Literature DB >> 28255667

Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry.

Gurleen Dhami1, Jing Zeng1, Hubert J Vesselle2, Paul E Kinahan2, Robert S Miyaoka2, Shilpen A Patel1, Ramesh Rengan1, Stephen R Bowen3,4.   

Abstract

PURPOSE: To design and apply a framework for predicting symptomatic radiation pneumonitis in patients undergoing thoracic radiation, using both pretreatment anatomic and perfused lung dose-volume parameters.
MATERIALS AND METHODS: Radiation treatment planning CT scans were coregistered with pretreatment [99mTc]MAA perfusion SPECT/CT scans of 20 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ≥ 2 (CTCAE v4 grading system). Anatomic lung dose-volume parameters were collected from the treatment planning scans. Perfusion dose-volume parameters were calculated from pretreatment SPECT/CT scans. Equivalent doses in 2 Gy per fraction were calculated in the lung to account for differences in treatment regimens and spatial variations in lung dose (EQD2lung).
RESULTS: Anatomic lung dosimetric parameters (MLD) and functional lung dosimetric parameters (pMLD70%) were identified as candidate predictors of grade ≥ 2 radiation pneumonitis (AUC > 0.93, p < 0.01). Pairing of an anatomic and functional dosimetric parameter (e. g., MLD and pMLD70%) may further improve prediction accuracy. Not all individuals with high anatomic lung dose (MLD > 13.6 GyEQD2lung, 19.3 Gy for patients receiving 60 Gy in 30 fractions) developed radiation pneumonitis, but all individuals who also had high mean dose to perfused lung (pMLD70% > 13.3 GyEQD2) developed radiation pneumonitis.
CONCLUSIONS: The preliminary application of this framework revealed differences between anatomic and perfused lung dosimetry in this limited patient cohort. The addition of perfused lung parameters may help risk stratify patients for radiation pneumonitis, especially in treatment plans with high anatomic mean lung dose. Further investigations are warranted.

Entities:  

Keywords:  Computed tomography; Radiotherapy; SPECT; Sequelae; Toxicity

Mesh:

Year:  2017        PMID: 28255667      PMCID: PMC5406240          DOI: 10.1007/s00066-017-1114-0

Source DB:  PubMed          Journal:  Strahlenther Onkol        ISSN: 0179-7158            Impact factor:   3.621


  28 in total

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