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  • 1
    Online Resource
    Online Resource
    Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design
    MDPI AG ; 2023
    In:  Cancers Vol. 15, No. 18 ( 2023-09-18), p. 4620-
    Details
    In: Cancers, MDPI AG, Vol. 15, No. 18 ( 2023-09-18), p. 4620-
    Abstract: We introduce a deep-learning- and a registration-based method for automatically analyzing the spatial distribution of nodal metastases (LNs) in head and neck (H/N) cancer cohorts to inform radiotherapy (RT) target volume design. The two methods are evaluated in a cohort of 193 H/N patients/planning CTs with a total of 449 LNs. In the deep learning method, a previously developed nnU-Net 3D/2D ensemble model is used to autosegment 20 H/N levels, with each LN subsequently being algorithmically assigned to the closest-level autosegmentation. In the nonrigid-registration-based mapping method, LNs are mapped into a calculated template CT representing the cohort-average patient anatomy, and kernel density estimation is employed to estimate the underlying average 3D-LN probability distribution allowing for analysis and visualization without prespecified level definitions. Multireader assessment by three radio-oncologists with majority voting was used to evaluate the deep learning method and obtain the ground-truth distribution. For the mapping technique, the proportion of LNs predicted by the 3D probability distribution for each level was calculated and compared to the deep learning and ground-truth distributions. As determined by a multireader review with majority voting, the deep learning method correctly categorized all 449 LNs to their respective levels. Level 2 showed the highest LN involvement (59.0%). The level involvement predicted by the mapping technique was consistent with the ground-truth distribution (p for difference 0.915). Application of the proposed methods to multicenter cohorts with selected H/N tumor subtypes for informing optimal RT target volume design is promising.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers15184620
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2527080-1
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  • 2
    Online Resource
    Online Resource
    Reduction of Elective Radiotherapy Treatment Volume in Definitive Treatment of Locally Advanced Head and Neck Cancer—Comparison of a Prospective Trial with a Revised Simulated Contouring Approach
    MDPI AG ; 2021
    In:  Journal of Clinical Medicine Vol. 10, No. 20 ( 2021-10-11), p. 4653-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 10, No. 20 ( 2021-10-11), p. 4653-
    Abstract: Definitive radiochemotherapy of locally advanced head and neck squamous cell cancer (HNSCC) achieves high locoregional tumor control rates; but is frequently associated with long-term toxicity. A future direction could be a de-escalation strategy focusing on treated volume rather than radiotherapy dose. This analysis evaluates radiotherapy dose and volume parameters of patients treated with a standard contouring approach in a clinical trial context compared with a revised volume-reduced contouring approach. In this case, 30 consecutive patients from the CheckRad-CD8 trial treated at a single study center were included in this analysis. Treatment toxicity and quality of life were assessed at the end of radiotherapy. Standard treatment plans (ST) following state of the art contouring guidelines that were used for patient treatment and volume reduced treatment plans (VRT) according to a revised simulated approach were calculated for each patient. Planning target volumes (PTV) and mean doses to 38 organs-at-risk structures were compared. At the end of radiotherapy patients reported high rates of mucositis; dysphagia and xerostomia. In addition; patient reported quality of life as assessed by the EORTC QLQ-HN35 questionnaire deteriorated. Comparing the two contouring approaches; the elective PTV_56 Gy and the high risk PTV_63 Gy (shrinking field) were significantly smaller in the VRT group. Significant reduction of mean dose to structures of the oral cavity; the larynx as well as part of the swallowing muscles and the submandibular glands was achieved in the simulated VRT-plan. Treatment de-intensification by reduction of the irradiated volume could potentially reduce treatment volume and mean doses to organs at risk. The proposed contouring approach should be studied further in the context of a clinical trial.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm10204653
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662592-1
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  • 3
    Online Resource
    Online Resource
    Paragangliomas of the Head and Neck : Local Control and Functional Outcome Following Fractionated Stereotactic Radiotherapy
    Ovid Technologies (Wolters Kluwer Health) ; 2019
    In:  American Journal of Clinical Oncology Vol. 42, No. 11 ( 2019-11), p. 818-823
    Details
    In: American Journal of Clinical Oncology, Ovid Technologies (Wolters Kluwer Health), Vol. 42, No. 11 ( 2019-11), p. 818-823
