ClotView - Feasibility & Cost/Materials Analysis

What ClotView Is (from your slides)

Feasibility Assessment

Technical Feasibility: MODERATE-HIGH

• Compression ultrasound for DVT is already the clinical gold standard - so the sensing physics is proven.
• Miniaturizing it into a wearable cuff is the hard part. Flexible/wearable ultrasound arrays already exist in research (e.g. UC San Diego's skin patch ultrasound, 2021). So this is technically achievable but not trivial.
• The challenge: piezoelectric transducer arrays need good acoustic coupling with skin (requires gel or gel-like membrane). In a cuff format this is solvable with a fixed gel pad.

• NIRS is very well-established in wearables (pulse oximeters use a subset of it). Tissue oxygenation NIRS is used clinically in brain monitoring and muscle research.
• Integrating it into a limb cuff at 700-900 nm to detect downstream oxygen drop is biologically sound - a clot causes ischemia → lower StO₂ downstream.
• This is the easier of the two modalities to miniaturize.

• A binary or probability classifier trained on UST + NIRS paired signals is very achievable with current ML tools. The main bottleneck is labeled training data.

• The two modalities are complementary (UST = structural, NIRS = functional), which reduces false positives. This is scientifically sound.

Key Feasibility Risks

Materials List & Cost Estimate

Prototype (Single Unit - R&D/Proof of Concept)

For a Polished Prototype (~5 units for testing)

• Add PCB fabrication (Gerber → JLCPCB): ~$200-500
• Custom silicone molding: ~$300-800 (one-time mold cost)
• Total for 5 units: ~$3,000 - $6,000

Mass Production Cost (if scaled to thousands of units)

• Bill of Materials drops to roughly $80 - $150/unit at volume
• Retail price target would be $500 - $1,500 (comparable to handheld Doppler devices)

Development Stage Feasibility Roadmap

Bottom Line

What is Feasibility?

The 5 Types of Feasibility (for ClotView)

1. 🔧 Technical Feasibility

• Does the technology (UST + NIRS) exist? YES - both are proven
• Can they be miniaturized into a wearable cuff? YES, but challenging
• Can AI analyze the combined signals? YES

2. 💰 Economic / Financial Feasibility

• Prototype cost: ~$500 - $1,200
• Mass production cost: ~$80 - $150/unit
• Market need: HUGE (millions of DVT cases yearly)
• Current alternatives (MRI, Doppler) cost thousands of dollars

3. ⚙️ Operational Feasibility

• Is it simple enough for bedside use? Needs to be
• Does it need a specialist to operate? Should NOT - that's your selling point
• Can it work without internet? Should have offline AI mode

4. ⏱️ Time Feasibility

5. ⚖️ Legal / Regulatory Feasibility

• Medical devices need approval (FDA in USA, CE Mark in Europe, CDSCO in India)
• Class II or III medical device - needs clinical proof it is safe and accurate
• This is the hardest and most expensive part

Simple One-Line Summary

Feasibility = checking if your idea is POSSIBLE, PRACTICAL, and WORTH DOING before you build it.

Thrombus Detection & Management Devices Currently in the Market

🔍 DETECTION / DIAGNOSIS Devices (Direct Competitors to ClotView)

1. Doppler Ultrasound Machines

• Companies: GE Healthcare, Philips, Siemens Healthineers
• How it works: Sound waves image veins; doctor compresses vein to check for clot
• Used in: Hospitals, radiology departments
• Cost: $20,000 - $100,000+
• Problem: Needs a trained specialist, not portable, not wearable
• ClotView advantage: You are building exactly the portable version of this

2. Point-of-Care Ultrasound (POCUS)

• Companies: Clarius, Butterfly Network (iQ+), Philips Lumify
• How it works: Handheld ultrasound probe connected to a phone/tablet
• Cost: $2,000 - $10,000
• Used in: Emergency rooms, bedside
• Problem: Still needs a trained doctor to interpret images, no NIRS, no AI scoring
• ClotView advantage: Automated dual-mode (UST + NIRS) with AI - no specialist needed

3. D-Dimer Blood Tests

• Companies: Roche Diagnostics, Becton Dickinson, Baebies (FINDER platform - FDA Breakthrough Device, April 2025)
• How it works: Blood test that measures clot breakdown products
• Cost: $20 - $150 per test
• Problem: High false positive rate, needs blood draw, gives no visual info, cannot locate clot
• ClotView advantage: Non-invasive, gives exact location visually

