You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


1. Introduction {#sec1}
===============

Transcatheter aortic valve implantation (TAVI) is a well-established first-line therapy for severe symptomatic aortic stenosis (AS) patients who are at intermediate or higher surgical risk \[[@B1], [@B2]\]. Paravalvular leak (PVL) is common after TAVI and has been linked with worse survival \[[@B3]\]. Preprocedural multislice computed tomography (MSCT) is considered the most reliable method for measuring aortic root parameters in patients undergoing TAVI and has shown to be more advantageous in decreasing rates of PVL compared to echocardiography and, hence, has become the preferred imaging method for TAVI patients \[[@B4]\]. Some risk factors for developing PVL after TAVI have been identified \[[@B3], [@B5]--[@B8]\]. However, there is currently no integrated method which includes all parameters that may predict PVL after TAVI. We sought to conduct the present study to investigate the determinants and outcome of PVL after TAVI and to evaluate the role of aortic valve calcification (AVC) distribution in predicting PVL.

2. Materials and Methods {#sec2}
========================

2.1. Patient Population {#sec2.1}
-----------------------

Data from 270 consecutive patients with severe symptomatic AS who underwent TAVI at west China hospital of Sichuan University, Sichuan, China, from April 2012 to November 2017 were retrospectively analyzed. Of these, 3 patients had preexisting surgical valve and 11 patients had no prostheses implantation due to potential risk of coronary occlusion or annulus rupture found during the procedure of predilatation. Thus, 256 patients were finally included. All included patients have undergone MSCT and transesophageal or transthoracic echocardiography (TEE, TTE) before TAVI for prosthesis sizing and selection of vascular access and TEE or TTE during the procedure for PVL assessment. The baseline surgical operative risk was calculated using the Surgeons Risk Score for Prediction of Mortality (STS score) \[[@B9]\].

Based on the severity of PVL after TAVI, patients were divided into two groups: ≥mild PVL group or \<mild PVL group. In patients with ≥mild PVL, AVC distribution and PVL jet location were analyzed. Then we calculated the matching rates of AVC distribution and PVL jet for each aortic root region (annulus, body of leaflet, and tip of leaflet) first for all patients and then for each tricuspid aortic valve (TAV), bicuspid aortic valve (BAV) type I, and BAV type 0 subgroups. Finally, matching rates of cusps calcifications and commissures calcifications with PVL jet were analyzed. The study was approved by the institutional review board, and all patients provided written signed consent.

2.2. MSCT Acquisition and Image Analysis {#sec2.2}
----------------------------------------

CT scans were performed using a 64-MSCT scanner (SOMATOM Definition Flash; Siemens Healthineers, Erlangen, Germany). Aortic root measurements were accomplished by analyzing pre-TAVI MSCT with OsiriX (OsiriX Foundation, Geneva, Switzerland) ([Figure 1](#fig1){ref-type="fig"}). The aortic valve annulus was defined as a plane including the lowest basal attachment points of the aortic valve leaflets in the left ventricular outflow tract (LVOT). MSCT measurements included minimum and maximum annular diameters, area, and circumference, as well as LVOT area. The mean annular diameter was calculated by taking the average of the minimum and maximum diameters. Measurements were performed using midsystolic MSCT images ([Figure 2](#fig2){ref-type="fig"}). The area of a completely expanded transcatheter heart valve (THV) was calculated by the following formula: (3.14 × radius^2^ measured in mm^2^). On this basis, prosthesis mismatch was calculated using the method described by Buzzatti et al. \[[@B10]\] as follows: (\[mean diameter of the prosthesis/mean annulus diameter\] × 100). Annular cover index was calculated as follows: (\[THV area × area of the annulus/THV area\] × 100). Annular ellipticity was calculated as (\[maximum annular diameter − minimum annular diameter/maximum annular diameter\] × 100) and LVOT nontubularity as (\[annular area − LVOT area/annular area\] × 100) using a method introduced by Condado et al. \[[@B11]\].

