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Online Supplemental Appendix

The SENTINEL Trial Site and Investigator ListingCedars-Sinai Medical Center

PI: Raj MakkarSub-I: Hasanian Al-Jilaihawi

Los Angeles, CA United States

Cleveland Clinic PI: Samir Kapadia

Sub-I: Amar Krishnaswamy Sub-I: E. Murat Tuzcu Sub-I: Stephanie Mick

Cleveland, OH United States

Columbia University Medical Center PI: Susheel KodaliSub-I: Tamin Nazif

New York, NY United States

Emory University Hospital Midtown PI: Vinod Thourani

Sub-I: Vasilis Babaliaros Sub-I: Chandan Devireddy Sub-I: Kreton Mavromatis

Atlanta, GAUnited States

MedStar Washington Hospital Center PI: Ron Waksman

Sub-I: Lowell Satler Sub-I: Augusto Pichard

Washington, DC United States

University of Pennsylvania PI: Wilson Szeto

Sub-I: Saif AnwaruddinSub-I: Prashanth Vallabhajosyula

Sub-I: Jay GiriSub-I: Howard Herrmann

Philadelphia, PA United States

Barnes - Jewish Hospital PI: Alan Zajarias

Sub-I: John Lasala St. Louis, MO United States

Henry Ford Health System PI: Adam Greenbaum Sub-I: William O’Neill

Sub-I: Marvin Eng Detroit, MI

United States

Morton Plant Hospital PI: Joshua Rovin Sub-I: Lang Lin

Sub-I: Douglas Spriggs Clearwater, FL United States

Weill Cornell Medical Center PI: Shing-Chiu Wong

Sub-I: Geoffrey Bergman Sub-I: Arash Salemi

New York, NY United States

The University of Texas - Health Science Center PI: Richard SmallingSub-I: Biswajit Kar

Sub-I: Pranav Loyalka Houston, TX

United States

University of Virginia Health System PI: D. Scott Lim

Sub-I: Michael Ragosta Charlottesville, VA

United States

University of Washington PI: Mark Reisman

Sub-I: James McCabe Sub-I: Creighton Don

Seattle, WAUnited States

Icahn School of Medicine at Mount Sinai PI: Samin Sharma

Sub-I: Annapoorna Kini Sub-I: George Dangas

New York, NYUnited States

Sentara Norfolk General Hospital PI: Paul Mahoney

Norfolk, VA United States

St. Thomas Hospital PI: Andrew Morse

Sub-I: Mark Stankewicz Sub-I: Evelio Rodriguez

Nashville, TNUnited States

Herzzentrum Leipzig GmbH -Universitätsklinik PI: Axel Linke

Sub-I: Norman Mangner Sub-I: Felix Woitek

LeipzigGermany

Asklepios Klinik St. Georg PI: Christian Frerker

HamburgGermany

St. Luke's Hospital PI: David Cohen Kansas City, MO

United States

APPENDIX 1: MRI ACQUISITION AND ANALYSIS METHODOLOGY

STUDY PROCEDURES

Magnetic Resonance Imaging

Brain MRI assessments were performed at baseline, 2-7 days and 30 days post procedure. MRI scans were obtained

according to a protocol provided by the MRI reading center (Buffalo Neuroimaging Analysis Center, Buffalo, NY,

USA) that also performed all sequential co-registration of MRI scans in a blinded manner. MR images at each site

were acquired only on a 3 Tesla certified and validated system at 0, 2-7 and 30 days. Diffusion weighted images

(DWI) were acquired with a 2D echo planar sequence with one b=0 image and 3 orthogonal diffusion directions

with b=1000 s/mm.1 Additional parameters were: repetition time (TR) = 13000ms, echo time (TE) = 100ms, slice

thickness = 3mm (no gap), acquisition matrix 204 x 156, final voxel size = 1.25mm x 1.25mm x 3.0mm. The DWI

images were required at baseline and 2-7 days post procedure on all evaluable imaging cohort patients. Fluid

attenuated inversion recovery (FLAIR) images were acquired with a 2D spin echo inversion recovery sequence with

an inversion time (TI) of 2580ms. Additional parameters were: TR = 9730ms, TE=92ms, slice thickness = 2mm (no

gap), acquisition matrix 256 x 186, final voxel size = 0.94mm x 1.17mm x 2.0mm. The FLAIR images were

required at baseline and 30 days post procedure on all evaluable imaging cohort patients. High resolution T1-

weighted images (hires-T1) were acquired with an MP-RAGE sequence. Additional parameters were: TR = 1690ms,

TE=2.57ms, flip angle (FA) = 12, TI=1100ms, slice thickness = 1.5mm (no gap), acquisition matrix 256 x 224, final

voxel size = 1.00mm x 1.00mm x 1.5mm. Finally, either a manufacturer-based dual-echo GRE sequence was used to

acquire B0 field maps (voxel size = 4.00mm x 4.00mm x 5.00mm), or the DWI images were acquired with two

different phase encoding directions. Minor site-specific deviations were allowed to accommodate individual scanner

capabilities, provided they were approved by MR physicists at the reading center and were acquired consistently

within the site.

