CardioSpectra Lab · Pre-clinical · May 2026

See the heart
as it actually is.

A tri-modal intracardiac platform that fuses hyperspectral optics, bio-impedance and tissue elastography into a live, patient-specific cardiac digital twin — at the catheter tip, during the procedure.

Device class
8 Fr deflectable diagnostic catheter
Modalities
Optical · Impedance · Elastoco-located
Software
FusionSuite SaMDreal-time twin
First indication
Cardiac amyloidosis Dx
Scroll
01 · The diagnostic gap

Today, the heart is mapped
but not understood.

Electroanatomic systems show where electricity travels. Contact-force catheters report mechanical touch. NIRS prototypes hint at biochemistry. None of them, together, tell a cardiologist what the tissue under the catheter actually is. That blind spot is why cardiac amyloidosis goes undiagnosed in roughly 1 in 8 HFpEF patients01 — and why ablation recurrence remains stubbornly high a decade after CARTO 3.

0%
of HFpEF patients carry undiagnosed cardiac amyloidosis. González-López et al. · Eur Heart J 2015
$0B
Global EP ablation market by 2030. iData Research · 2024 forecast
0%+
CAGR in the cardiac-amyloid Dx & Tx market through the Tafamidis era. Internal market model · CardioSpectra 2026
0M
Pacemakers implanted worldwide each year — the long-tail opportunity for an embedded sensor (CardioSpectra Lite). WHO MedTech registry · 2024
02 · The catheter

Three orthogonal modalities.
One tissue-contact point.

An 8 French, 110 cm deflectable diagnostic catheter that integrates a sapphire optical window, four platinum–iridium ring electrodes, and a PZT/PVDF micro-elastography stack within a single PEEK distal tip. Each sample is timestamped to a shared clock and co-registered to the electroanatomic map — so optical, electrical and mechanical data describe the same square millimetre of tissue.

Specification
Value
Tolerance
Standard
Shaft outer diameter
8 Fr · 2.67 mm
±0.04 mm
ISO 11070
Working length
110 cm
±1 cm
Internal
Deflection
Bidirectional · 180°
±5°
EP standard
Distal housing
PEEK (Victrex 450G)
Cl. VI
ISO 10993-1 / -5 / -10
Sampling rate
All modalities at 50 Hz
±1 ms drift
Common clock
Tissue classes
Normal · Fibrosis · Amyloid · Ischemic · Inflamed
≥ 90% accuracy
Histology-validated
03 · FusionSuite

A real-time digital twin
that updates with every contact.

FusionSuite builds a patient-specific finite-element heart mesh from pre-procedural MRI or CT, then continuously assimilates live tri-modal catheter data through an ensemble Kalman filter. A physics-informed neural surrogate replaces hours of monodomain solving08 with sub-500 ms inference — so the twin updates in stride with the electrophysiologist.07

01
Patient-specific mesh
nnU-Net pipeline segments cine MRI / contrast CT into a finite-element mesh in under 90 seconds.11
02
Tri-modal → tissue parameter mapping
Catheter measurements drive per-node conductivity tensors, ionic-model parameters and local stiffness — confidence-weighted by the classifier's calibrated uncertainty.
03
PINN surrogate · sub-500 ms inference
A physics-informed network trained on 10 000+ openCARP simulations replaces the solver in the live loop, on a single GPU.12
04
Closed-loop ablation planning
Virtual lesion placement runs against the twin in real-time, surfacing predicted recurrence risk before energy is delivered.07
04 · Nexus

One institution
cannot learn the heart
alone.

Nexus is the federated-learning layer13 that lets every CardioSpectra installation contribute to a shared model without a single byte of patient data leaving the hospital.14 Gradient updates are clipped and DP-noised on-prem,15 then aggregated against a histologically grounded spectral tissue reference library that audits drift against 3-, 6- and 12-month ablation outcomes.

0 sites · target Y1
Federation rollout
0 entries
Spectral reference library v1
0 & 6 & 12 mo
Outcome-anchored drift detection
DP-SGD
Differential privacy primitive
05 · Evidence base

Built on the
published literature.

CardioSpectra sits at the intersection of four mature research lines — cardiac amyloidosis, multimodal intracardiac sensing, patient-specific cardiac digital twins, and federated medical AI. Every architectural decision is anchored to peer-reviewed work below.

