Analysis of right ventricular mass from magnetic resonance imaging data: a simple post-processing algorithm for correction of partial-volume effects

Magnetic resonance imaging (MRI) of the right ventricle (RV) offers important diagnostic information, but the accuracy of this information is hampered by the complex geometry of the RV. Here, we propose a novel postprocessing algorithm that corrects for partial-volume effects in the analysis of standard MRI cine images of RV mass (RVm) and evaluate the method in clinical and preclinical data. Self-corrected RVm measurement was compared with conventionally measured RVm in 16 patients who showed different clinical indications for cardiac MRI and in 17 Wistar rats with different degrees of pulmonary congestion. The rats were studied under isoflurane anaesthesia. To evaluate the reliability of the proposed method, the measured end-systolic and end-diastolic RVm were compared. Accuracy was evaluated by comparing preclinical RVm to ex vivo RV weight (RVw). We found that use of the self-correcting algorithm improved reliability compared with conventional segmentation. For clinical data, the limits of agreement (LOAs) were -1.8 +/- 8.6g (self-correcting) vs. 5.8 +/- 7.8g (conventional), and coefficients of variation (CoVs) were 7.0% (self-correcting) vs. 14.3% (conventional). For preclinical data, LOAs were 21 +/- 46 mg (self-correcting) vs. 64 +/- 89 mg (conventional), and CoVs were 9.0% (self-correcting) and 17.4% (conventional). Self-corrected RVm also showed better correspondence with the ex vivo RVw: LOAs were -5 +/- 80 mg (self-correcting) vs. 94 +/- 116 mg (conventional) in end-diastole and -26 +/- 74 mg (self-correcting) vs. 31 +/- 98 mg (conventional) in end-systole. The new self-correcting algorithm improves the reliability and accuracy of RVm measurements in both clinical and preclinical MRI. It is simple and easy to implement and does not require any additional MRI data. NEW & NOTEWORTHY Magnetic resonance imaging (MRI) of the right ventricle (RV) offers important diagnostic information, but the accuracy of this information is hampered by the complex geometry of the RV. In particular, the crescent shape of the RV renders it particularly vulnerable to partial-volume effects. We present a new, simple, self-correcting algorithm that can be applied to correct partial-volume effects in MRI-based RV mass estimation. The self-correcting algorithm offers improved reliability and accuracy compared with the conventional approach.

Automated summary

The proposed self-correcting algorithm improves the reliability and accuracy of RVm measurements in both clinical and preclinical MRI data. The algorithm shows lower limits of agreement and coefficients of variation compared to conventional segmentation in clinical data, and similar improvements in preclinical data as well.