2.3. Analysis of Aortic Valve Calcification {#sec2.3}
-------------------------------------------

The analysis of calcification was performed using diastolic MSCT images at 75% of the RR interval using calcium volume scoring system \[[@B5], [@B12]\]. An adjusted threshold of 550 Hounsfield units was used for calcification quantification for most patients \[[@B5], [@B7]\]. Calcium quantification was performed by a cardiologist experienced in cardiovascular imaging. The aortic root was divided into the following regions in the craniocaudal axis along the long axis of the aortic valve/LVOT: annulus (from 3 mm above to 2 mm below the annular plane) and leaflet (from 3 mm above the annular plane to the superior edge of leaflets). Then each leaflet was visually divided into three-thirds; one-third near the edge of leaflet was considered "tip of leaflet" and the remaining two-thirds were considered "body of leaflet" ([Figure 3](#fig3){ref-type="fig"}). Each anatomical region was divided into 4 or 6 sectors to correspond to the leaflets and commissures distribution in BAV and TAV patients, respectively. The total AVC volume was calculated; then AVC distribution was analyzed for each region.

2.4. PVL Assessment {#sec2.4}
-------------------

Evaluation of PVL severity was performed at the end of the procedure. PVL was considered positive if it was present after completing all interventions. Echocardiographic assessment was performed by a board-certified echocardiographer experienced in TAVI imaging. PVL was classified using color Doppler imaging into trace, mild, moderate, or severe as suggested by the Valve Academic Research Consortium-2 (VARC-2) consensus recommendations \[[@B13]\]. The location of the PVL jets was determined retrospectively by a board-certified echocardiographer and was blinded to the results of AVC volume and distribution analysis.

2.5. The Procedure {#sec2.5}
------------------

Implanted prostheses included the self-expandable prosthesis (the first-generation CoreValve, Medtronic, Inc., Minneapolis, Minnesota. Venus A-Valve, Venus MedTech, Inc., Hangzhou, China. VitaFlow Valve, MicroPort, Inc., Shanghai, China; and Taurus One Valve; Peijia, Inc., Suzhou, China), the mechanical-expandable prosthesis (Lotus Valve; Boston Scientific, Inc., Natick, MA, USA), and Edwards SAPIEN XT or SAPIEN3 valves (Edwards LifeSciences, Inc., Irvine, California, USA) ([Figure 4](#fig4){ref-type="fig"}). Prosthesis selection depended on prosthesis availability. Based on the agreement of the heart team, all the patients underwent TAVI using the transfemoral access, except for two patients in whom the transsubclavian and transcarotid approach were used due to unfavorable femoral anatomy. Valve sizing was based on the consensus of a multidisciplinary heart team that includes senior interventional cardiologists, cardiovascular surgeons, and imaging specialists. The need for predilatation was decided by the heart team. Similarly, the choice of postdilatation was at the discretion of the heart team and was generally based on the postdeployment echocardiographic imaging showing significant PVL.

2.6. Statistical Analyses {#sec2.6}
-------------------------

Mean ± standard deviation was used for continuous variables and numbers with percentages for categorical variables. Comparisons between groups were performed with the Chi-square test for categorical variables and Student\'s *t*-test or Wilcoxon rank-sum test for continuous variables as appropriate. Exploratory multivariable analysis by logistic regression was performed to evaluate the predictors of ≥mild PVL after TAVI. The final model included variables associated with univariate analysis (all variables with a *p*value \< 0.1). Statistical analysis was performed using the Statistical Package for Social Sciences, version 21.0, for Windows (SPSS. Chicago, Illinois). All reported *p*values are two-sided and were considered statistically significant if \<0.05.

