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Boromand G, Haugen-Cange H, Asparusova M, Ekestubbe A, Kjeller G. Long-term follow-up of osteoradionecrosis of the mandible. Acta Odontol Scand 2024; 82:48-54. [PMID: 37772879 DOI: 10.1080/00016357.2023.2257316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 09/05/2023] [Indexed: 09/30/2023]
Abstract
AIM Investigating the prevalence of mandibular ORN in a single Swedish Oncology Center. METHODS A total of 450 patients, treated with radiotherapy for squamous cell carcinoma in the oropharynx between 2004 and 2014 were included. Three different techniques of radiotherapy were studied. ORN diagnosis was set when clinical signs according to Marx were observed, or if radiological signs were staged according to Schwartz and Kagan. RESULTS Using the staging system, 90 patients (20%) were diagnosed with ORN. The mean age of the ORN patients was 56.6 years, the older the patient the lower the risk of developing ORN (p = .01). The risk of developing ORN for patients receiving Intensity Modulated Radiotherapy was lower compared to patients treated with the other techniques in the multivariable analysis. Brachytherapy significantly increases the risk of ORN. The risk of ORN increased by 8% each year after radiation (p = .04). The mean time to the ORN diagnosis was 3.9 years. In the multivariate analysis, the risk of ORN increased by 13% each year after radiation (p = .0013). CONCLUSION The mean radiation dose was of greater importance for the risk of ORN than the maximum dose. Elderly people with oropharyngeal cancer were less prone to develop ORN.
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Affiliation(s)
- Ghazaleh Boromand
- Department of Oral and Maxillofacial Surgery, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Hedda Haugen-Cange
- Department of Oncology, Institute of Clinical Sciences at Gothenburg University and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Martin Asparusova
- Department of Oral and Maxillofacial Surgery, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Annika Ekestubbe
- Department of Oral and Maxillofacial Radiology, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Goran Kjeller
- Department of Oral and Maxillofacial Surgery, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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Reber B, Van Dijk L, Anderson B, Mohamed ASR, Fuller C, Lai S, Brock K. Comparison of Machine-Learning and Deep-Learning Methods for the Prediction of Osteoradionecrosis Resulting From Head and Neck Cancer Radiation Therapy. Adv Radiat Oncol 2023; 8:101163. [PMID: 36798732 PMCID: PMC9926206 DOI: 10.1016/j.adro.2022.101163] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
Purpose Deep-learning (DL) techniques have been successful in disease-prediction tasks and could improve the prediction of mandible osteoradionecrosis (ORN) resulting from head and neck cancer (HNC) radiation therapy. In this study, we retrospectively compared the performance of DL algorithms and traditional machine-learning (ML) techniques to predict mandible ORN binary outcome in an extensive cohort of patients with HNC. Methods and Materials Patients who received HNC radiation therapy at the University of Texas MD Anderson Cancer Center from 2005 to 2015 were identified for the ML (n = 1259) and DL (n = 1236) studies. The subjects were followed for ORN development for at least 12 months, with 173 developing ORN and 1086 having no evidence of ORN. The ML models used dose-volume histogram parameters to predict ORN development. These models included logistic regression, random forest, support vector machine, and a random classifier reference. The DL models were based on ResNet, DenseNet, and autoencoder-based architectures. The DL models used each participant's dose cropped to the mandible. The effect of increasing the amount of available training data on the DL models' prediction performance was evaluated by training the DL models using increasing ratios of the original training data. Results The F1 score for the logistic regression model, the best-performing ML model, was 0.3. The best-performing ResNet, DenseNet, and autoencoder-based models had F1 scores of 0.07, 0.14, and 0.23, respectively, whereas the random classifier's F1 score was 0.17. No performance increase was apparent when we increased the amount of training data available for DL model training. Conclusions The ML models had superior performance to their DL counterparts. The lack of improvement in DL performance with increased training data suggests that either more data are needed for appropriate DL model construction or that the image features used in DL models are not suitable for this task.
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Affiliation(s)
- Brandon Reber
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Lisanne Van Dijk
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
- University of Groningen, Groningen, Netherlands
| | - Brian Anderson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
- University of California, San Diego, San Diego, California
| | | | - Clifton Fuller
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stephen Lai
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kristy Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
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Glas HH, Kraeima J, Tribius S, Leusink FKJ, Rendenbach C, Heiland M, Stromberger C, Rashad A, Fuller CD, Mohamed ASR, Lai SY, Witjes MJH. Three-Dimensional Evaluation of Isodose Radiation Volumes in Cases of Severe Mandibular Osteoradionecrosis for the Prediction of Recurrence after Segmental Resection. J Pers Med 2022; 12:jpm12050834. [PMID: 35629256 PMCID: PMC9143211 DOI: 10.3390/jpm12050834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Pre-operative margin planning for the segmental resection of affected bone in mandibular osteoradionecrosis (ORN) is difficult. The aim of this study was to identify a possible relation between the received RT dose, exposed bone volume and the progression of ORN after segmental mandibular resection. Method: Patients diagnosed with grade 3-4 ORN for which a segmental resection was performed were included in the study. Three-dimensional reconstructions of RT isodose volumes were fused with postoperative imaging. The primary outcome was the recurrence of ORN after segmental resection. Subsequently, RT exposed mandibular bone volumes were calculated and the location of the bone cuts relative to the isodose volumes were assessed. Results: Five out of thirty-three patients developed recurrent ORN after segmental mandibular resection. All cases with recurrent ORN were resected inside an isodose volume of ≥56 Gy. The absolute mandibular volume radiated with 56 Gy was significantly smaller in the recurrent group (10.9 mL vs. 30.7 mL, p = 0.006), as was the proportion of the mandible radiated with 56 Gy (23% vs. 45%, p = 0.013). Conclusion: The volume of radiated bone was not predictive for risk of progression. The finding that recurrent ORN occurred with bone resection margins within the 56 Gy isodose volume suggests that this could serve as a starting point for the pre-operative planning of reducing the risk of ORN recurrence.
