B Berthon1, M Evans2, C Marshall3, N Palaniappan2, N Cole2, V Jayaprakasam2, T Rackley2, E Spezi4. 1. Wales Research & Diagnostic PET Imaging Centre, Cardiff, UK. Electronic address: beatrice.walker@espci.fr. 2. Velindre Cancer Centre, Cardiff, UK. 3. Wales Research & Diagnostic PET Imaging Centre, Cardiff, UK. 4. Velindre Cancer Centre, Cardiff, UK; School of Engineering, Cardiff University, Cardiff, UK.
Abstract
PURPOSE: To evaluate the feasibility and impact of using a novel advanced PET auto-segmentation method in Head and Neck (H&N) radiotherapy treatment (RT) planning. METHODS: ATLAAS, Automatic decision Tree-based Learning Algorithm for Advanced Segmentation, previously developed and validated on pre-clinical data, was applied to 18F-FDG-PET/CT scans of 20 H&N patients undergoing Intensity Modulated Radiation Therapy. Primary Gross Tumour Volumes (GTVs) manually delineated on CT/MRI scans (GTVpCT/MRI), together with ATLAAS-generated contours (GTVpATLAAS) were used to derive the RT planning GTV (GTVpfinal). ATLAAS outlines were compared to CT/MRI and final GTVs qualitatively and quantitatively using a conformity metric. RESULTS: The ATLAAS contours were found to be reliable and useful. The volume of GTVpATLAAS was smaller than GTVpCT/MRI in 70% of the cases, with an average conformity index of 0.70. The information provided by ATLAAS was used to grow the GTVpCT/MRI in 10 cases (up to 10.6mL) and to shrink the GTVpCT/MRI in 7 cases (up to 12.3mL). ATLAAS provided complementary information to CT/MRI and GTVpATLAAS contributed to up to 33% of the final GTV volume across the patient cohort. CONCLUSIONS: ATLAAS can deliver operator independent PET segmentation to augment clinical outlining using CT and MRI and could have utility in future clinical studies.
PURPOSE: To evaluate the feasibility and impact of using a novel advanced PET auto-segmentation method in Head and Neck (H&N) radiotherapy treatment (RT) planning. METHODS: ATLAAS, Automatic decision Tree-based Learning Algorithm for Advanced Segmentation, previously developed and validated on pre-clinical data, was applied to 18F-FDG-PET/CT scans of 20 H&N patients undergoing Intensity Modulated Radiation Therapy. Primary Gross Tumour Volumes (GTVs) manually delineated on CT/MRI scans (GTVpCT/MRI), together with ATLAAS-generated contours (GTVpATLAAS) were used to derive the RT planning GTV (GTVpfinal). ATLAAS outlines were compared to CT/MRI and final GTVs qualitatively and quantitatively using a conformity metric. RESULTS: The ATLAAS contours were found to be reliable and useful. The volume of GTVpATLAAS was smaller than GTVpCT/MRI in 70% of the cases, with an average conformity index of 0.70. The information provided by ATLAAS was used to grow the GTVpCT/MRI in 10 cases (up to 10.6mL) and to shrink the GTVpCT/MRI in 7 cases (up to 12.3mL). ATLAAS provided complementary information to CT/MRI and GTVpATLAAS contributed to up to 33% of the final GTV volume across the patient cohort. CONCLUSIONS: ATLAAS can deliver operator independent PET segmentation to augment clinical outlining using CT and MRI and could have utility in future clinical studies.
Authors: Beatrice Berthon; Emiliano Spezi; Paulina Galavis; Tony Shepherd; Aditya Apte; Mathieu Hatt; Hadi Fayad; Elisabetta De Bernardi; Chiara D Soffientini; C Ross Schmidtlein; Issam El Naqa; Robert Jeraj; Wei Lu; Shiva Das; Habib Zaidi; Osama R Mawlawi; Dimitris Visvikis; John A Lee; Assen S Kirov Journal: Med Phys Date: 2017-07-02 Impact factor: 4.071
Authors: Constantin Lapa; Ursula Nestle; Nathalie L Albert; Christian Baues; Ambros Beer; Andreas Buck; Volker Budach; Rebecca Bütof; Stephanie E Combs; Thorsten Derlin; Matthias Eiber; Wolfgang P Fendler; Christian Furth; Cihan Gani; Eleni Gkika; Anca-L Grosu; Christoph Henkenberens; Harun Ilhan; Steffen Löck; Simone Marnitz-Schulze; Matthias Miederer; Michael Mix; Nils H Nicolay; Maximilian Niyazi; Christoph Pöttgen; Claus M Rödel; Imke Schatka; Sarah M Schwarzenboeck; Andrei S Todica; Wolfgang Weber; Simone Wegen; Thomas Wiegel; Constantinos Zamboglou; Daniel Zips; Klaus Zöphel; Sebastian Zschaeck; Daniela Thorwarth; Esther G C Troost Journal: Strahlenther Onkol Date: 2021-07-14 Impact factor: 3.621
Authors: Craig Parkinson; Kieran Foley; Philip Whybra; Robert Hills; Ashley Roberts; Chris Marshall; John Staffurth; Emiliano Spezi Journal: EJNMMI Res Date: 2018-04-11 Impact factor: 3.138