3. Results {#sec3}
==========

3.1. Baseline Characteristics {#sec3.1}
-----------------------------

Overall, median age was 74 ± 6 years old, and 43.4% were females. The mean STS score was 8 ± 4.35 and NYHA ≥ III in 234 (91.4%) patients. At baseline, the median left ventricular ejection fraction was 54.7 ± 15%, and the mean transvalvular peak velocity was 5 m/s. We observed that those with higher transvalvular peak velocity were associated with PVL after TAVI. The mean pressure gradient dropped from 64 mmHg to 13.7 mmHg immediately after the procedure. Before the procedure, 60 (23.4%) patients had moderate to severe aortic regurgitation, and 43 (16.8%) had moderate to severe mitral regurgitation. Baseline characteristics of patients are shown in [Table 1](#tab1){ref-type="table"}.

3.2. Procedural and MSCT Characteristics {#sec3.2}
----------------------------------------

Seventy-five patients (29.3%) had ≥mild PVL after the procedure. Of them, 15 patients had moderate PVL and PVL was severe in 2 patients. Among included patients, 213 (83.2%) patients received self-expandable prostheses, 32 (12.5%) received mechanically expandable prostheses, and the remaining 11 (4.3%) patients received balloon-expandable prostheses ([Figure 4](#fig4){ref-type="fig"}). By univariate analysis, neither prosthesis type nor size was significantly associated with the occurrence of ≥PVL. MSCT-derived maximum, minimum, mean annular diameters, and annulus area were 27.1 ± 3.14 mm, 21.3 ± 2.75 mm, 24.2 ± 2.63 mm, and 462.7 ± 101.2 mm^2^, respectively. All these annulus parameters were significantly associated with PVL. Interestingly, annular ellipticity, annular area cover index, prosthesis-mismatch index, and LVOT nontubularity were not associated with PVL. The mean total AVC volume was 798 ± 594.5 mm^3^. The overall analysis indicates that AVC volume was strongly associated with PVL ([Table 2](#tab2){ref-type="table"}).

3.3. Multivariate Analysis {#sec3.3}
--------------------------

By multivariate analysis, calcification volume (OR: 1.001 \[95% CI: 1.000, 1.002\] *p*=0.01) and prosthesis type (self-expandable versus non-self-expandable) (OR: 3.489 \[95% CI: 1.096, 11.105\] *p*=0.034) were found to be independent predictors of ≥mild PVL after TAVI, although prosthesis type was not associated with PVL by univariate analysis. Multivariate analysis is shown in [Table 3](#tab3){ref-type="table"}.

3.4. Calcification Distribution and PVL Jet Location {#sec3.4}
----------------------------------------------------

An example illustrating PVL jet location on postprocedural TEE short axes view matching with the location of aortic valve calcification (AVC) on MSCT is shown in [Figure 5](#fig5){ref-type="fig"}. PVL jet location matched, in varying proportions, with calcification at all regions of the aortic root, and the highest matching rate was with calcification at body of leaflets compared to calcification at the annulus or tip of leaflets as shown in [Figure 6](#fig6){ref-type="fig"}. Matching rates of PVL jet were higher with cusp calcifications than commissure calcifications, particularly in TAV subgroup ([Figure 7](#fig7){ref-type="fig"}).

3.5. Outcome {#sec3.5}
------------

At discharge, left ventricular ejection fraction was higher in patients with \<mild PVL compared to those with ≥PVL, but no difference was observed in transvalvular valve peak velocity or mean pressure gradient. No statically significant difference in the rate of all-cause and cardiovascular mortality between patients with ≥mild PVL and those with a lesser degree of PVL at 30-day, 6-month, and 1-year follow-up ([Table 4](#tab4){ref-type="table"}).

4. Discussion {#sec4}
=============

The main findings of the current study include the following. (1) Risk factors for ≥ mild PVL include AVC volume, larger annulus dimensions, and pre-TAVI transvalvular peak velocity. AVC volume and prosthesis type (self-expandable versus non-self-expandable) were independent predictors of ≥mild PVL. (2) PVL jet matched, in varying proportion, with calcification at all aortic root regions, and the highest matching rate was with calcification at body of leaflets. Moreover, matching rates of PVL jet were higher with cusp calcifications than commissure calcifications, particularly in TAV subgroup. (3) No association between ≥ mild PVL and all-cause and cardiovascular mortality at 1-year follow-up.