DWI acquisitions are subject to substantial artifacts, including eddy current distortions, susceptibility-induced

warping, and signal dropout. Although these do not have a substantial impact on clinical assessment of large lesions

associated with stroke or transient ischemic attack (TIA), they are quite large relative to the small embolic lesions

resulting from the TAVI procedure – distortions may easily be on the order of 1cm, while lesions may be as small as

a few mm. Therefore, a number of pre-processing steps were taken to improve image quality and subsequent

analysis. First, the raw DWI images were corrected for distortions using FMRIB’s FSL FDT library.2 This was

accomplished using either directly acquired fieldmaps or by inferring the field map from paired, phase-reversed

DWI acquisitions.3 Next, the diffusion b=0 (b0) and three corrected b=1000 diffusion-encoded raw images were

combined to create trace and apparent diffusivity coefficient (ADC) images.

Because the lesions are often so small, subtraction imaging was also employed to increase lesion salience.4 Baseline

DWI and FLAIR images were voxel-wise subtracted from follow-up images to produce direct change maps. To

facilitate this subtraction approach, additional pre-processing steps were performed. First, low-frequency spatial

intensity inhomogeneities on FLAIR images were corrected using N3.5 Corrected FLAIR and DWI trace images

were further standardized by applying a piecewise-linear histogram adjustment method to compensate for scan-to-

scan variability in absolute intensity.6 Finally, to facilitate direct longitudinal analysis, all within-subject scans were

co-registered to each subject’s baseline FLAIR image using FLIRT with 6 degrees of freedom.7

Lesions were delineated on corrected and aligned 2-7, and 30 day DWI trace images and 30 day FLAIR images

using a semi-automated contouring technique provided by the JIM software package, with simultaneous reference to

the ADC and subtraction images.8 Using this approach, a trained operator identified lesions individually, and for

each lesion an assistive algorithm delineated a highly reproducible iso-contour at the maximum local gradient. The

operator viewed all images and change maps simultaneously to increase confidence and also coded lesions as new or

persistent.

In addition to lesion counts and volumetry, vascular territory was also assessed using an atlas-based technique. For

this purpose, a vascular territory atlas was manually created in the standard MNI 152 template space9 based on

existing literature,10 and including 28 separate regions. Individual hires-T1 images were used to non-linearly align

this atlas to individual lesion maps. First, individuals’ hires-T1 images were corrected for intensity inhomogeneity

using N3, then aligned to the MNI 152 template using a two-stage process consisting of an initial rigid-body co-

registration followed by composition with a warp field obtained from a non-linear warping technique.11 These

transforms were then inverted, and applied to the original atlas. Lesion number and volume within each vascular

territory were than assessed separately.

APPENDIX 2: NEUROCOGNITIVE TEST BATTERY

The Stroke and Cerebrovascular Disease Division, Department of Neurology, Columbia University Medical Center designed a neurocognitive test battery tailored to the presumed mechanisms of cognitive impairment in the setting of transcatheter aortic-valve implantation (TAVI) and the deployment of this investigational cerebral protection device: perfusion failure in the cerebral circulation and microembolism to the brain. In the former case, cognitive dysfunction is global (bi-hemispheral) in nature, producing deficits in processing speed, executive function, and attention/concentration.12 In the instance of microembolism, these particles are too small to cause the branch occlusions needed for focal neurocognitive syndromes, such as aphasia (left hemisphere) or visual neglect (right hemisphere).13 Rather, there is a diffuse impact that can be either bi-hemispheral or within a single hemisphere across a wide swath of brain territory in the MCA and ACA distribution territories.12 A weakness in prior studies examining the neurocognitive impact of TAVI is the lack of specificity and sensitivity in the tests used. Either measures are too brief (e.g. the Mini Mental State Exam, or MMSE)14 or have not been validated in the setting of diffuse vascular disease (e.g., RBANS),15 raising concern about Type II error. The battery employed in this study, and its variants, have been used in both NIH-funded (NHLBI, NINDS) and industry-sponsored studies, assessing neurocognitive sequelae in end-stage heart failure and LVAD support,16,17 carotid artery disease,18-20 and recently piloted in the PARTNER 2 trial to establish feasibility in the target demographic. All tests are standardized, well- validated instruments in the literature21 and provide extensive normative data permitting baseline analysis and change over time, at 30 and 90 days post implantation. Both efficacy (improvement) and safety (worsening) can be derived from these measures. The MMSE was given only to establish comparability to prior work and to serve as a covariate for baseline mental status. Depression is also a covariate.

Neurocognitive Test Laterality DomainTrails A Bi-hemispheral AttentionTrails B Bi-hemispheral Executive FunctionDigit Span Bi-hemispheral AttentionDigit Symbol Bi-hemispheral Processing SpeedLetter-Number Sequencing Bi-hemispheral Working MemoryControlled Oral Word Association Left Hemisphere Processing SpeedHopkins Verbal Learning Test Left Hemisphere Verbal MemoryRey Complex Figure (Copy) Right Hemisphere Executive FunctionBrief Visual Memory Test Right Hemisphere Visual MemoryMini Mental State Exam --- Mental StatusGeriatric Depression Scale --- DepressionDeveloped by Ronald M. Lazar, PhD, FAHA, FAAN, Professor and Marykay Pavol, PhD, ABCN, Assistant Professor, Doris & Stanley Tananbaum Stroke Center Neurological Institute of New York

Primary Neurocognitive Analysis: Comparison of the change in composite neurocognitive z-scores from Baseline to 30-days post-TAVR between the group in whom the Sentinel device was used and the group that did not receive distal protection, controlling for MMSE and the depression scores.

