Literature DB >> 33761491

Synthetic CT for single-fraction neoadjuvant partial breast irradiation on an MRI-linac.

M L Groot Koerkamp1, Y J M de Hond1,2, M Maspero1,3, C Kontaxis1, S Mandija1,3, J E Vasmel1, R K Charaghvandi4, M E P Philippens1, B van Asselen1, H J G D van den Bongard5, S S Hackett1, A C Houweling1.   

Abstract

A synthetic computed tomography (sCT) is required for daily plan optimization on an MRI-linac. Yet, only limited information is available on the accuracy of dose calculations on sCT for breast radiotherapy. This work aimed to (1) evaluate dosimetric accuracy of treatment plans for single-fraction neoadjuvant partial breast irradiation (PBI) on a 1.5 T MRI-linac calculated on a) bulk-density sCT mimicking the current MRI-linac workflow and b) deep learning-generated sCT, and (2) investigate the number of bulk-density levels required. For ten breast cancer patients we created three bulk-density sCTs of increasing complexity from the planning-CT, using bulk-density for: (1) body, lungs, and GTV (sCTBD1); (2) volumes for sCTBD1plus chest wall and ipsilateral breast (sCTBD2); (3) volumes for sCTBD2plus ribs (sCTBD3); and a deep learning-generated sCT (sCTDL) from a 1.5 T MRI in supine position. Single-fraction neoadjuvant PBI treatment plans for a 1.5 T MRI-linac were optimized on each sCT and recalculated on the planning-CT. Image evaluation was performed by assessing mean absolute error (MAE) and mean error (ME) in Hounsfield Units (HU) between the sCTs and the planning-CT. Dosimetric evaluation was performed by assessing dose differences, gamma pass rates, and dose-volume histogram (DVH) differences. The following results were obtained (median across patients for sCTBD1/sCTBD2/sCTBD3/sCTDLrespectively): MAE inside the body contour was 106/104/104/75 HU and ME was 8/9/6/28 HU, mean dose difference in the PTVGTVwas 0.15/0.00/0.00/-0.07 Gy, median gamma pass rate (2%/2 mm, 10% dose threshold) was 98.9/98.9/98.7/99.4%, and differences in DVH parameters were well below 2% for all structures except for the skin in the sCTDL. Accurate dose calculations for single-fraction neoadjuvant PBI on an MRI-linac could be performed on both bulk-density and deep learning sCT, facilitating further implementation of MRI-guided radiotherapy for breast cancer. Balancing simplicity and accuracy, sCTBD2showed the optimal number of bulk-density levels for a bulk-density approach.
© 2021 Institute of Physics and Engineering in Medicine.

Entities:  

Keywords:  MRI-linac; MRI-only radiotherapy; convolutional networks; partial breast irradiation; pseudo-CT

Year:  2021        PMID: 33761491     DOI: 10.1088/1361-6560/abf1ba

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  2 in total

1.  Generation of Synthetic-Pseudo MR Images from Real CT Images.

Authors:  Isam F Abu-Qasmieh; Ihssan S Masad; Hiam H Al-Quran; Khaled Z Alawneh
Journal:  Tomography       Date:  2022-05-03

2.  Movement assessment of breast and organ-at-risks using free-breathing, self-gating 4D magnetic resonance imaging workflow for breast cancer radiation therapy.

Authors:  Melanie Habatsch; Manuel Schneider; Martin Requardt; Sylvain Doussin
Journal:  Phys Imaging Radiat Oncol       Date:  2022-05-14
  2 in total

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