4.1. Incidence of PVL after TAVI {#sec4.1}
--------------------------------

Despite improvements in TAVI technology, PVL after TAVI remains commonly reported with variable frequencies \[[@B3], [@B14]\]. This variability was assumed to be due to differences in the imaging modalities used in different centers, evaluation timing, the grading system, and variability in prostheses type \[[@B15]\]. In the current study, 29.3% of patients had ≥mild PVL, which is consistent with several reports \[[@B8], [@B10], [@B16]\].

4.2. Risk Factors for PVL {#sec4.2}
-------------------------

Smaller annulus size has been reported to be protective against the presence of PVL, explained by the better congruence between the small annulus and THV. However, the prostheses might be undersized in patients with larger aortic annuli \[[@B17]\]. Results from REVIVAL trial showed that larger aortic annulus was a predictor of post-TAVI central aortic regurgitation rather than PVL due to the requirement of larger postdilatation balloon leading to possible leaflet distortion \[[@B18]\]. Conversely, some publications have reported that larger annulus dimensions were not predictors of PVL \[[@B7], [@B8]\]. In the present study, larger annulus dimensions were significantly associated with ≥mild PVL. As well as that, a meta-analysis study found that undersizing of the prosthesis relative to the annulus size was the main cause of PVL \[[@B3]\]. However, most of the studies included in their meta-analysis measured aortic annulus using TEE rather than MSCT, which has been proven to underestimate the annulus size \[[@B4]\]. In the present study, however, no statistically significant correlation was found between these parameters and the incidence of PVL, which can be explained by the proper oversizing in our study, as the prosthesis size was always greater than that of the annulus ([Table 2](#tab2){ref-type="table"}). Therefore, these results indicate that an appropriate oversizing based on accurate MSCT-derived annulus measurement is crucial to minimize the incidence of PVL after TAVI. Wong et al. \[[@B19]\] reported that elliptical aortic annulus as a predictor of PVL after TAVI. However, several other studies found no correlation, which is consistent with our results \[[@B3], [@B8]\].

4.3. Calcification Volume and Distribution {#sec4.3}
------------------------------------------

The present study evaluated both severity of PVL and PVL location in relation to the distribution of aortic valve calcification. We found that patients with ≥mild PVL had significantly greater calcification in all regions of the aortic valve. Similarly, previous studies have shown that aortic root calcification predicts significant PVL after TAVI \[[@B5], [@B7]\]. Importantly, several studies suggested that the distribution of calcification on the aortic root is more important than the calcification volume in determining PVL after TAVI \[[@B5]--[@B7], [@B20]\]. However, results of these studies varied; Koos et al. \[[@B6]\] showed that calcium distribution asymmetry had no role in predicting the severity of PVL after TAVI. Ewe et al. \[[@B20]\] found that calcification at the aortic wall near the annulus level was of more importance compared to leaflet calcification in predicting PVL. Marwan et al. \[[@B7]\] reported that annulus calcification was an important determinant in predicting PVL. In addition, they reported no difference in commissure calcification between patients with and without PVL. Khalique et al. \[[@B5]\] used similar methodology like the one we used for classifying the calcification of aortic valve complex and confirmed that both leaflet and annulusLVOT calcification predict significant PVL. The current study found that calcification at all regions of the aortic valve may predict the presence of PVL at the corresponding location. However, calcifications at the body of leaflets were found to be the main determinant in predicting PVL after TAVI. Annulus calcifications and calcifications at the tip of leaflets were less important in predicting PVL. Interestingly, cusp calcifications were found to be more important than commissure calcification in predicting PVL, particularly in TAV and BAV type 0 patients. We believe that leaflet calcification, as suggested by our results and results of a study by Khalique et al. is as important as annular and LVOT calcifications in predicting PVL \[[@B5]\]. The underlying mechanism may be leaflet and annulus/LVOT calcifications causing prosthesis underexpansion and incomplete contact between the prosthesis and its landing zone. In addition, our results suggested that, compared to cusp calcification, commissural calcification is less important in predicting PVL. This finding as suggested by previous report \[[@B5]\] could probably be explained by the fact that contrary to cusp calcifications, commissure calcifications are easier to be pushed outward during the predilatation and deployment procedure and, hence, do not affect the sealing of the prosthesis to its landing zone. We compared the number of patients who underwent predilatation and found that 95% of BAV patients underwent predilatation, in contrast to TAV patients where only 71% (*p* \< 0.001) were predilated which may further explain the lower contributing effect of commissure/raphe calcification, in BAV patients, to the development of PVL.

