Calcium Pattern Assessment in Patients with Severe Aortic Stenosis Via the Chou's 5-Steps Rule

Paravalvular leak prediction after transcatheter aortic valve replacement with self-expandable prosthesis based on quantitative aortic calcification analysis

Background

Paravalvular leak (PVL) is one of the most common complications of transcatheter aortic valve replacement (TAVR) and affects short- and long-term outcomes. The aim of this study was to identify the computed tomography (CT) imaging biomarkers that allow PVL after TAVR to be predicted.

Methods

Patients were included who had severe aortic valve stenosis, had undergone TAVR with a self-expanding valve, and had undergone a pre-procedural CT scan. Data on baseline characteristics, procedural and long-term outcomes were collected retrospectively. We used MATLAB software with a self-developed algorithm for CT scan analysis and found parameters that quantified aortic valve calcifications (AVC) in detail.

Results

Fifty patients were included. The identified CT-derived parameters included AVC size, volume, thickness and density, as well as calcium radial distribution. The volume of the largest calcium block, calcium perimeter and calcium size (assessed by Feret's diameter) showed a strong association with PVL occurrence after TAVR (P=0.012, P=0.001 and P=0.045, respectively). The prognostic model showed that a 10 mm² increase in the local AVC amount in each valve section was associated with a 9.8% (95% CI: 2-18%; P=0.019) increase in the risk of PVL occurrence in the corresponding area after TAVR. ROC analysis revealed that the cut-off point of the AVC area was 96.5 mm² in the polar coordinate system presentation. Kaplan-Meier curves showed worse PVL-free survival in patients with more than 96.5 mm² of calcium area (P=0.013; log-rank).

Conclusions

Quantitative AVC assessment for PVL prediction may play an important role in screening before TAVR. In future, the use of quantitative AVC assessment as an imaging biomarker in TAVR candidates and the creation and extension of an online database containing quantitative AVC parameters may help to identify high PVL risk patients.

Some illuminating remarks on molecular genetics and genomics as well as drug development

Facing the explosive growth of biological sequences unearthed in the post-genomic age, one of the most important but also most difficult problems in computational biology is how to express a biological sequence with a discrete model or a vector, but still keep it with considerable sequence-order information or its special pattern. To deal with such a challenging problem, the ideas of "pseudo amino acid components" and "pseudo K-tuple nucleotide composition" have been proposed. The ideas and their approaches have further stimulated the birth for "distorted key theory", "wenxing diagram", and substantially strengthening the power in treating the multi-label systems, as well as the establishment of the famous "5-steps rule". All these logic developments are quite natural that are very useful not only for theoretical scientists but also for experimental scientists in conducting genetics/genomics analysis and drug development. Presented in this review paper are also their future perspectives; i.e., their impacts will become even more significant and propounding.