4. CT Venography / MRI Venography

• Companies: Siemens, GE, Canon Medical
• How it works: Full body scanner maps veins with contrast dye
• Cost: $1,500 - $5,000 per scan
• Problem: Radiation (CT), very expensive, hospital-only, slow
• ClotView advantage: Bedside, real-time, no radiation, no dye

🛠️ TREATMENT Devices (Remove Clots - Different from ClotView but shows the market)

📊 Market Size (2025-2026)

🎯 Where ClotView Fits (The GAP in the Market)

How UST (Ultrasound Transducer) Connects Wirelessly in ClotView

The Full Wireless Pipeline

Piezoelectric Transducer Array
        ↓
  Analog Front-End IC
  (amplify + filter raw US signal)
        ↓
  ADC (Analog to Digital Converter)
  (converts signal to digital data)
        ↓
  Microprocessor / FPGA
  (beamforming + image processing)
        ↓
  Bluetooth 5.0 / Wi-Fi Module
        ↓
  Phone / Tablet App
  (display UST image + NIRS heatmap)

Step-by-Step Explanation

Step 1 - Transducer Sends & Receives Sound

• The piezoelectric array in the cuff sends ultrasound pulses (5-10 MHz) into the limb
• Reflected echoes come back and are converted to electrical signals

Step 2 - Analog Front-End (AFE) IC

• Raw ultrasound signals are very tiny (microvolts)
• The AFE chip amplifies and filters the signal
• Example chip: Texas Instruments AFE5832 or Analog Devices AD9272
• This chip sits inside the cuff housing (wired to transducer - very short cable, just a few cm)

Step 3 - ADC + FPGA (The Brain)

• The amplified signal is digitized by an ADC (Analog to Digital Converter)
• An FPGA (like Xilinx Artix-7) does beamforming - reconstructing the 2D vein image from raw echo data
• This is the most power-hungry part - runs on the onboard Li-Po battery

Step 4 - Wireless Transmission

Step 5 - App on Phone/Tablet

• Receives the data wirelessly
• Renders the UST vein image on one side
• Renders the NIRS oxygen heatmap on the other side
• AI model runs on-device and gives the clot probability score

Real-World Example Already Doing This

• Transducer + processing chip inside the probe
• Sends images over Wi-Fi to a phone app
• No cable to the screen at all

The Only Wired Part

Simple Summary

The cuff has its own mini-computer + battery inside. It processes the ultrasound signal onboard, then sends the finished image wirelessly via Wi-Fi/Bluetooth to your phone or tablet app. No wire between cuff and screen - only a short internal wire between transducer and chip inside the cuff itself.

Butterfly iQ+ & Ultrasound Research for Clot Detection

What is Butterfly iQ+?

• Made by Butterfly Network Inc. (NYSE: BFLY)
• World's first single-chip, whole-body handheld ultrasound (launched 2018 as iQ, then iQ+ in 2020, iQ3 in 2024)
• Uses Ultrasound-on-Chip™ semiconductor technology - replaces traditional bulky piezoelectric arrays with a semiconductor chip
• Connects wirelessly to a phone/tablet via Wi-Fi
• Cost: ~$2,000-$3,000 per probe (vs $20,000+ for traditional machines)
• Used by emergency doctors at bedside for DVT detection ("POCUS" - Point of Care Ultrasound)

Research: Does Ultrasound Actually Work for DVT Detection?

Study 1 - Best Evidence (Systematic Review + Meta-Analysis, 2024)

• Hercz et al., West J Emerg Med, 2024 - PMID 38596931
• 15 studies, 2,511 patients
• Results:

• 3-point compression method was more accurate than 2-point
• Conclusion: POCUS by trained physicians is excellent for DVT - nearly as good as radiology

Study 2 - Meta-Analysis of POCUS Protocols (2024)

• Zaki et al., Ultrasound J, 2024 - PMID 39080184
• 26 studies analyzed

• POCUS diagnosis was significantly faster than waiting for radiology
• Conclusion: POCUS should be first-line DVT imaging in emergency settings

Study 3 - AI-Guided Ultrasound for DVT (2025 - Key Limitation!)