Operators should be cautious when dealing with heavily calcified aortic valves, especially calcifications on areas found to predict PVL after TAVI. In such patients, significant PVL should be anticipated and hopefully prevented by a wise selection of the prosthesis type and proper predilatation to help spread calcified leaflets and preparation for balloon postdilatation and even implantation of a second valve in case of significant PVL.

4.4. Prosthesis Type {#sec4.4}
--------------------

Widely variable incidence of PVL after TAVI has been observed among patients with both balloon-expandable and self-expandable prostheses. Athappan et al., in their meta-analysis study, found that the incidence of ≥moderate aortic regurgitation after the implantation of self-expandable and balloon-expandable valves was 16% and 9%, respectively \[[@B3]\]. Similarly, a recent study confirmed that aortic regurgitation after TAVI was found to be more frequent in patients with self-expandable prosthesis compared to those with balloon-expandable ones \[[@B21]\]. Conversely, some other studies reported no significant association between prosthesis type and incidence of PVL \[[@B8]\]. In our study, by univariate analysis, prosthesis type had no role in predicting PVL. However, in multivariate analysis, the prosthesis type (self-expandable prosthesis versus non-self-expandable prosthesis) was a predictor of PVL. It should be mentioned that, in the present study, the number of patients who received a self-expandable prosthesis (83%) is significantly greater than those who received another type of prostheses (17%). Hence, it cannot be concluded that a certain prosthesis predicts PVL. Further evaluation of the outcome of different prosthesis types in terms of PVL is warranted using a large and equal number of patients for each prosthesis type.

Yoon et al. found that, in patients with BAV anatomy, new-generation devices were associated with less moderate or severe PVL compared to early-generation devices \[[@B22]\]. Similarly, our results showed that around 40% and 30% of patients who underwent TAVI using CoreValve and Venus A-Valve, respectively, had ≥mild PVL. On the other hand, only less than 25% of those who received new-generation devices had ≥mild PVL after TAVI ([Figure 4](#fig4){ref-type="fig"}). Although new-generation devices have less incidence of PVL and, hence, should be preferred over early-generation ones, nevertheless, mild PVL still occur and minimizing PVL is crucial for better outcome of TAVI, particularly in an intermediate-to-low risk patients.

4.5. Outcome {#sec4.5}
------------

There was no difference in terms of all-cause and cardiovascular mortality at 1-year follow-up. This may be explained by the relatively younger age of included patients (mean age was 74 years) and the relatively short follow-up period.

5. Conclusions {#sec5}
==============

Risk factors for PVL after TAVI include AVC volume, larger annulus dimensions, and pre-TAVI transvalvular peak velocity. AVC volume is an independent predictor of PVL. Body of leaflet calcifications (versus annulus and tip of leaflet) and cusps calcifications (versus commissures) were more important in predicting PVL. There was no association between ≥mild PVL and 30-day, 6-month, or 1-year all-cause and cardiovascular mortality.

6. Limitations {#sec6}
==============

We acknowledge that our study has some limitations. First, this is a retrospective study at one center; we need to be cautious when extrapolating the present findings to other cohorts. Second, most of the included patients underwent TAVI using self-expandable prosthesis. Hence, the study is insufficient to assess the impact of prosthesis type on the incidence of PVL. Third, a relatively short follow-up period makes it hard to estimate mortality, and longer follow-up is warranted. Finally, the number of patients in whom the correlation between calcification distribution and PVL was analyzed was relatively small. This will need to be explored in a larger population.

