Assessment of setup uncertainty in hypofractionated liver radiation therapy with a breath-hold technique using automatic image registration-based image guidance.


Journal

Radiation oncology (London, England)
ISSN: 1748-717X
Titre abrégé: Radiat Oncol
Pays: England
ID NLM: 101265111

Informations de publication

Date de publication:
30 Aug 2019
Historique:
received: 14 02 2019
accepted: 21 08 2019
entrez: 1 9 2019
pubmed: 1 9 2019
medline: 11 2 2020
Statut: epublish

Résumé

Target localization in radiation therapy is affected by numerous sources of uncertainty. Despite measures to minimize the breathing motion, the treatment of hypofractionated liver radiation therapy is further challenged by residual uncertainty coming from involuntary organ motion and daily changes in the shape and location of abdominal organs. To address the residual uncertainty, clinics implement image-guided radiation therapy at varying levels of soft-tissue contrast. This study utilized the treatment records from the patients that have received hypofractionated liver radiation therapy using in-room computed tomography (CT) imaging to assess the setup uncertainty and to estimate the appropriate planning treatment volume (PTV) margins in the absence of in-room CT imaging. We collected 917 pre-treatment daily in-room CT images from 69 patients who received hypofractionated radiation therapy to the liver with the inspiration breath-hold technique. For each treatment, the daily CT was initially aligned to the planning CT based on the shape of the liver automatically using a CT-CT alignment software. After the initial alignment, manual shift corrections were determined by visual inspection of the two images, and the corrections were applied to shift the patient to the physician-approved treatment position. Considering the final alignment as the gold-standard setup, systematic and random uncertainties in the automatic alignment were quantified, and the uncertainties were used to calculate the PTV margins. The median discrepancy between the final and automatic alignment was 1.1 mm (0-24.3 mm), and 38% of treated fractions required manual corrections of ≥3 mm. The systematic uncertainty was 1.5 mm in the anterior-posterior (AP) direction, 1.1 mm in the left-right (LR) direction, and 2.4 mm in the superior-inferior (SI) direction. The random uncertainty was 2.2 mm in the AP, 1.9 mm in the LR, and 2.2 mm in the SI direction. The PTV margins recommended to be used in the absence of in-room CT imaging were 5.3 mm in the AP, 3.5 mm in the LR, and 5.1 mm in the SI direction. Manual shift correction based on soft-tissue alignment is substantial in the treatment of the abdominal region. In-room CT can reduce PTV margin by up to 5 mm, which may be especially beneficial for dose escalation and normal tissue sparing in hypofractionated liver radiation therapy.

Sections du résumé

BACKGROUND BACKGROUND
Target localization in radiation therapy is affected by numerous sources of uncertainty. Despite measures to minimize the breathing motion, the treatment of hypofractionated liver radiation therapy is further challenged by residual uncertainty coming from involuntary organ motion and daily changes in the shape and location of abdominal organs. To address the residual uncertainty, clinics implement image-guided radiation therapy at varying levels of soft-tissue contrast. This study utilized the treatment records from the patients that have received hypofractionated liver radiation therapy using in-room computed tomography (CT) imaging to assess the setup uncertainty and to estimate the appropriate planning treatment volume (PTV) margins in the absence of in-room CT imaging.
METHODS METHODS
We collected 917 pre-treatment daily in-room CT images from 69 patients who received hypofractionated radiation therapy to the liver with the inspiration breath-hold technique. For each treatment, the daily CT was initially aligned to the planning CT based on the shape of the liver automatically using a CT-CT alignment software. After the initial alignment, manual shift corrections were determined by visual inspection of the two images, and the corrections were applied to shift the patient to the physician-approved treatment position. Considering the final alignment as the gold-standard setup, systematic and random uncertainties in the automatic alignment were quantified, and the uncertainties were used to calculate the PTV margins.
RESULTS RESULTS
The median discrepancy between the final and automatic alignment was 1.1 mm (0-24.3 mm), and 38% of treated fractions required manual corrections of ≥3 mm. The systematic uncertainty was 1.5 mm in the anterior-posterior (AP) direction, 1.1 mm in the left-right (LR) direction, and 2.4 mm in the superior-inferior (SI) direction. The random uncertainty was 2.2 mm in the AP, 1.9 mm in the LR, and 2.2 mm in the SI direction. The PTV margins recommended to be used in the absence of in-room CT imaging were 5.3 mm in the AP, 3.5 mm in the LR, and 5.1 mm in the SI direction.
CONCLUSIONS CONCLUSIONS
Manual shift correction based on soft-tissue alignment is substantial in the treatment of the abdominal region. In-room CT can reduce PTV margin by up to 5 mm, which may be especially beneficial for dose escalation and normal tissue sparing in hypofractionated liver radiation therapy.

Identifiants

pubmed: 31470860
doi: 10.1186/s13014-019-1361-6
pii: 10.1186/s13014-019-1361-6
pmc: PMC6717376
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

154

Subventions

Organisme : NCI NIH HHS
ID : P30 CA016672
Pays : United States

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Auteurs

Gye Won Choi (GW)

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Yelin Suh (Y)

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Prajnan Das (P)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Joseph Herman (J)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Emma Holliday (E)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Eugene Koay (E)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Albert C Koong (AC)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Sunil Krishnan (S)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Bruce D Minsky (BD)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Grace L Smith (GL)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Cullen M Taniguchi (CM)

Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Sam Beddar (S)

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. abeddar@mdanderson.org.
The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX, 77030, USA. abeddar@mdanderson.org.

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Classifications MeSH