Composite Score Calculation: A z-score for each domain was calculated based on the normative means and standard deviations for each neurocognitive test supplied by the Neurocognitive Core Lab at Columbia. These norms were stratified by age and education (when possible). When there is more than one test for a given domain (e.g., Trails A and Digit Span for “Attention”), an average was computed from the z-scores comprising the tests for that domain. When there is more than one outcome for a given test (e.g., Total Recall, Delayed Recall and Recognition for “Verbal Memory”), a mean z-score was derived from these outcomes. The composite

neurocognitive z-score for each treatment group is the average z-score from all domains (Attention, Executive Function, Processing Speed, Verbal Memory, Visual Memory). Change scores were calculated (by domain) by subtracting post-surgical exam scores from the baseline scores.

Secondary Neurocognitive Analyses:

1. The interaction of the 30-day composite neurocognitive change score for each treatment group with lesion outcomes from post-TAVR DWI, 30-Day FLAIR, and Baseline FLAIR.

2. Change in neurocognitive composite scores from baseline to 7-days and baseline to 90-days post-TAVR for each treatment group.

3. Baseline composite neurocognitive scores for all study participants to characterize pre-TAVR cognitive function and correlations between these baseline composite scores and baseline FLAIR imaging variables.

4. Change in individual domain scores from Baseline to 7-days, 30-days and 90-days post-TAVR between the group in whom the Sentinel device was used and the group that did not receive distal protection, and the relationships among these domain scores to Baseline FLAIR, post-TAVR DWI and 30-Day FLAIR imaging variables.

APPENDIX 3. MULTIVARIABLE MODEL METHODOLOGY

IntroductionDuring the time of design and initiation of the Sentinel trial, only one TAVR device was commercially available in the U.S. However, several additional TAVR devices became available during the course of the trial and were not stratified in the randomization. In addition, given that this is a first-in-kind study and the data evidenced significant skew and large variance, it was possible that a key baseline that was not pre-identified. This supplement will describe the steps taken to address these concerns in a post-hoc analysis.

Analysis PopulationThe ITT population used in this analysis are all randomized patients that have had a MRI follow-up post TAVR irrespective of whether the follow-up falls within the 2-7 day windows as specified by the protocol.

Normalizing the Outcome: New Volumes in Protected or All Territories Post TAVR ProcedureA log transformation was required to normalize the skewed end point lesion volume data, baseline T2-FLAIR volumes, and baseline HU-850 aortic valve calcification measures. The high frequency of zero values required a correction to the logarithmic transformation. Zero values were set to 5 mm3, the midpoint of zero the MRI detection limit of 10 mm3. In the rest of this supplement, the prefix LNZ will indicate that the data has been transformed as described in this section. Figure S3-1 shows the distribution of the LNZ transformed lesion volumes in protected and all territories.

Figure 3-1: Histogram of New Volumes on the Log Base E scale where zero volumes are set to 5 mm3 on the arithmetic scale and Log Base E[5] on the log scale.

Identifying Key Baseline CovariatesA comprehensive univariate analysis of all baseline characteristics (characteristics that existed before the TAVR procedure) was performed with the baseline characteristic as predictor and the transformed new volumes in protected territories as the outcome. Table S3-1 provides the list of baseline characteristics that were tested.

Table 3-1: List of Baseline Characteristics Used for Univariate Analyses

Characteristic Characteristic CharacteristicAcute Success [Y/N] Distal Vessel Diameter Pre-Dilation [Y/N]

Age Dual Antiplatelet Therapy [Y/N] Procedure Time

Antithrombotic Medications [Y/N] Education Proximal Vessel Diameter

Any Adverse Event(s) during the procedure

Ethnicity Race

Any Diabetes [Y/N] General anesthesia used [Y/N] Region[USA/Germany]

Any other clinically significant infections, allergies, diseases, or surgeries [Y/N]

Heart Rate Respiration

AVA Indexed Height (inches) Rosenhek2

Baseline Geriatric Depression Score History of Atrial Fibrillation [Y/N] Sex [Female/Male]

Baseline Modified Rankin Scale History of Peripheral vascular disease [Y/N]

STS

Baseline Neurocognitive z Overall lnz[baseline volumes] Systole Blood Pressure

BMI lnz[HU_850Volume] TAVR Access

BSA Mean aortic valve area Temperature

Center Modified Allen Result [Normal/Abnormal]]

TIA [Y/N]

Coronary Artery Disease [Y/N] Neurological Deficit [Y/N] Weight (lbs)

CT Result[Normal/Abnormal] NIH Stroke Scale

Currently Taking Medications [Y/N] Peak Aortic Jet Velocity

Diastole Blood Pressure Porcelin Aorta [Y/N]

Dilatation[Yes/No] Post Dilatation

Baseline T2-FLAIR and HU850 Volume measurements were transformed using the LNZ transformation previously described.

Any baseline characteristic with a p-value less than or equal to 0.1 (see Table S3-1 for a list of characteristics tested) were included in a step-wise multi-variable regression model (Table 3-2). The stepwise regression model minimized the AIC and variables entered the model if they had a p- value ≤0.1 and exited the model if the p-value was >0.05. The results of the forward and backward stepwise regression model is shown in Table S3-3. Only LNZ[Baseline T2-FLAIR Volumes] was retained out of all the variables listed in Table 3-2. Only the LNZ[Baseline T2-FLAIR Volumes] Was Predictive of LNZ[New Volumes in Protected Territories].