This research was supported by the National Natural Science Foundation of China (Grants nos. 81970325 and 81600347, Beijing, China) and the Supporting Project of Department of Science and Technology of Sichuan Province (Grants nos. 2017TD0004 and 2017SZ0054, Sichuan, China). The funding sources were not involved in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication.

Data Availability
=================

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest
=====================

The authors declare that they have no conflicts of interest.

Authors\' Contributions
=======================

Abdullah Hagar and Yijian Li contributed equally to this work.

![Multiplanar reconstruction used for the assessment of aortic root. (a) Single oblique sagittal view; (b) coronal view; (c) double oblique transverse view.](JITC2020-8249497.001){#fig1}

![Aortic annular measurements on the MSCT. (a) Maximum and minimum annular diameters; (b) annular area; (c) annular circumference.](JITC2020-8249497.002){#fig2}

![Anatomical regions of the aortic root. (a) Regions of the aortic valve in the craniocaudal axis along the long axis of the aortic valve/LVOT: annulus (from 3 mm above to 2 mm below the annular plane) and leaflet (from 3 mm above the annular plane to the superior edge of leaflets); (b) parts of aortic valve leaflet.](JITC2020-8249497.003){#fig3}

![Degree of PVL for each prosthesis type.](JITC2020-8249497.004){#fig4}

![Example showing paravalvular leak jet location on echocardiography matching with the location of AVC on MSCT (image of the MSCT is rotated to be easily compared with the corresponding view of echocardiography). LC: left coronary cusp; RC: right coronary cusp; NC: noncoronary cusp.](JITC2020-8249497.005){#fig5}

![Matching rates of calcification distribution and PVL jet location based on the site of calcification on the aortic root. PVL+, Cal+: paravalvular leak present at the specific location and calcification present at the corresponding location; PVL+, Cal−: paravalvular leak present at a specific location without calcification at the corresponding location; BAV: bicuspid aortic valve; TAV: tricuspid aortic valve.](JITC2020-8249497.006){#fig6}

![Matching rates of calcification distribution and PVL jet location (Cusps versus commissures). PVL+, Cal+: paravalvular leak present at the specific location and calcification present at the corresponding location; PVL+, Cal−: paravalvular leak present at a specific location without calcification at the corresponding location; BAV: bicuspid aortic valve; TAV: tricuspid aortic valve.](JITC2020-8249497.007){#fig7}

###### 

Baseline characteristics of patients based on the severity of PVL.