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Affiliation(s)
- Haye H. Glas
- Department of Oral and Maxillofacial Surgery, University Medical Center Groningen, University of Groningen, 9713GZ Groningen, The Netherlands; (J.K.); (M.J.H.W.)
- Correspondence: ; Tel.: +31-(0)50-361-25-61
| | - Joep Kraeima
- Department of Oral and Maxillofacial Surgery, University Medical Center Groningen, University of Groningen, 9713GZ Groningen, The Netherlands; (J.K.); (M.J.H.W.)
| | - Silke Tribius
- Hermann-Holthusen-Institute for Radiation Oncology, Asklepios Hospital St. Georg, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany;
| | - Frank K. J. Leusink
- Department of Oral and Maxillofacial Surgery, Amsterdam University Medical Center, 1100DD Amsterdam, The Netherlands;
| | - Carsten Rendenbach
- Department of Oral and Maxillofacial Surgery, Charité–Universitätsmedizin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 12203 Berlin, Germany; (C.R.); (M.H.)
| | - Max Heiland
- Department of Oral and Maxillofacial Surgery, Charité–Universitätsmedizin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 12203 Berlin, Germany; (C.R.); (M.H.)
| | - Carmen Stromberger
- Department of Radiation Oncology and Radiation Therapy, Charité–Universitätsmedizin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 12203 Berlin, Germany;
| | - Ashkan Rashad
- Department of Oral, Maxillofacial and Facial Plastic Surgery, RWTH Aachen University Hospital, 52074 Aachen, Germany;
| | - Clifton D. Fuller
- Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (C.D.F.); (A.S.R.M.); (S.Y.L.)
| | - Abdallah S. R. Mohamed
- Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (C.D.F.); (A.S.R.M.); (S.Y.L.)
| | - Stephen Y. Lai
- Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (C.D.F.); (A.S.R.M.); (S.Y.L.)
- Department of Head and Neck Surgery, Division of Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Max J. H. Witjes
- Department of Oral and Maxillofacial Surgery, University Medical Center Groningen, University of Groningen, 9713GZ Groningen, The Netherlands; (J.K.); (M.J.H.W.)
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Gundestrup AK, Lynggaard CD, Forner L, Heino TJ, Jakobsen KK, Fischer-Nielsen A, Grønhøj C, von Buchwald C. Mesenchymal Stem Cell Therapy for Osteoradionecrosis of the Mandible: a Systematic Review of Preclinical and Human Studies. Stem Cell Rev Rep 2021; 16:1208-1221. [PMID: 32869179 DOI: 10.1007/s12015-020-10034-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Osteoradionecrosis (ORN) of the mandible is a severe complication of radiotherapy for head and neck cancer and is arduously difficult to manage. Current treatment options carry risks with some patients remaining incurable. Mesenchymal stromal/stem cell (MSC) therapy has shown promising results supporting osteogenesis and regeneration of radiotherapy-damaged tissues. The aim of this study was to systematically review the literature on the safety and efficacy of MSCs in treating ORN. METHODS A systematic search was performed on MEDLINE, Embase, Cochranes Library online databases, and clinicaltrials.gov to identify preclinical and clinical studies examining the effect of MSCs on osseous healing of ORN. The preclinical studies were assessed according to the SYRCLEs guidelines and risk of bias tool. RESULTS Six studies (n = 142) from 5 countries were eligible for analysis. Of these four were preclinical studies and two clinical case studies. Preclinical studies found MSC treatment to be safe, demonstrating bone restorative effects and improved soft tissue regeneration. In the clinical cases, healing of bone and soft tissue was reported with no serious adverse events. CONCLUSION The evidence from the included studies suggests that MSCs may have beneficial regenerative effects on the healing of ORN. None of the studies reported adverse events with the use of MSCs. More carefully controlled studies with well-identified cells are however needed to demonstrate the efficacy of MSCs in a clinical setting. Graphical abstract.
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Affiliation(s)
- Anders Kierkegaard Gundestrup
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Charlotte Duch Lynggaard
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Lone Forner
- Department of Oral and Maxillofacial Surgery, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Terhi J Heino
- Institute of Biomedicine, Faculty of Medicine, University of Turku, Turku, Finland
| | - Kathrine Kronberg Jakobsen
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anne Fischer-Nielsen
- Department of Immunology, Cell Therapy Facility, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Christian Grønhøj
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Christian von Buchwald
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
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