    Abstract: To investigate local control and functional outcome following state-of-the-art fractionated stereotactic radiotherapy (FSRT) for paragangliomas of the head and neck. Methods: In total, 40 consecutive patients with paragangliomas of the head and neck received conventionally FSRT from 2003 to 2016 at the Department of Radiation Oncology of the University Hospital Erlangen. Local control, toxicities, and functional outcome were examined during follow-up. In total, 148 magnetic resonance imaging studies were subjected to longitudinal volumetric analysis using whole tumor segmentation in a subset of 22 patients. Results: A total of 80.0% (32/40) of patients received radiotherapy as part of their primary treatment. In 20.0% (8/40) of patients, radiation was used as salvage treatment after tumor recurrence in patients initially treated with surgery alone. The median dose applied was 54.0 Gy (interdecile range, 50.4 to 56.0 Gy) in single doses of 1.8 or 2 Gy. Local control was 100% after a median imaging follow-up of 52.2 months (range, 0.8 to 152.9 mo). The volumetric analysis confirmed sustained tumor control in a subset of 22 patients and showed transient enlargement (range, 129.6% to 151.2%) in 13.6% of cases (3/22). After a median volumetric follow-up of 24.6 months mean tumor volume had diminished to 86.1% compared with initial volume. In total, 52.5% (21/40) of patients reported improved symptoms after radiotherapy, 40% (16/40) observed no subjective change with only 7.5% (3/40) reporting significant worsening. Conclusions: State-of-the-art FSRT provides excellent control and favorable functional outcome in patients with paragangliomas of the head and neck. The volumetric analysis provides improved evidence for sustained tumor control.
    Type of Medium: Online Resource
    ISSN: 0277-3732
    URL: Article
    DOI: 10.1097/COC.0000000000000614
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2019
    detail.hit.zdb_id: 2043067-X
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  • 4
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    Online Resource
    Transient Enlargement in Meningiomas Treated with Stereotactic Radiotherapy
    MDPI AG ; 2022
    In:  Cancers Vol. 14, No. 6 ( 2022-03-17), p. 1547-
    Details
    In: Cancers, MDPI AG, Vol. 14, No. 6 ( 2022-03-17), p. 1547-
    Abstract: To investigate the occurrence of pseudoprogression/transient enlargement in meningiomas after stereotactic radiotherapy (RT) and to evaluate recently proposed volumetric RANO meningioma criteria for response assessment in the context of RT. Sixty-nine meningiomas (benign: 90%, atypical: 10%) received stereotactic RT from January 2005–May 2018. A total of 468 MRI studies were segmented longitudinally during a median follow-up of 42.3 months. Best response and local control were evaluated according to recently proposed volumetric RANO criteria. Transient enlargement was defined as volumetric increase ≥20% followed by a subsequent regression ≥20%. The mean best volumetric response was −23% change from baseline (range, −86% to +19%). According to RANO, the best volumetric response was SD in 81% (56/69), MR in 13% (9/69) and PR in 6% (4/69). Transient enlargement occurred in only 6% (4/69) post RT but would have represented 60% (3/5) of cases with progressive disease if not accounted for. Transient enlargement was characterized by a mean maximum volumetric increase of +181% (range, +24% to +389 %) with all cases occurring in the first year post-RT (range, 4.1–10.3 months). Transient enlargement was significantly more frequent with SRS or hypofractionation than with conventional fractionation (25% vs. 2%, p = 0.015). Five-year volumetric control was 97.8% if transient enlargement was recognized but 92.9% if not accounted for. Transient enlargement/pseudoprogression in the first year following SRS and hypofractionated RT represents an important differential diagnosis, especially because of the high volumetric control achieved with stereotactic RT. Meningioma enlargement during subsequent post-RT follow-up and after conventional fractionation should raise suspicion for tumor progression.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers14061547
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 5
    Online Resource
    Online Resource
    Magnetresonanztomographie für die stereotaktische Strahlentherapie des Gehirns : Anforderungen und Fehlerquellen – eine Übersicht
    Springer Science and Business Media LLC ; 2020
    In:  Strahlentherapie und Onkologie Vol. 196, No. 5 ( 2020-05), p. 444-456
    Details
    In: Strahlentherapie und Onkologie, Springer Science and Business Media LLC, Vol. 196, No. 5 ( 2020-05), p. 444-456
    Abstract: Due to its superior soft tissue contrast, magnetic resonance imaging (MRI) is essential for many radiotherapy treatment indications. This is especially true for treatment planning in intracranial tumors, where MRI has a long-standing history for target delineation in clinical practice. Despite its routine use, care has to be taken when selecting and acquiring MRI studies for the purpose of radiotherapy treatment planning. Requirements on MRI are particularly demanding for intracranial stereotactic radiotherapy, where accurate imaging has a critical role in treatment success. However, MR images acquired for routine radiological assessment are frequently unsuitable for high-precision stereotactic radiotherapy as the requirements for imaging are significantly different for radiotherapy planning and diagnostic radiology. To assure that optimal imaging is used for treatment planning, the radiation oncologist needs proper knowledge of the most important requirements concerning the use of MRI in brain stereotactic radiotherapy. In the present review, we summarize and discuss the most relevant issues when using MR images for target volume delineation in intracranial stereotactic radiotherapy.