  Clinical characteristics                       All (*n* = 256)   ≥mild PVL (*n* = 75)   \<mild PVL (*n* = 181)   *p* value
  ---------------------------------------------- ----------------- ---------------------- ------------------------ -----------
  Age (year)                                     74 ± 6            73.68 ± 5.89           74.17 ± 6.19             0.56
  Female gender                                  111 (43.4%)       29 (38.7%)             82 (45.3%)               0.33
  Body mass index                                22.12 ± 3.44      21.88 ± 3.30           22.35 ± 3.59             0.33
  STS SCORE                                      8.01 ± 4.4        8.1 ± 4.01             7.93 ± 4.78              0.80
  History of dyspnoea                            230 (89.8%)       65 (86.7%)             165 (91.2%)              0.27
  History of chest pain                          74 (28.9%)        19 (25.3%)             55 (30.4%)               0.42
  History of syncope                             41 (16.4%)        13 (17.3%)             28 (15.5%)               0.71
  Hypertension                                   114 (44.5%)       37 (49.3%)             77 (42.5%)               0.32
  Diabetes mellitus                              46 (17.9%)        15 (20%)               31 (17.1%)               0.59
  Chronic obstructive pulmonary disease          162 (63.2%)       50 (66.7%)             112 (61.9%)              0.47
  Coronary artery disease                        110 (42.9%)       32 (42.7%)             78 (43.1%)               0.95
  Previous myocardial infarction                 5 (1.9%)          2 (2.7%)               3 (1.7%)                 0.61
  Peripheral vascular disease                    143 (55.8%)       35 (46.7%)             108 (59.7%)              0.057
  Prior stroke or transient ischemic attack      34 (13.2%)        8 (10.7%)              26 (14.4%)               0.43
  Chronic kidney disease                         36 (14.0%)        13 (17.3%)             23 (12.7%)               0.33
  Atrial fibrillation                            37 (14.4%)        9 (12%)                28 (15.5%)               0.47
  NYHA                                                                                                             0.88
   Class I                                       1 (0.4%)          0                      1 (1.6%)                  
   Class II                                      21 (8.2%)         6 (8%)                 15 (8.3%)                 
   Class III                                     113 (44.1%)       35 (46.7%)             78 (43.1%)                
   Class IV                                      121 (47.2%)       34 (45.3%)             87 (48.1%)                
   NYHA III/IV                                   234 (91.4%)       69 (92%)               165 (91.2%)              0.82
  Echocardiographic factors                                                                                         
   Left ventricular ejection fraction (%)        54.7 ± 15         52.93 ± 14.98          56.48 ± 15.12            0.088
   Aortic valve peak velocity (m/s)              5 ± 0.73          5.15 ± 0.75            4.94 ± 0.71              0.035
   Aortic valve mean pressure gradient (mm Hg)   64.32 ± 19.3      66.56 ± 20.57          62.08 ± 17.97            0.084
   Aortic regurgitation (moderate to severe)     60 (23.4%)        24 (26.3%)             36 (19.9%)               0.19
   Mitral regurgitation (moderate to severe)     43 (16.8%)        17 (19.5%)             26 (16%)                 0.42

Data are presented as mean ± SD or percentages. NYHA: New York Heart Association; STS score: Society of Thoracic Surgeon score.

###### 

Procedural and MSCT characteristics of patients based on the severity of PVL.

  ----------------------------------------------------------------------------------------------------------------------
  Procedural factors                         All (*n* = 256)   ≥mild PVL (*n* = 75)   \<mild PVL (*n* = 181)   *p*\
                                                                                                               value
  ------------------------------------------ ----------------- ---------------------- ------------------------ ---------
  Annular maximum diameter (mm)              27.1 ± 3.14       27.67 ± 3.19           26.52 ± 3.10             0.01

  Annular minimum diameter (mm)              21.3 ± 2.75       21.67 ± 2.71           20.85 ± 2.80             0.03

  Annular mean diameter (mm)                 24.2 ± 2.63       24.67 ± 2.66           23.69 ± 2.59             0.01

  Annular area (mm^2^)                       462.7 ± 101.2     481.09 ± 103.24        444.38 ± 99.21           0.001

  Annular ellipticity                        21.17 ± 8.9       21.33 ± 8.46           21.02 ± 9.47             0.81

  Diameter derived prosthesis mismatch (%)   12.8 ± 9.9        12.09 ± 10.46          13.62 ± 9.26             0.25

  Prosthesis/mean annulus diameter ratio     1.13 ± 0.10       1.12 ± 0.10            1.14 ± 0.09              0.25

  Calcification volume (mm^3^)               798 ± 594.5       991.64 ± 709.94        604.37 ± 479.05          \<0.001

  Presence of predilatation                                    150 (82.9%)            66 (88%)                 0.30

  Area cover index                           19.9 ± 14.6       18.66 ± 15.52          21.14 ± 13.66            0.21

  Depth of implantation (mm)                 6.8 ± 4.43        7.21 ± 4.47            6.40 ± 4.39              0.27

  LVOT nontubularity                         −5.3 ± 18.46      −7.15 ± 18.59          −3.46 ± 18.33            0.15

  Second valve implantation                  28 (10.9%)        7 (9.3%)               21 (11.6%)               0.59

