QUANTIFYING LOCAL LUNG PERFUSION AND VENTILATION USING CORRELATED SPECT AND CT DATA

Citation
Emf. Damen et al., QUANTIFYING LOCAL LUNG PERFUSION AND VENTILATION USING CORRELATED SPECT AND CT DATA, The Journal of nuclear medicine, 35(5), 1994, pp. 784-792
Citations number
15
Categorie Soggetti
Radiology,Nuclear Medicine & Medical Imaging
ISSN journal
01615505
Volume
35
Issue
5
Year of publication
1994
Pages
784 - 792
Database
ISI
SICI code
0161-5505(1994)35:5<784:QLLPAV>2.0.ZU;2-7
Abstract
A clinically applicable method for quantifying lung perfusion and vent ilation on a subregional (local) scale from SPECT scans in order to es timate local lung function in patients with pre-existing pulmonary dis ease and to monitor local treatment effects was developed and evaluate d. Methods: SPECT Tc-99m perfusion and Kr-81m ventilation images were corrected for photon attenuation and scatter effect with a postreconst ruction correction method incorporating a variable-effective linear-at tenuation coefficient calculated from spatially-correlated CT data. A new algorithm was developed to quantify local ventilation from the SPE CT data, which, in contrast with other algorithms, makes no assumption s on ventilation homogeneity over the lung. The quantification procedu re was applied to clinical data from patients with a normal lung funct ion and from patients suffering from radiation-induced pulmonary dysfu nction. Results: The calculated attenuation correction factors on the observed number of counts in the lung range from 2.0 to 3.0 and 2.3 to 3.5 for Kr-81m and Tc-99m, respectively, showing a systematic increas e from the diaphragm to the lung apex. As a result of this correction, the values of local perfusion and ventilation differ 10%-15% from val ues calculated without attenuation correction. The calculated values o f the local ventilation are 10%-50% lower than those found by quantifi cation algorithms which assume homogeneous ventilation. Conclusions: T he methods presented here are robust with respect to uncertainties in the input parameters and yield realistic values for perfusion and vent ilation distribution in the lung with an intrinsic accuracy (largely d etermined by count statistics) of about 10%.