Related Experiment Video
Updated: Mar 2, 2026
Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
Published on: April 12, 2024
Sci-Fri AM: Imaging - 04: SPECT-based functional lung imaging in the prediction of radiation pneumonitis: A
D Hoover1, R H Reid2, G Rodrigues3,4
1London Regional Cancer Program, Department of Physics and Engineering.
Purpose:
To investigate whether functionally-weighted dose-volume histogram (DVH) parameters are more predictive of radiation-induced pneumonitis (RP) than standard parameters such as V20 and mean lung dose (MLD).
Materials And Methods:
A retrospective chart review identified 26 patients who received curative-intent radiation therapy for primary carcinoma of the lung. Prior to treatment, all patients received single photon emission computed tomography (SPECT) to assess both lung ventilation and lung perfusion. Patients were assessed for clinical RP using standard criteria and were separated into a non-RP group (RP grade < 2) and an RP-group (RP grade ≥ 2). Standard DVH parameters (V10, V20, V30, MLD) and their function-weighted counterparts (for perfusion: pF10, pF20, pF30, pMLD; for ventilation: vF10, vF20, vF30, vMLD) were evaluated for each group. Receiver operating characteristics (ROC) curves were created and the area under the curve (AUC) computed.
Results:
7 of 26 patients had grade ≥ 2 pneumonitis. Both pF20 (p=0.022) and vF20 (p=0.036) were significantly different between the 2 groups; V20 was not (p=0.06). Both pF30 (p=0.008) and vF30 (p=0.025) were significantly different between groups while V30 failed to reach significance (p=0.072). Standard MLD (p=0.011), pMLD (p=0.001), and vMLD (p=0.011) were all significantly different. The ROC curves indicated that both the perfusion-weighted parameters and the ventilation-weighted parameters outperformed the standard DVH parameters as predictors of RP grade ≥2.
Conclusions:
SPECT-based, function-weighted DVH parameters appear to be useful as predictors of RP.
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