Chen Yurui, Anzai Isao A, Kalfa David M, Vedula Vijay
Department of Mechanical Engineering, Columbia University, New York, NY, USA.
Section of Pediatric and Congenital Cardiac Surgery, Division of Cardiac, Thoracic, and Vascular Surgery, Department of Surgery, New York-Presbyterian Morgan Stanley Children's Hospital, Columbia University Medical Center, New York, NY, USA.
medRxiv. 2025 Jul 16:2025.07.15.25331596. doi: 10.1101/2025.07.15.25331596.
Borderline left ventricle (BLV) presents a dilemma between pursuing a biventricular repair (BiVR) and a Stage 1 palliation (S1P) because a discordant pursuit of BiVR increases mortality risk. We aim to develop and validate a personalized computational model to assist surgical decision-making by predicting virtual surgery hemodynamics in BLV patients.
We developed a novel multi-block lumped parameter network (LPN) model of a BLV circulatory system. Patient-specific model parameters were estimated using a semi-automatic tuning framework to fit clinical data in ten retrospectively identified BLV patients. Virtual surgeries (BiVR and S1P) were performed on each patient to quantify post-operative hemodynamics.
In patients who clinically received S1P (Group I, N=5), a virtual BiVR predicted significantly elevated mean pulmonary artery pressure (PAP: 38.00±10.0 vs. 17.50±2.7 mmHg, <0.01), mean left atrial pressure (LAP: 25.40±8.2 vs. 6.20±1.2 mmHg, <0.0001), and single ventricle end-diastolic pressure (SVEDP: 21.80±8.7 vs. 4.80±1.3 mmHg, <0.0001) compared with a virtual S1P. A virtual BiVR in patients who clinically underwent BiVR (Group II, N=5) did not predict any adverse hemodynamic outcome.
A novel digital twinning framework was developed to predict hemodynamics following virtual surgeries in BLV patients. The model predictions align with the clinically adopted procedure in this retrospectively selected cohort by predicting unacceptable PAP, LAP, and SVEDP. This predictive tool may guide surgeons in determining the hemodynamically optimal surgery for BLV infants, but it needs prospective validation.
边缘性左心室（BLV）在进行双心室修复（BiVR）和一期姑息治疗（S1P）之间存在两难抉择，因为不协调地追求BiVR会增加死亡风险。我们旨在开发并验证一个个性化计算模型，通过预测BLV患者虚拟手术的血流动力学来辅助手术决策。
我们开发了一种新型的BLV循环系统多模块集总参数网络（LPN）模型。使用半自动调谐框架估计患者特异性模型参数，以拟合十例回顾性确定的BLV患者的临床数据。对每位患者进行虚拟手术（BiVR和S1P），以量化术后血流动力学。
在临床上接受S1P的患者（第一组，N = 5）中，与虚拟S1P相比，虚拟BiVR预测平均肺动脉压（PAP：38.00±10.0 vs. 17.50±2.7 mmHg，P<0.01）、平均左心房压（LAP：25.40±8.2 vs. 6.20±1.2 mmHg，P<0.0001）和单心室舒张末期压力（SVEDP：21.80±8.7 vs. 4.80±1.3 mmHg，P<0.0001）显著升高。在临床上接受BiVR的患者（第二组，N = 5）中，虚拟BiVR未预测到任何不良血流动力学结果。
开发了一种新型数字孪生框架，以预测BLV患者虚拟手术后的血流动力学。通过预测不可接受的PAP、LAP和SVEDP，该模型预测结果与该回顾性选择队列中临床采用的手术方法一致。这种预测工具可能会指导外科医生为BLV婴儿确定血流动力学上最优的手术方式，但需要进行前瞻性验证。
