A GRIN-coupled multimode fibre delivers broadband VIS–NIR light through a sapphire window into the contacted tissue and collects the diffuse reflectance back to an on-console spectrometer. The result: a per-contact biochemical fingerprint of amyloid load, fibrosis, ischemia and inflammation.04
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.
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.
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.
Four Pt–Ir micro-ring electrodes at 150 µm spacing drive a low-current sweep across the tissue interface, separating intracellular from extracellular conductivity and capturing the dielectric signature that distinguishes healthy from scarred myocardium.05
A miniature PZT actuator emits a controlled shear pulse; an adjacent PVDF film captures the return. From propagation delay and damping we recover local stiffness — the single most reliable physical correlate of advanced amyloid infiltration.06
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
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.
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.
-
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
-
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
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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
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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
-
05
Schwan HP. Electrical properties of tissue and cell suspensions. Advances in Biological and Medical Physics · 1957 · 5:147-209
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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
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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
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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
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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
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10
Niederer SA, Lumens J, Trayanova NA. Computational models in cardiology. Nature Reviews Cardiology · 2019 · 16(2):100-111
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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
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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
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13
Rieke N, Hancox J, Li W, et al. The future of digital health with federated learning. npj Digital Medicine · 2020 · 3:119
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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
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15
Abadi M, Chu A, Goodfellow I, et al. Deep learning with differential privacy. Proc. ACM CCS · 2016 · 308-318
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.
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.
Cardiologist and inventor of the CardioSpectra platform. Filed the founding provisional in October 2025. Leads clinical, regulatory and platform strategy.
Practicing electrophysiologist responsible for procedural workflow design, EP lab integration, and the clinical-evidence pathway through to first-in-human.
Cardiac imaging lead. Owns the MRI / CT → patient-specific mesh pipeline and the histology-anchored validation strategy.
Drives the first-indication strategy on cardiac amyloidosis — patient selection, referral networks and the path to reimbursement coverage.
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.
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.