Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Impact of dose calculation algorithm on magnetic resonance imaging-only radiotherapy for prostate and glioma

af Wetterstedt, Sacha LU ; Persson, Emilia LU ; Jamtheim Gustafsson, Christian LU ; Gunnlaugsson, Adalsteinn LU ; Lerner, Minna LU ; Olsson, Lars E LU orcid and Pommer, Tobias LU (2026) In Physics and imaging in radiation oncology 40.
Abstract
Background and purpose: Synthetic computed tomography (sCT) enables magnetic resonance imaging (MRI)-only radiotherapy by providing electron density information for dose calculation. While sCT-based planning has been proven sufficiently accurate for convolution-based dose calculation algorithms, linear Boltzmann transport equation (LBTE)-based approaches exhibit higher sensitivity to tissue heterogeneities. This study evaluated the accuracy of both dose calculation algorithm types for MRI-only in prostate and glioma radiotherapy.

Materials and methods: Clinical treatment plans for thirty-nine prostate cancer patients and seventeen glioma patients were recalculated on atlas- and deep learning (DL)-based sCTs and conventional CT... (More)
Background and purpose: Synthetic computed tomography (sCT) enables magnetic resonance imaging (MRI)-only radiotherapy by providing electron density information for dose calculation. While sCT-based planning has been proven sufficiently accurate for convolution-based dose calculation algorithms, linear Boltzmann transport equation (LBTE)-based approaches exhibit higher sensitivity to tissue heterogeneities. This study evaluated the accuracy of both dose calculation algorithm types for MRI-only in prostate and glioma radiotherapy.

Materials and methods: Clinical treatment plans for thirty-nine prostate cancer patients and seventeen glioma patients were recalculated on atlas- and deep learning (DL)-based sCTs and conventional CT using convolution- and LBTE-based algorithms. Target dose metrics were analyzed as relative differences, while organs of interest (OOI) dose criteria were evaluated as absolute differences between sCT- and CT-based calculations. Statistical significance was assessed using paired t-tests (α = 0.05).

Results: For target volumes, statistically significant differences between sCT- and CT-based calculations were observed for both dose calculation algorithms (p < 0.001). In prostate patients, mean differences in target dose metrics were ≤ 1.4% for the LBTE-based algorithm and ≤ 0.5% for the convolution-based algorithm. Slightly smaller dose differences were observed for glioma patients, ≤ 0.8% and ≤ 0.5%, respectively. OOI dose differences were small (≤ 0.6%). The LBTE-based algorithm consistently yielded the largest dose differences between CT and sCT.

Conclusions: Although the LBTE-based approach demonstrated higher sensitivity to sCT-related CT number discrepancies than the convolution-based dose calculation algorithm, the resulting dose differences remained within clinically acceptable limits, supporting the robustness of MRI-only radiotherapy for both atlas- and DL-based sCTs. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Physics and imaging in radiation oncology
volume
40
article number
101045
publisher
Elsevier
external identifiers
  • pmid:42602256
  • scopus:105046544603
ISSN
2405-6316
DOI
10.1016/j.phro.2026.101045
language
English
LU publication?
yes
id
d0f97ac4-a75d-400b-bc41-18597153b84d
date added to LUP
2026-09-25 13:37:36
date last changed
2026-09-26 04:00:34
@article{d0f97ac4-a75d-400b-bc41-18597153b84d,
  abstract     = {{Background and purpose: Synthetic computed tomography (sCT) enables magnetic resonance imaging (MRI)-only radiotherapy by providing electron density information for dose calculation. While sCT-based planning has been proven sufficiently accurate for convolution-based dose calculation algorithms, linear Boltzmann transport equation (LBTE)-based approaches exhibit higher sensitivity to tissue heterogeneities. This study evaluated the accuracy of both dose calculation algorithm types for MRI-only in prostate and glioma radiotherapy.<br/><br/>Materials and methods: Clinical treatment plans for thirty-nine prostate cancer patients and seventeen glioma patients were recalculated on atlas- and deep learning (DL)-based sCTs and conventional CT using convolution- and LBTE-based algorithms. Target dose metrics were analyzed as relative differences, while organs of interest (OOI) dose criteria were evaluated as absolute differences between sCT- and CT-based calculations. Statistical significance was assessed using paired t-tests (α = 0.05).<br/><br/>Results: For target volumes, statistically significant differences between sCT- and CT-based calculations were observed for both dose calculation algorithms (p &lt; 0.001). In prostate patients, mean differences in target dose metrics were ≤ 1.4% for the LBTE-based algorithm and ≤ 0.5% for the convolution-based algorithm. Slightly smaller dose differences were observed for glioma patients, ≤ 0.8% and ≤ 0.5%, respectively. OOI dose differences were small (≤ 0.6%). The LBTE-based algorithm consistently yielded the largest dose differences between CT and sCT.<br/><br/>Conclusions: Although the LBTE-based approach demonstrated higher sensitivity to sCT-related CT number discrepancies than the convolution-based dose calculation algorithm, the resulting dose differences remained within clinically acceptable limits, supporting the robustness of MRI-only radiotherapy for both atlas- and DL-based sCTs.}},
  author       = {{af Wetterstedt, Sacha and Persson, Emilia and Jamtheim Gustafsson, Christian and Gunnlaugsson, Adalsteinn and Lerner, Minna and Olsson, Lars E and Pommer, Tobias}},
  issn         = {{2405-6316}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Physics and imaging in radiation oncology}},
  title        = {{Impact of dose calculation algorithm on magnetic resonance imaging-only radiotherapy for prostate and glioma}},
  url          = {{http://dx.doi.org/10.1016/j.phro.2026.101045}},
  doi          = {{10.1016/j.phro.2026.101045}},
  volume       = {{40}},
  year         = {{2026}},
}