A · Cardiac amyloidosis & first indication
  1. 01
    González-López E, Moñivas-Palomero V, Escobar-López L, et al. Wild-type transthyretin amyloidosis as a cause of heart failure with preserved ejection fraction. European Heart Journal · 2015 · 36(38):2585-94
  2. 02
    Maurer MS, Schwartz JH, Gundapaneni B, et al. Tafamidis treatment for patients with transthyretin amyloid cardiomyopathy. New England Journal of Medicine · 2018 · 379(11):1007-16
  3. 03
    Ruberg FL, Grogan M, Hanna M, Kelly JW, Maurer MS. Transthyretin amyloid cardiomyopathy: JACC state-of-the-art review. JACC · 2019 · 73(22):2872-91
B · Multimodal intracardiac sensing
  1. 04
    Singh-Moon RP, Marboe CC, Hendon CP. Near-infrared spectroscopy integrated catheter for characterization of myocardial tissues. Biomedical Optics Express · 2015 · 6(7):2494-2511
  2. 05
    Schwan HP. Electrical properties of tissue and cell suspensions. Advances in Biological and Medical Physics · 1957 · 5:147-209
  3. 06
    Couade M, Pernot M, Messas E, et al. In vivo quantitative mapping of myocardial stiffening and transmural anisotropy during the cardiac cycle. IEEE Trans. Medical Imaging · 2011 · 30(2):295-305
C · Cardiac digital twins & in-silico EP
  1. 07
    Boyle PM, Zghaib T, Zahid S, et al. Computationally guided personalized targeted ablation of persistent atrial fibrillation. Nature Biomedical Engineering · 2019 · 3:870-879
  2. 08
    Plank G, Loewe A, Neic A, et al. The openCARP simulation environment for cardiac electrophysiology. Computer Methods and Programs in Biomedicine · 2021 · 208:106223
  3. 09
    Rodero C, Strocchi M, Marciniak M, et al. Linking statistical shape models and simulated function in the healthy adult human heart. PLOS Computational Biology · 2021 · 17(4):e1008851
  4. 10
    Niederer SA, Lumens J, Trayanova NA. Computational models in cardiology. Nature Reviews Cardiology · 2019 · 16(2):100-111
D · AI & federated learning
  1. 11
    Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature Methods · 2021 · 18(2):203-211
  2. 12
    Raissi M, Perdikaris P, Karniadakis GE. Physics-informed neural networks for solving forward and inverse problems involving nonlinear PDEs. Journal of Computational Physics · 2019 · 378:686-707
  3. 13
    Rieke N, Hancox J, Li W, et al. The future of digital health with federated learning. npj Digital Medicine · 2020 · 3:119
  4. 14
    Dayan I, Roth HR, Zhong A, et al. Federated learning for predicting clinical outcomes in patients with COVID-19. Nature Medicine · 2021 · 27:1735-1743
  5. 15
    Abadi M, Chu A, Goodfellow I, et al. Deep learning with differential privacy. Proc. ACM CCS · 2016 · 308-318
06 · Pipeline

From bench to bedside,
candidly sequenced.

We work the way investors and the FDA both reward — software MVP and benchtop sensor rig progressing in parallel, integrating around month nine. Bench evidence first; alpha catheter second; pre-submission meeting before any biocompatibility spend.

Q4 2025
Provisional patent
Tri-modal catheter, FusionSuite and Nexus filed. Continuation-in-part drafted May 2026.
2026 · Now
Bench rig + software MVP
Three-modality benchtop sensor rig acquiring ex-vivo cardiac data; FusionSuite skeleton on public MRI cohorts.
Q4 2026
Integrated demo
Bench-acquired data assimilated into the digital twin. Methods preprint, non-provisional filed.
2027
Alpha catheter · FDA Q-Sub
CDMO build of the integrated 8 Fr catheter. Pre-submission with the FDA. ISO 10993 begins.
2028 +
GLP preclinical · FIH
Porcine EP studies. De Novo / 510(k) preparation. First-in-human readiness.
07 · Founders

Built by physicians
who feel the gap.

CardioSpectra Lab is led by Krtin Singhal, MD, and a founding team of four practicing cardiologists spanning general cardiology, electrophysiology and imaging — the clinicians who live the diagnostic gap CardioSpectra closes. We are actively expanding the team with mechatronics, ML and regulatory leadership.

Krtin Singhal, MD
Founder · Inventor · CEO

Cardiologist and inventor of the CardioSpectra platform. Filed the founding provisional in October 2025. Leads clinical, regulatory and platform strategy.

Adarsh Balaji, MD
Lead Investigator

Practicing electrophysiologist responsible for procedural workflow design, EP lab integration, and the clinical-evidence pathway through to first-in-human.

Vikaskumar Patel, MD
Lead Investigator

Cardiac imaging lead. Owns the MRI / CT → patient-specific mesh pipeline and the histology-anchored validation strategy.

Nayan Doobay, MD
Lead Investigator

Drives the first-indication strategy on cardiac amyloidosis — patient selection, referral networks and the path to reimbursement coverage.

Konstantin Kecman, MD
Chief of Clinical Development

Owns the FDA pathway, pre-submission strategy and the design-history file. Bridges the engineering programme to ISO 13485, ISO 10993 and the GLP preclinical lab.

08 · Get in touch

Closing the loop
between
seeing and treating.

CardioSpectra is pre-clinical and currently raising. We respond personally to physicians, investors and prospective collaborators within two business days.

Direct line to Krtin Singhal, MD · Founder