Table 3-2: Results of Univariate Analysis of Baseline Characteristics predicting transformed New Volumes in Protected Territories

Source Pr > F Source Pr > FBaseline T2-FLAIR Volume Strata (High/Low)

<.0001 Weight (lbs) 0.0568

LNZ[Baseline Lesion Volume] <.0001 Neurological Deficit [Y/N] 0.0594LNZ[Baseline T2-FLAIR Lesion Number]

0.0024 Currently taking medications (Y/N) 0.0632

LNZ[HU_850 Volume] 0.009 Peak Aortic Jet Velocity 0.0636Age 0.0155 STS Risk score 0.0643Dilatation Post TAVR Procedure 0.034 Rosenhek2 0.071Temperature 0.0495 Neurocognitive Verbal Memory Score 0.078BSA 0.0517 History of Percutaneous Coronary Intervention (Y/N) 0.0884

Table 3-3: Results of stepwise regression model

Parameter DF Estimate Standard Error

t Value P-Value

Intercept 1 0.88 1.041516 0.85 0.39.

LNZ[Baseline T2-FLAIR Volumes] 1 0.44 0.116631 3.83 0.0002

Figure 3-2 shows a scatter plot of Post Procedure New Volumes in Protected Territories vs. Baseline T2-FLAIR Volumes on a log base 10 scale (zero values are set to 1). There is a clear relationship between the two. However, there is a great deal of variability. Therefore, to reduce the additional variability that might be added to the model if one uses the continuous data, the baseline data was transformed into a binary variable, volumes above the median of the pooled baseline data (high) or below the median of the baseline data (low).

The covariate assessment was repeated for the new volumes in all territories with the same results.

Figure 3-2: Post Procedure New Volumes in Protected Territories vs. Baseline T2-FLAIR Volumes

Building the model to assess treatment effectsIn the previous sections, baseline T2-FLAIR volume was identified as the key baseline covariate. Further, the randomization was not stratified by TAVR device. Potential differences due to physician selection preferences or design differences may affect the outcome and are of scientific interest in the burgeoning TAVR market; therefore the TAVR Device was added to the model as described below.Yijk ~ Baseline Volumek + TAVRi + Treatmentj + EijkWhere Yijk is either the LNZ[New Volumes in Protected Territories] or LNZ[New Volumes in All Territories]

In order to get stable TAVR device estimates from the model, Medtronic CoreValve which only contributed 7 patients with imaging follow-up, were excluded from the analysis.

ResultsThe p-values in reported in this section represent the adjusted p-values within each ANOVA. The results of the analysis of variance for LNZ[New Volumes in Protected Territories] are in Table 4-3 and Figure 3-1. Once the model is adjusted for baseline T2-FLAIR volumes, TAVR device and the interaction between TAVR device and treatment arm, treatment arm as a main effect is shown to be a significant predictor of the outcome (p=0.025).

It should be noted that there is a significant interaction effect between treatment arm and TAVR device. The overall treatment effect, after adjustment for TAVR device, and the interaction between TAVR and Treatment, is a 42% reduction in post procedure new lesion volume in protected areas [see Supplemental Table 6 following this appendix). However, SAPIEN 3 generated the lowest post procedure new lesion volume (30%–50% lower than the other TAVR devices; see Supplemental Table 6). Therefore, SAPIEN 3 derived the least benefit from the use of the Sentinel device resulting in little to no difference between the treatment arms. This is responsible for the significant interaction effect between the device and treatment. Unfortunately, since the randomization was not stratified by TAVR device, the low new lesion volumes in the S3 TAVR device could be due to a number of reasons including the influence of the use of clinician judgement when matching device to patient.

4

2

0

-2

-4 2 4 6 8 10

This interaction effect may be due to unknown factors associated with clinician judgment as to which device to use at the time of the procedure. Therefore, while the impact of the treatment and its interaction with TAVR device on the outcome can be surmised from this model, the size of the treatment effect requires a more rigorous design that controls for baseline volume and randomizes the TAVR device to the patient.

Table 4-3: Results of Analysis of Variance Using LNZ[New Volumes in Protected Territories]

Effect Numerator DF Denominator DF F Value P-value

BL T2-FLAIR Lesion Volume (High/Low) 1 175 19.08 <0.0001

Valve Type 2 175 1.81 0.1666

Arm 1 175 5.13 0.0248

Valve Type*Arm 2 175 4.24 0.0159

Figure 3-1: Diagnostic Plot for the Analysis of Variance for LNZ[New Volumes in Protected territories]

-

Sensitivity analysesThe analysis of variance for both the LNZ[New Volumes in Protected Territories] and LNZ[New Volumes in All Territories] was repeated with using the LNZ[Baseline Volumes] as a continuous variable. The overall results were the same except the p-value for treatment arm increased to 0.041 and 0.078 for LNZ[New Volumes in Protected Territories] and LNZ[New Volumes in All Territories] respectively.

The analysis of variance was also repeated using the ranks of the New Volumes in Protected or All territories as outcome, essentially making the outcome a uniform distribution. The p-values for the treatment arm was the similar, 0.031 and .066 for LNZ[New Volumes in Protected Territories] and LNZ[New Volumes in All Territories] respectively.

