Magnetic resonance imaging-guided versus surrogate-based motion tracking in liver radiation therapy: A prospective comparative study

Chiara Paganelli, Matteo Seregni, Giovanni Fattori, Paul Summers, Massimo Bellomi, Guido Baroni, Marco Riboldi

Research output: Contribution to journalArticle

Abstract

Purpose This study applied automatic feature detection on cine-magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each feature was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.

Original languageEnglish
Pages (from-to)840-848
Number of pages9
JournalInternational Journal of Radiation Oncology Biology Physics
Volume91
Issue number4
DOIs
Publication statusPublished - Mar 15 2015

Fingerprint

liver
magnetic resonance
radiation therapy
Radiotherapy
Magnetic Resonance Imaging
Prospective Studies
Liver
Cine Magnetic Resonance Imaging
temporal resolution
Volunteers
markers
tumors
high resolution
Population
Neoplasms

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Radiation
  • Cancer Research
  • Medicine(all)

Cite this

Magnetic resonance imaging-guided versus surrogate-based motion tracking in liver radiation therapy : A prospective comparative study. / Paganelli, Chiara; Seregni, Matteo; Fattori, Giovanni; Summers, Paul; Bellomi, Massimo; Baroni, Guido; Riboldi, Marco.

In: International Journal of Radiation Oncology Biology Physics, Vol. 91, No. 4, 15.03.2015, p. 840-848.

Research output: Contribution to journalArticle

@article{b8d2910c7e294176b26c45c2f2500ced,
title = "Magnetic resonance imaging-guided versus surrogate-based motion tracking in liver radiation therapy: A prospective comparative study",
abstract = "Purpose This study applied automatic feature detection on cine-magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each feature was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7{\%} to 23{\%} (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30{\%} in 50{\%} of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.",
author = "Chiara Paganelli and Matteo Seregni and Giovanni Fattori and Paul Summers and Massimo Bellomi and Guido Baroni and Marco Riboldi",
year = "2015",
month = "3",
day = "15",
doi = "10.1016/j.ijrobp.2014.12.013",
language = "English",
volume = "91",
pages = "840--848",
journal = "International Journal of Radiation Oncology Biology Physics",
issn = "0360-3016",
publisher = "Elsevier Inc.",
number = "4",

}

TY - JOUR

T1 - Magnetic resonance imaging-guided versus surrogate-based motion tracking in liver radiation therapy

T2 - A prospective comparative study

AU - Paganelli, Chiara

AU - Seregni, Matteo

AU - Fattori, Giovanni

AU - Summers, Paul

AU - Bellomi, Massimo

AU - Baroni, Guido

AU - Riboldi, Marco

PY - 2015/3/15

Y1 - 2015/3/15

N2 - Purpose This study applied automatic feature detection on cine-magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each feature was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.

AB - Purpose This study applied automatic feature detection on cine-magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each feature was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.

UR - http://www.scopus.com/inward/record.url?scp=84924705992&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924705992&partnerID=8YFLogxK

U2 - 10.1016/j.ijrobp.2014.12.013

DO - 10.1016/j.ijrobp.2014.12.013

M3 - Article

C2 - 25752399

AN - SCOPUS:84924705992

VL - 91

SP - 840

EP - 848

JO - International Journal of Radiation Oncology Biology Physics

JF - International Journal of Radiation Oncology Biology Physics

SN - 0360-3016

IS - 4

ER -