  Postdilatation                             115 (44.9%)       45 (60%)               70 (38.7%)               0.002

  Size of the prosthesis (mm)                                                                                  0.23

   23                                        46 (19.9%)        9 (12.0%)              37 (20.4%)                

   26                                        109 (42.6%)       30 (40%)               79 (43.6%)                

   29                                        74 (28.9%)        26 (34.7%)             48 (26.5%)                

   31/32                                     27 (10.5%)        10 (13.3%)             17 (9.9%)                 

  Prosthesis type                                                                                              0.054

   Self-expandable                           213 (83.2%)       69 (91.9%)             144 (79.6%)               

   Mechanically expandable                   32 (12.5%)        4 (5.4%)               28 (15.5%)                

   Balloon expandable                        11 (4.3%)         2 (2.7%)               9 (5.0%)                  

   Type of native valve                                                                                        0.61

   Tricuspid                                 114 (44.5%)       31 (41.3%)             83 (45.9%)                

   Bicuspid type I                           58 (22.6%)        16 (21.3%)             42 (23.2%)                

   Bicuspid type 0                           84 (32.8%)        28 (37.3%)             56 (30.9%)                
  ----------------------------------------------------------------------------------------------------------------------

Data are presented as mean ± SD or percentages. LVOT: left ventricular outflow tract.

###### 

Multiple regression analysis.

  ----------------------------------------------------------------------------------------------
  Variable                                                       OR (95% CI)             *p*\
                                                                                         value
  -------------------------------------------------------------- ----------------------- -------
  Peripheral vascular disease                                    0.644 (0.335--1.237)    0.18

  Calcification volume (mm^3^)                                   1.001 (1.000--1.002)    0.010

  Prosthesis type (self-expandable versus non-self-expandable)   3.489 (1.096--11.105)   0.034

  Left ventricular ejection fraction (%)                         0.981 (0.959--1.004)    0.097

  Transvalvular peak velocity (m/s)                              1.826 (0.334--9.985)    0.488

  Transvalvular mean pressure gradient (mmHg)                    0.991 (0.928--1.058)    0.789

  Annular maximum diameter (mm)                                  1.105 (0.835--1.461)    0.486

  Annular minimum diameter (mm)                                  1.118 (0.844--1.483)    0.437

  Annular mean diameter (mm)                                     1.251 (0.712--2.199)    0.437

  Annular area (mm^2^)                                           0.995 (0.982--1.009)    0.50
  ----------------------------------------------------------------------------------------------

###### 

Follow-up outcome data.

  ----------------------------------------------------------------------------------------------------------------
  At discharge                           All (*n* = 256)   ≥mild PVL (*n* = 75)   \<mild PVL (*n* = 181)   *p*\
                                                                                                           value
  -------------------------------------- ----------------- ---------------------- ------------------------ -------
  Transvalvular peak velocity            2.44 ± 1.1        2.39 ± 0.52            2.49 ± 1.59              0.61

  Transvalvular mean pressure gradient   13.7 ± 5.9        13.85 ± 5.82           13.49 ± 6.13             0.66

  Left ventricular ejection fraction     55.87 ± 12.1      53.67 ± 12.17          58.07 ± 12.04            0.008

  30 days                                                                                                   

   All-cause morality                                      5 (6.7%)               5 (2.8%)                 0.16

   Cardiac-related mortality                               4 (5.3%)               3 (1.7%)                 0.19

  6-months                                                                                                  

   All-cause mortality                                     8 (10.7%)              8 (4.4%)                 0.08

   Cardiac-related mortality                               5 (6.7%)               4 (2.2%)                 0.13

  1 year                                                                                                    

   All-cause mortality                                     8 (10.7%)              9 (5.0%)                 0.11

   Cardiac-related mortality                               5 (6.7%)               5 (2.8%)                 0.16
  ----------------------------------------------------------------------------------------------------------------

Data are presented as mean ± SD or percentages.

[^1]: Guest Editor: Mohamad Alkhouli