Predicted

Residual by Predicted Plot

Resid

ual

Supplemental Table 1. Baseline characteristics of the Safety Cohort – ITT, evaluable for MACCE

Safety+Test (N=234)

Control (N=111)

Total (N=345) P-value1

Age - years 83.1 [77.2, 87.5] n=234

85.0 [78.5, 89.0] n=111

83.8 [78.0, 87.9] n=345

0.0896

Male 47.4% (111/234) 49.5% (55/111) 48.1% (166/345) 0.7305

BMI 26.4 [23.2, 30.9] n=231

27.1 [24.0, 30.6] n=109

26.9 [23.4, 30.8] n=340

0.6580

STS PROM Score 5.8 [4.0, 8.0] n=234

6.4 [4.5, 8.6] n=111

6.0 [4.2, 8.1] n=345

0.0565

History of Atrial Fibrillation

33.3% (78/234) 31.5% (35/111) 32.8% (113/345) 0.8063

History of PVD 15.4% (36/234) 14.4% (16/111) 15.1% (52/345) 0.8732

History of CAD 52.1% (122/234) 55.0% (61/111) 53.0% (183/345) 0.6456

Previous CABG 17.1% (40/234) 21.6% (24/111) 18.6% (64/345) 0.3737

Previous PCI 16.7% (39/234) 16.2% (18/111) 16.5% (57/345) 1.0000

History of Type II Diabetes

32.5% (76/234) 38.7% (43/111) 34.5% (119/345) 0.2761

Previous Stroke2 5.6% (13/234) 1.8% (2/111) 4.3% (15/345) 0.1577

Previous TIA 8.1% (19/234) 7.2% (8/111) 7.8% (27/345) 0.8336

Heavily Calcified Aorta 2.1% (5/234) 1.8% (2/111) 2.0% (7/345) 1.0000

NYHA Class III/IV 83.5% (192/230) 82.4% (89/108) 83.1% (281/338) 0.9077

Echocardiographic Findings

Valve Area (cm2) 0.7 ± 0.17 (231) 0.7 ± 0.20 (110) 0.7 ± 0.18 (341) 0.9542

Mean aortic valve gradient (mmHg)

41.5 [33.0, 50.0] n=229

41.0 [32.0, 47.0] n=110

41.0 [32.4, 49.0] n=339

0.3564

Note: Continuous data presented as Mean ± SD (n) or Median [IQR] (n). Categorical data presented using % (n/N).1P-values are testing for statistical differences across randomized arms. Continuous data are compared usingANOVA; categorical data are compared using Fisher's exact test.2Defined as neurological deficit lasting more than 24 hours confirmed by imaging.

Supplemental Table 2. Baseline characteristics of patients with and without paired baseline and 2-7 day MRI

Observed MRI (N=189)

Missing MRI (N=51)


Age - years 84.1 [78.5, 87.6] 83.1 [75.4, 89.4] 83.8 [78.1, 88.3] 0.5216(189) (51) (240)

Male 47.6% (90/189) 56.9% (29/51) 49.6% (119/240) 0.2712

BMI 27.0 [23.7, 30.8] 27.7 [24.5, 32.1] 27.0 [23.8, 31.0] 0.2921(186) (50) (236)

STS PROM Score 6.0 [4.4, 8.0] (189) 6.9 [3.8, 9.3] (51) 6.0 [4.2, 8.2] (240) 0.6404

History of Atrial Fibrillation

33.3% (63/189) 29.4% (15/51) 32.5% (78/240) 0.7364

History of PVD 14.8% (28/189) 13.7% (7/51) 14.6% (35/240) 1.0000

History of CAD 53.4% (101/189) 51.0% (26/51) 52.9% (127/240) 0.7550

Previous CABG 23.3% (44/189) 5.9% (3/51) 19.6% (47/240) 0.0048

Previous PCI 15.9% (30/189) 21.6% (11/51) 17.1% (41/240) 0.4012

History of Type II Diabetes

37.6% (71/189) 41.2% (21/51) 38.3% (92/240) 0.6309

Previous Stroke2 3.2% (6/189) 9.8% (5/51) 4.6% (11/240) 0.0590

Previous TIA 7.4% (14/189) 5.9% (3/51) 7.1% (17/240) 1.0000


NYHA Class III/IV 83.7% (154/184) 84.3% (43/51) 83.8% (197/235) 0.2825

Lesion Volume as 7783.6 [2982.1, 10285.9 [4638.0, 7847.9 [3243.2, 0.3318calculated on FLAIR 18224.4] (189) 17038.5] (39) 17854.5] (228)(mm3)


Valve Area (cm2) 0.7 ± 0.18 (187) 0.7 ± 0.18 (50) 0.7 ± 0.18 (237) 0.2974

Mean aortic valve 40.6 [32.0, 47.7] 44.5 [40.0, 56.0] 41.1 [33.5, 49.2] 0.0029gradient (mmHg) (186) (50) (236)

Note: Continuous data presented as Mean ± SD (n) or Median [IQR] (n). Categorical data presented using % (n/N).1P-values are testing for statistical differences across randomized arms. Continuous data are compared usingANOVA for mean or two-sided Wilcoxon text for median; categorical data are compared using Fisher's exact test.2Defined as neurological deficit lasting more than 24 hours confirmed by imaging.