    Type of Medium: Online Resource
    ISSN: 0179-7158 , 1439-099X
    URL: Article
    DOI: 10.1007/s00066-020-01604-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2003907-4
    detail.hit.zdb_id: 84983-2
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  • 6
    Online Resource
    Online Resource
    Oligometastatic head and neck cancer: Which patients benefit from radical local treatment of all tumour sites?
    Springer Science and Business Media LLC ; 2021
    In:  Radiation Oncology Vol. 16, No. 1 ( 2021-12)
    Details
    In: Radiation Oncology, Springer Science and Business Media LLC, Vol. 16, No. 1 ( 2021-12)
    Abstract: There is a large lack of evidence for optimal treatment in oligometastatic head and neck cancer and it is especially unclear which patients benefit from radical local treatment of all tumour sites. Methods 40 patients with newly diagnosed oligometastatic head and neck cancer received radical local treatment of all tumour sites from 14.02.2008 to 24.08.2018. Primary endpoint was overall survival. Time to occurrence of new distant metastases and local control were evaluated as secondary endpoints as well as prognostic factors in univariate und multivariate Cox’s regression analysis. To investigate the impact of total tumour volume on survival, all tumour sites were segmented on baseline imaging. Results Radical local treatment included radiotherapy in 90% of patients, surgery in 25% and radiofrequency ablation in 3%. Median overall survival from first diagnosis of oligometastatic disease was 23.0 months, 2-year survival was 48%, 3-year survival was 37%, 4-year survival was 24% and 5-year survival was 16%. Median time to occurrence of new distant metastases was 11.6 months with freedom from new metastases showing a tail pattern after 3 years of follow-up (22% at 3, 4- and 5-years post-treatment). In multivariate analysis, better ECOG status, absence of bone and brain metastases and lower total tumour volume were significantly associated with improved survival, whereas the number of metastases and involved organ sites was not. Conclusions Radical local treatment in oligometastatic head and neck cancer shows promising outcomes and needs to be further pursued. Patients with good performance status, absence of brain and bone metastases and low total tumour volume were identified as optimal candidates for radical local treatment in oligometastatic head and neck cancer and should be considered for selection in future prospective trials.
