Background— Pulmonary vascular resistance (PVR) quantification is important in the treatment of children with pulmonary hypertension. The Fick principle, used to quantify pulmonary artery flow, may be a flawed technique. We describe a novel method of PVR quantification by the use of magnetic resonance (MR) flow data and invasive pressure measurements. Methods and Results— In 24 patients with either suspected pulmonary hypertension or congenital heart disease requiring preoperative assessment, PVR was calculated by the use of simultaneously acquired MR flow and invasive pressure measurements (condition 1). In 19 of the 24 patients, PVR was also calculated at 20 ppm nitric oxide +30% (condition 2) and at 20 ppm nitric oxide +100% oxygen (condition 3), with the use of the MR method. This method proved safe and feasible in all patients. In 15 of 19 patients, PVR calculated by Fick flow was compared with the MR method. At condition 1, Bland-Altman analysis revealed a bias of 2.3% (MR > Fick) and limits of agreement of 50.2% to −45.5%. At condition 2, there was poorer agreement (bias was 28%, and the limits of agreement were 151.3% to 95.2%). At condition 3, there was very poor agreement (bias was 54.2%, and the limits of agreement were 174.4% to −66.0%). Conclusions— We have demonstrated the feasibility of using simultaneous invasive pressure measurements and MR flow data to measure PVR in humans.
14 July 2015 in Journal of Magnetic Resonance Imaging
Respiratory organ motion has a significant impact on the planning and delivery of radiotherapy (RT) treatment for lung cancer. Currently widespread techniques, such as 4D-computed tomography (4DCT), cannot be used to measure variability of this motion from one cycle to the next. In this paper, we describe the use of fast magnetic resonance imaging (MRI) techniques to investigate the intra- and inter-cycle reproducibility of respiratory motion and also to estimate the level of errors that may be introduced into treatment delivery by using various breath-hold imaging strategies during lung RT planning. A reference model of respiratory motion is formed to enable comparison of different breathing cycles at any arbitrary position in the respiratory cycle. This is constructed by using free-breathing images from the inhale phase of a single breathing cycle, then co-registering the images, and thereby tracking landmarks. This reference model is then compared to alternative models constructed from images acquired during the exhale phase of the same cycle and the inhale phase of a subsequent cycle, to assess intra- and inter-cycle variability ('hysteresis' and 'reproducibility') of organ motion. The reference model is also compared to a series of models formed from breath-hold data at exhale and inhale. Evaluation of these models is carried out on data from ten healthy volunteers and five lung cancer patients. Free-breathing models show good levels of intra- and inter-cycle reproducibility across the tidal breathing range. Mean intra-cycle errors in the position of organ surface landmarks of 1.5(1.4)-3.5(3.3) mm for volunteers and 2.8(1.8)-5.2(5.2) mm for patients. Equivalent measures of inter-cycle variability across this range are 1.7(1.0)-3.9(3.3) mm for volunteers and 2.8(1.8)-3.3(2.2) mm for patients. As expected, models based on breath-hold sequences do not represent normal tidal motion as well as those based on free-breathing data, with mean errors of 4.4(2.2)-7.7(3.9) mm for volunteers and 10.1(6.1)-12.5(6.3) mm for patients. Errors are generally larger still when using a single breath-hold image at either exhale or inhale to represent the lung. This indicates that account should be taken of intra- and inter-cycle respiratory motion variability and that breath-hold-based methods of obtaining data for RT planning may potentially introduce large errors. This approach to analysis of motion and variability has potential to inform decisions about treatment margins and optimize RT planning.