Supplemental Table 3. Baseline and procedural characteristics of patients with paired baseline and 2-7 day MRI – ITT, complete case population

Control Arm (N=98)

Device Arm (N=91)


Age 85.0 [79.7, 89.0] 83.2 [77.8, 87.2] 84.1 [78.5, 87.6] 0.1397(98) (91) (189)

Male 50.0% (49/98) 45.1% (41/91) 47.6% (90/189) 0.5605

BMI 27.0 [23.7, 30.6] 26.8 [23.7, 31.8] 27.0 [23.7, 30.8] 0.5113(96) (90) (186)

STS PROM Score 6.4 [4.6, 8.0] (98) 5.6 [4.2, 8.0] (91) 6.0 [4.4, 8.0] (189) 0.2999History of Atrial Fibrillation

32.7% (32/98) 34.1% (31/91) 33.3% (63/189) 0.8780

History of PVD 16.3% (16/98) 13.2% (12/91) 14.8% (28/189) 0.6826

History of CAD 55.1% (54/98) 51.6% (47/91) 53.4% (101/189) 0.6635

Previous CABG 22.0% (20/91) 24.5% (24/98) 23.3% (44/189) 0.7324

Previous PCI 16.5% (15/91) 15.3% (15/98) 15.9% (30/189) 0.8447

History of Diabetes 36.7% (36/98) 39.6% (36/91) 38.1% (72/189) 0.7647

Previous Stroke2 3.1% (3/98) 3.3% (3/91) 3.2% (6/189) 1.0000

Previous TIA 6.1% (6/98) 8.8% (8/91) 7.4% (14/189) 0.5827


NYHA Class III/IV 80.0% (76/95) 87.6% (78/89) 83.7% (154/184) 0.1696

Lesion Volume as 7800.1 [3248.4, 7551.6 [2127.8, 7783.6 [2982.1, 0.5881calculated on FLAIR 17315.3] 19875.6] 18224.4](mm3)


Valve Area (cm2) 0.7 ± 0.17 (89) 0.7 ± 0.20 (98) 0.7 ± 0.18 (187) 0.5969

Mean aortic valve 40.0 [31.8, 46.5] 41.0 [32.3, 50.2] 40.6 [32.0, 47.7] 0.2929gradient (mmHg) (98) (88) (186)

Note: Continuous data presented as Mean ± SD (n) or Median [IQR] (n). Categorical data presented using% (n/N).1P-values are testing for statistical differences across randomized arms. Continuous data are comparedusing ANOVA or two-sided Wilcoxon test; categorical data are compared using Fisher's exact test.2Defined as neurological deficit lasting more than 24 hours confirmed by imaging.

Supplemental Table 4. Baseline characteristics of patients with paired baseline and 30 day neurocognitive assessment

Control Arm (N=92)

Device Arm (N=93)


Age 84.8 [78.4, 89.0](92)

83.1 [77.8, 87.2](93)

83.8 [78.1, 88.3](185)

0.2585

Male 50.0% (46/92) 49.5% (46/93) 49.7% (92/185) 1.0000

BMI 27.3 [24.5, 31.1](90)

27.0 [23.7, 32.6](92)

27.1 [24.1, 31.8](182)

0.7377

STS PROM Score 6.4 [4.5, 8.5] (92) 5.3 [3.9, 7.9] (93) 6.0 [4.2, 8.0] (185) 0.1214History of Atrial Fibrillation

31.5% (29/92) 31.2% (29/93) 31.4% (58/185) 1.0000

History of PVD 12.0% (11/92) 15.1% (14/93) 13.5% (25/185) 0.6679

History of CAD 55.4% (51/92) 50.5% (47/93) 53.0% (98/185) 0.5568

Previous CABG 22.8% (21/92) 19.4% (18/93) 21.1% (39/185) 0.5927

Previous PCI 12.0% (11/92) 21.5% (20/93) 16.8% (31/185) 0.1145

History of Diabetes 39.1% (36/92) 41.2% (39/93) 40.5% (75/185) 0.7651

Previous Stroke2 1.1% (1/92) 3.2% (3/93) 2.2% (4/185) 0.6209

Previous TIA 5.4% (5/92) 8.6% (8/93) 7.0% (13/185) 0.5669


NYHA Class III/IV 80.9% (72/89) 84.6% (77/91) 82.8% (149/180) 0.5574


Valve Area (cm2) 0.7 ± 0.21 (91) 0.7 ± 0.17 (91) 0.7 ± 0.19 (182) 0.7162

Mean aortic valve gradient (mmHg)

40.8 [33.0, 47.0](91)

41.5 [32.3, 53.0](90)

41.0 [32.4, 49.0](181)

0.4658

Note: Continuous data presented as Mean ± SD (n) or median [IQR] (n). Categorical data presented using% (n/N).1P-values are testing for statistical differences across randomized arms. Continuous data are comparedusing ANOVA or two-sided Wilcoxon test; categorical data are compared using Fisher's exact test.2Defined as neurological deficit lasting more than 24 hours confirmed by imaging.