    Type of Medium: Online Resource
    ISSN: 1748-717X
    URL: Article
    DOI: 10.1186/s13014-021-01790-w
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2224965-5
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  • 7
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    Online Resource
    FSRT vs. SRS in Brain Metastases—Differences in Local Control and Radiation Necrosis—A Volumetric Study
    Frontiers Media SA ; 2020
    In:  Frontiers in Oncology Vol. 10 ( 2020-9-30)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 10 ( 2020-9-30)
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    DOI: 10.3389/fonc.2020.559193
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
    detail.hit.zdb_id: 2649216-7
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  • 8
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    DataSheet_2.zip
    Frontiers Media SA ; 2023
    In:  Frontiers in Oncology Vol. 13 ( 2023-9-14)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 13 ( 2023-9-14)
    Abstract: The potential of large language models in medicine for education and decision-making purposes has been demonstrated as they have achieved decent scores on medical exams such as the United States Medical Licensing Exam (USMLE) and the MedQA exam. This work aims to evaluate the performance of ChatGPT-4 in the specialized field of radiation oncology. Methods The 38th American College of Radiology (ACR) radiation oncology in-training (TXIT) exam and the 2022 Red Journal Gray Zone cases are used to benchmark the performance of ChatGPT-4. The TXIT exam contains 300 questions covering various topics of radiation oncology. The 2022 Gray Zone collection contains 15 complex clinical cases. Results For the TXIT exam, ChatGPT-3.5 and ChatGPT-4 have achieved the scores of 62.05% and 78.77%, respectively, highlighting the advantage of the latest ChatGPT-4 model. Based on the TXIT exam, ChatGPT-4’s strong and weak areas in radiation oncology are identified to some extent. Specifically, ChatGPT-4 demonstrates better knowledge of statistics, CNS & amp; eye, pediatrics, biology, and physics than knowledge of bone & amp; soft tissue and gynecology, as per the ACR knowledge domain. Regarding clinical care paths, ChatGPT-4 performs better in diagnosis, prognosis, and toxicity than brachytherapy and dosimetry. It lacks proficiency in in-depth details of clinical trials. For the Gray Zone cases, ChatGPT-4 is able to suggest a personalized treatment approach to each case with high correctness and comprehensiveness. Importantly, it provides novel treatment aspects for many cases, which are not suggested by any human experts. Conclusion Both evaluations demonstrate the potential of ChatGPT-4 in medical education for the general public and cancer patients, as well as the potential to aid clinical decision-making, while acknowledging its limitations in certain domains. Owing to the risk of hallucinations, it is essential to verify the content generated by models such as ChatGPT for accuracy.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2023.1265024
    DOI: 10.3389/fonc.2023.1265024.s001
    DOI: 10.3389/fonc.2023.1265024.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2649216-7
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  • 9
    Online Resource
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    DataSheet_2.zip
    Frontiers Media SA ; 2023
    In:  Frontiers in Oncology Vol. 13 ( 2023-2-16)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 13 ( 2023-2-16)
    Abstract: Deep learning-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. In particular, there is no publicly available open-source solution for large-scale autosegmentation of HN_LNL in the research setting. Methods An expert-delineated cohort of 35 planning CTs was used for training of an nnU-net 3D-fullres/2D-ensemble model for autosegmentation of 20 different HN_LNL. A second cohort acquired at the same institution later in time served as the test set (n = 20). In a completely blinded evaluation, 3 clinical experts rated the quality of deep learning autosegmentations in a head-to-head comparison with expert-created contours. For a subgroup of 10 cases, intraobserver variability was compared to the average deep learning autosegmentation accuracy on the original and recontoured set of expert segmentations. A postprocessing step to adjust craniocaudal boundaries of level autosegmentations to the CT slice plane was introduced and the effect of autocontour consistency with CT slice plane orientation on geometric accuracy and expert rating was investigated. Results Blinded expert ratings for deep learning segmentations and expert-created contours were not significantly different. Deep learning segmentations with slice plane adjustment were rated numerically higher (mean, 81.0 vs. 79.6, p = 0.185) and deep learning segmentations without slice plane adjustment were rated numerically lower (77.2 vs. 79.6, p = 0.167) than manually drawn contours. In a head-to-head comparison, deep learning segmentations with CT slice plane adjustment were rated significantly better than deep learning contours without slice plane adjustment (81.0 vs. 77.2, p = 0.004). Geometric accuracy of deep learning segmentations was not different from intraobserver variability (mean Dice per level, 0.76 vs. 0.77, p = 0.307). Clinical significance of contour consistency with CT slice plane orientation was not represented by geometric accuracy metrics (volumetric Dice, 0.78 vs. 0.78, p = 0.703). Conclusions We show that a nnU-net 3D-fullres/2D-ensemble model can be used for highly accurate autodelineation of HN_LNL using only a limited training dataset that is ideally suited for large-scale standardized autodelineation of HN_LNL in the research setting. Geometric accuracy metrics are only an imperfect surrogate for blinded expert rating.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2023.1115258
    DOI: 10.3389/fonc.2023.1115258.s001
    DOI: 10.3389/fonc.2023.1115258.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2649216-7
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