Real-time video kinematic evaluation of the in situ beating right ventricle after pulmonary valve replacement in patients with tetralogy of Fallot: a pilot study

Abstract

OBJECTIVES The timing for pulmonary valve replacement (PVR) after tetralogy of Fallot repair is controversial, due to limitations in estimating right ventricular dysfunction and recovery. Intraoperative imaging could add prognostic information, but transoesophageal echocardiography is unsuitable for exploring right heart function. Right ventricular function after PVR was investigated in real time using a novel video-based contactless kinematic evaluation technology (Vi.Ki.E.), which calculates cardiac fatigue and energy consumption. METHODS Six consecutive patients undergoing PVR at 13.8 ± 2.6 years (range 6.9–19.8) after the repair of tetralogy of Fallot were enrolled. Mean right ventricular end-diastolic and end-systolic volume at magnetic resonance imaging were 115.6 ± 16.2 ml/m2 and 61.5 ± 14.6 ml/m2, respectively. Vi.Ki.E. uses a fast-resolution camera placed 45 cm above the open chest, recording cardiac kinematics before and after PVR. An algorithm defines cardiac parameters, such as energy, fatigue, maximum contraction velocity and tissue displacement. RESULTS There were no perioperative complications, with patients discharged in satisfactory clinical conditions after 7 ± 2 days (range 5–9). Vi.Ki.E. parameters describing right ventricular dysfunction decreased significantly after surgery: energy consumption by 45% [271 125 ± 9422 (mm/s)2 vs 149 202 ± 11 980 (mm/s)2, P = 0.0001], cardiac fatigue by 12% (292 671 ± 29 369 mm/s2 vs 258 755 ± 42 750 mm/s2, P = 0.01), contraction velocity by 54% (3412 ± 749 mm/s vs 1579 ± 400 mm/s, P = 0.0007) and displacement by 23% (27 ± 4 mm vs 21 ± 4 mm, P = 0.01). Patients undergoing PVR at lower end-diastolic volumes, had greater functional recovery of Vi.Ki.E. parameters. CONCLUSIONS Intraoperative Vi.Ki.E shows immediate recovery of right ventricular mechanics after PVR with less cardiac fatigue and energy consumption, providing novel insights that may have a prognostic relevance for functional recovery.

Artificial Intelligence Supports Decision Making during Open-Chest Surgery of Rare Congenital Heart Defects

“…First, we assessed the cardiac kinematics (Figure 6a) in one ToF patient who underwent PVR with a known favorable outcome (discharged after 7 days of hospitalization). As in our previous works [22,23], we observed a decreasing trend for all Vi.Ki.E. parameters, which was significant for the energy and perimeter.…”

“…The Vi.Ki.E. assessment showed a decreasing trend for all kinematic parameters in line with our previous studies on right ventricular unloading [22,23]. We used the signal-to-noise ratio (SNR) predictor as a representative feature to build a simplified 2D classification model, named "decision surface", for both coordinates.…”

“…We applied Vi.Ki.E. in the field of myocardial ischemia [21] and complex congenital heart diseases such as Tetralogy of Fallot (ToF) [22,23], which is the most common RV pathology representing 7-10% of the congenital cardiac defects [24]. Interestingly, in our most recent work on ToF [23], we observed a promising correlation between the before surgery Vi.Ki.E.…”

“…In this study, we trained two SML classifiers based on Vi.Ki.E., a contactless imaging technology developed by our laboratories to evaluate the RV kinematics [21][22][23]43]. We used the Vi.Ki.E.…”

“…The surgical methods and selection criteria of our study were described in our previous work [22]. Briefly, all surgical procedures were performed by one surgeon (G.B.L.)…”