgical complications due to fibrosis is not supported by the present observations.
- 4 September 2023
- Published by MDPI AG in Preprints.org
Open AccessDefining an Optimal Time Window for Salvage Surgery: Primary Radiochemotherapy Does Not Induce Radiomically Assessable Short-Term Alterations of Skeletal Muscle Composition in Head and Neck Squamous Cell Carcinoma
Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity-modulation, desired radiation-induced effects observed in HNSCC, may also be observed as side-effects in healthy tissue e.g. the sternocleidomastoideus muscle (SCM). These side-effects (e.g. tissue fibrosis) depend on the interval between completion of RCT and restaging-CT. For salvage surgery, the optimal time window for surgery is currently postulated between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC-patients are sparse. The present study quantifies tissue alterations in SCM and paravertebral musculature (PVM) after RCT applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters 1) volume, 2) mean positivity of pixels (MPP) and 3) uniformity were extracted with mint lesionTM in the staging-CTs and restaging-CTs of 98 HNSCC-patients. Of these, 25 were female, the mean age was 62 (±9.6) years and 80.9% were UICC Stage IV. The mean restaging-interval was 55 (±28; range29-229) days. Only the mean volume significantly decreased after RCT from 9.0 to 8.4 and 96.5 to 91.9 ml for SCM and PVM, respectively (both p=0.007, both Cohen’s d=0.28). In addition, the mean body mass index (BMI) decreases from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p<0.001); Cohen's d = 0.9). The mean BMI-decrease significantly correlated with the volume decrease for SCM (r=0.27; p=0.007) and PVM (r=0.41; p0.05). The present data supports the postulated optimal interval for salvage surgery of 6 to 12 weeks. Irrespective of the remaining risk-benefit ratio of salvage surgery, the risk of additional surgical complications due to fibrosis is not supported by the present observations.