Supplemental Table 5. DW-MRI Median new lesion volume and number of new lesions by TAVR device type (unadjusted analysis, Day 2-7)

Control Arm Device Arm P-value1

Median New Lesion Volume (mm3), Protected Territories

SAPIEN XT 322 (31, 785.7), n=14 55.4 (0, 181.9), n=15 0.0455

SAPIEN 3 143.4 (33, 233.3), n=56 104.7 (50.1, 384.3), n=52 0.4454

CoreValve Evolut R 324.3 (141.1, 1077.8), n=24 147.7 (18.5, 479.9), n=21 0.1185

Median New Lesion Volume (mm3), All Territories

SAPIEN XT 518.1 (134.5, 1170.7), n=14 114 (29, 321.7), n=15 0.0341

SAPIEN 3 193.5 (59.3, 464.1), n=56 265 (131.8, 962.1), n=52 0.0516

CoreValve Evolut R 807.2 (326.6, 1716.5), n=24 369.1 (63.3, 786.4), n=21 0.0465

Median New Lesion Number, Protected Territories

SAPIEN XT 3.5 (1, 9), n=14 2 (0, 3), n=15 0.0347

SAPIEN 3 2 (1, 4), n=56 2 (1, 6.5), n=52 0.0425

CoreValve Evolut R 5.5 (2.5, 11.5), n=24 2 (1, 6), n=21 0.0189

Median New Lesion Number, All Territories

SAPIEN XT 7 (1, 12), n=14 2 (1, 5), n=15 0.0300

SAPIEN 3 4 (1.5, 6), n=56 3 (2, 10), n=52 0.0124

CoreValve Evolut R 8.5 (5.5, 15.5), n=24 3 (1, 12), n=21 0.0346

Note: Medtronic CoreValve (which only contributed 7 patients with imaging follow-up) was excluded from this analysis.1Lesion volume analyses based on Wilcoxon test; lesion number analyses based on negative binomial regression model

Supplemental Table 6. 30-day median total new lesion volume (unadjusted analysis)

Test Arm (n=78)

Control Arm (n=80)

Observed Treatment Difference

(test - control)

Hodges-Lehmann Estimate of

Location Shift (95% CI) P-value1

Protected Territories

ITT, mm3

0 (0, 52.7) 0 (0, 83.1) 0.0 0 (0, 0) 0.8255

All Territories

ITT, mm3

0 (0, 73.8) 0 (0, 108.1) 0.0 0 (0, 0) 0.8507

Data are presented as median (IQR)1Based on Wilcoxon Test

Supplemental Table 7. Significant Results of (A) Univariate Analysis and (B) Multivariable Analysis of Baseline Characteristics Predicting Transformed New Volumes in Protected Territories

Source Pr > F Source Pr > FBaseline Volume Strata (High/Low) <.0001 Weight (lbs) 0.0568LNZ[Baseline Lesion Volume] <.0001 Neurological Deficit [Y/N] 0.0594LNZ[Baseline Lesion Number] 0.0024 Currently taking medications (Y/N) 0.0632LNZ[HU_850 Volume] 0.009 Peak Aortic Jet Velocity 0.0636Age 0.0155 STS Risk score 0.0643Dilatation Post TAVR Procedure 0.034 Rosenhek2 0.071Temperature 0.0495 Neurocognitive Verbal Memory Score 0.078BSA 0.0517 History of Percutaneous Coronary Intervention (Y/N) 0.0884A. Univariate Analysis

Parameter DF Estimate Standard Error

t Value P-Value

Intercept 1 0.88 1.041516 0.85 0.39.

Baseline T2-FLAIR Volume 1 0.44 0.116631 3.83 0.0002B. Multivariable Analysis

Supplemental Table 8. Least Squares Means and Test of Main Effects (adjusted by Interaction of Valve Type and Treatment Arm, and High/Low BL Lesion Volume) – ITT Population

EffectMean Estimate

(95% CI)p-value

Least Squares Mean new lesion volume (mm3), Protected territories

Control Arm162.8

(107.9, 245.5)0.0248

Device Arm83.3

(55.0, 126.1)

Least Squares Mean new lesion volume (mm3), all territories

Control Arm311.1

(212.2, 456.3)0.0500

Device Arm180.6

(122.7, 265.8)


Evolut R (n=45)172.6

(103.7, 287.2)

0.166SAPIEN 3 (n=108)113.6

(81.8, 157.8)

SAPIEN XT (n=29)80.5

(42.6, 152.0)


Evolut R (n=45)408.0

(253.9, 655.6)

0.021SAPIEN 3 (n=108)228.2

(168.0, 309.9)

SAPIEN XT (n=29)143.1

(79.1, 258.7)

Note: In order to get stable TAVR device estimates from the model, Medtronic CoreValve (which only contributed 7 patients with imaging follow-up) was excluded from the analysis.

Supplemental Table 9. Least Squares Means and Test of Interaction Effects (Arm within Valve Type adjusted by Treatment Arm, Valve Type and and High/Low BL Lesion Volume) – ITT, Lesion Volume

EffectControl Arm

Mean Estimate (95% CI)

Device Arm Mean Estimate

(95% CI)p-value*


Evolut R (n=45) 279.1(139.2, 559.4)

106.7(50.7, 224.7) 0.0642

SAPIEN XT (n=29) 162.7(65.3, 405.4)

39.8(16.5, 96.1) 0.0296

SAPIEN 3 (n=108) 95.0(60.2, 149.9)

135.8(84.7, 217.9) 0.2834


Evolut R (n=45) 691.0(361.6, 1320.4)

240.9(120.4, 481.7)

0.0297

SAPIEN XT (n=29) 268.1(114.5, 627.7)

76.3(33.6, 173.4)

0.0369

SAPIEN 3 (n=108) 162.5(106.2, 248.7)

320.3(206.3, 497.4)

0.0299

Note: In order to get stable TAVR device estimates from the model, Medtronic CoreValve (which only contributed 7 patients with imaging follow-up) was excluded from the analysis. *No adjustment for multiple comparisons was made.