• Multi-center, double-blind test on 294 patients
• AutoDVT (AI software guiding non-specialists to do the scan):

• 81% of scans had to be repeated 3 times due to failed scanning
• When a remote clinician reviewed: sensitivity jumped to 85%
• Conclusion: Current AI-guided DVT ultrasound is not yet safe enough for unsupervised use - needs better software

What This Means for ClotView

Bottom Line for Your Pitch

Research confirms ultrasound is highly accurate (90-97%) for DVT when used by trained people. The gap ClotView fills is that without training, AI-only guidance currently gets only 68% sensitivity - but that's because current systems use only ultrasound. ClotView's dual UST + NIRS fusion gives the AI two independent signals, which is your key scientific differentiator over devices like AutoDVT.

Research Articles: NIRS + Ultrasound for Clot/DVT Detection

The Big Picture

Stream 1 - NIRS Alone for DVT Detection

📄 Pioneer Study (2003) - Proof of Concept

• Korah et al., University of Louisville / Johns Hopkins
• PMID: 14562768
• What they did: Built a portable NIR probe (760 nm + 850 nm wavelengths - exactly what ClotView uses!) to measure oxyhemoglobin + deoxyhemoglobin changes in leg during exercise
• Key finding: DVT legs showed:
  • Higher blood volume in the limb
  • Faster blood filling rate
  • Inability to push blood out during muscle contraction
• Conclusion: "The NIR device proved to be an inexpensive, effective, and portable device that can detect DVT in the leg in real-time"
• Why it matters for ClotView: This is direct proof NIRS detects DVT - same wavelengths you are using (700-900 nm)

Stream 2 - NIRS + Ultrasound Combined (Hybrid) for DVT Prediction

📄 Combined NIRS + Ultrasound Study - Most Relevant!

• Cited in Aetna Clinical Policy Bulletin on NIR Spectroscopy
• What they did: Used both ultrasound measurements (vein diameter) AND NIRS-derived Resistance Index (RI) together to predict DVT
• Key findings:
  • NIR-derived RI > 2.3 = strong predictor of post-operative DVT (p=0.004)
  • Gastrocnemius vein diameter > 0.25 cm (from ultrasound) also predicted DVT
  • Using both together = best predictive accuracy
• Conclusion: "NIR spectroscopy-derived RI > 2.3 is a promising parameter for identifying patients at risk of developing post-operative DVT"
• Why it matters for ClotView: This is the exact scientific basis for your dual-mode approach - UST + NIRS together outperforms either alone

Stream 3 - NIRS for Limb Ischemia (What Happens Downstream of a Clot)

📄 Study 1: NIRS Monitors Foot Oxygen in Blocked Arteries (2016)

• Boezeman et al., Eur J Vasc Endovasc Surg, 2016 - PMID 27614555
• 14 patients with blocked arteries (critical limb ischemia)
• Key findings:
  • NIRS successfully detected real-time drop in tissue oxygen (StO₂) in ischemic limbs
  • After blood flow restored by surgery: StO₂ significantly increased (p<0.01)
  • Contralateral (healthy) leg showed no change
• Conclusion: NIRS is safe and feasible for non-invasive limb oxygen monitoring

📄 Study 2: NIRS Limb-to-Arm Ratio for Ischemia Detection (2016)

• Boezeman et al., Vascular, 2016 - PMID 26503733
• 61 ischemic patients vs 30 healthy controls
• Key finding: NIRS values were significantly different between ischemic and normal limbs (p<0.001) BUT single-point measurements had poor predictive value alone
• Important lesson for ClotView: NIRS alone has broad overlap between sick and healthy - this is WHY you need UST as well - dual mode fixes this weakness!

Stream 4 - NIRS-IVUS Combined (Inside Arteries - Coronary)

• Already an FDA-approved commercial device exists: TVC Imaging System (Infraredx)
• Combines NIRS + IVUS (ultrasound inside arteries) to detect lipid-rich plaques
• Proven in clinical trials for coronary artery disease
• Why it matters: Proves NIRS + US combination is clinically validated - just not yet done as an external wearable for DVT

Summary Table: Research Support for ClotView

The Scientific Gap ClotView Fills

No published study has yet combined external wearable NIRS + external ultrasound into one cuff for bedside DVT detection. The research shows both technologies work individually and directionally together - but your device is the first to propose integrating both non-invasively in a wearable cuff format with AI fusion. That is your original contribution and what makes it publishable.