Supplemental Figure 1. Correlation between neurocognitive score and MRI lesions

a. Protected territories

r = -0.2028

p = 0.0109

b. All territories

r = -0.2356

p = 0.003

References

1. Smith, S., Jenkinson, M., & Woolrich, M. Advances in functional and structural MR image analysis and

implementation as FSL. Neuroimage 2004;23 Suppl 1: S208–19.

2. Jezzard, P., & Balaban, R. Correction for geometric distortion in echo planar images from B0 field variations.

Magnetic Resonance in Medicine. 1995;34(1), 65–73.

3. Andersson, J.L.R., Skare, S., Ashburner, J. How to correct susceptibility distortions in spin-echo echo-planar

images: application to diffusion tensor imaging. NeuroImage, 20(2):870-888, 2003.

4. Liguori, M., Meier, D. S., Hildenbrand, P., Healy, B. C., Chitnis, T., Baruch, N. F., Guttmann, C. R. G. (2011).

One year activity on subtraction MRI predicts subsequent 4 year activity and progression in multiple sclerosis.

Journal of Neurology, Neurosurgery, and Psychiatry. 2011;82(10), 1125–31. doi:10.1136/jnnp.2011.242115

5. Sled, J. G., Zijdenbos, A. P., & Evans, A. C. A nonparametric method for automatic correction of intensity

nonuniformity in MRI data. IEEE Transactions on Medical Imaging. 1998;17(1), 87–97. doi:10.1109/42.668698

6. Nyul, L., Udupa, J., & Zhang, X. New variants of a method of MRI scale standardization. Medical Imaging,

IEEE. 2000;19(2), 143–150.

7. Jenkinson, M., & Smith, S. A global optimisation method for robust affine registration of brain images. Medical

Image Analysis, 2001;5(2), 143–156.

8. Tavazzi, E., Dwyer, M. G., Weinstock-Guttman, B., Lema, J., Bastianello, S., Bergamaschi, R., Munschauer, F. E.

Quantitative diffusion weighted imaging measures in patients with multiple sclerosis. Neuroimage,

2007;36(3):746–54. doi:10.1016/j.neuroimage.2007.03.056

9. Grabner, G., Janke, A., & Budge, M. (2006). Symmetric atlasing and model based segmentation: an application to

the hippocampus in older adults. In Medical Image Computing and Computer-Assisted Intervention (pp. 58–66).

Berlin: Springer.

10. Möller, T. B., & Reif, E. (2007). Pocket Atlas of Sectional Anatomy: Head and Neck (p. 264). Stuttgart: Thieme.

11. Hartkamp, N. S., De Cocker, L. J., Helle, M., van Osch, M. J. P., Kappelle, L. J., Bokkers, R. P. H., &

Hendrikse, J. In vivo visualization of the PICA perfusion territory with super-selective pseudo-continuous

arterial spin labeling MRI. NeuroImage, 2013;83:58–65. doi:10.1016/j.neuroimage.2013.06.070

12. Marshall RS, Lazar RM. Pumps, aqueducts, and drought management: Vascular physiology in vascular cognitive impairment. Stroke; a journal of cerebral circulation. 2011;42:221-226

13. Mohr J, Lazar R, Marshall R. Middle cerebral artery disease. In: Mohr J, Wolf P, Grotta J, Moskowitz M, Maybert M, von Kummer R, eds. Stroke: Pathophysiology, diagnosis and management. New York: Elsevier; 2011:385-424.

14. Kahlert P, Knipp SC, Schlamann M, Thielmann M, Al-Rashid F, Weber M, et al. Silent and apparent cerebral ischemia after percutaneous transfemoral aortic valve implantation: A diffusion-weighted magnetic resonance imaging study. Circulation. 2010;121:870-878

15. Ghanem A, Kocurek J, Sinning JM, Wagner M, Becker BV, Vogel M, et al. Cognitive trajectory after transcatheter aortic valve implantation. Circulation. Cardiovascular interventions. 2013;6:615–24.

16. Lietz K, Brown K, Ali SS, Colvin-Adams M, Boyle AJ, Anderson D…Lazar, RM. The role of cerebral hyperperfusion in postoperative neurologic dysfunction after left ventricular assist device implantation for end- stage heart failure. The Journal of thoracic and cardiovascular surgery. 2009;137:1012-1019

17. Festa JR, Jia X, Cheung K, Marchidann A, Schmidt M, Shapiro PA…Lazar, RM. Association of low ejection fraction with impaired verbal memory in older patients with heart failure. Archives of neurology. 2011;68:1021- 1026

18. Lazar RM, Marshall RS, Pile-Spellman J, Young WL, Hacein-Bey L, Sloan RP, et al. Continuous time estimation as a behavioural index of human cerebral ischaemia during temporary occlusion of the internal carotid artery. Journal of neurology, neurosurgery, and psychiatry. 1996;60:559-563

19. Marshall RS, Festa JR, Cheung YK, Chen R, Pavol MA, Derdeyn CP…Lazar, RM. Cerebral hemodynamics and cognitive impairment: Baseline data from the recon trial. Neurology. 2012;78:250-255

20. Festa JR, Schwarz LR, Pliskin N, Cullum CM, Lacritz L, Charbel FT…Lazar, RM. Neurocognitive dysfunction in adult moyamoya disease. Journal of neurology. 2010;257:806-815

21. Lezak D, Howieson D, Loring D. Neuropsychological assessment. Oxford University Press; 2004.

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