Medical Hyperspectral Imaging: Benefits, Challenges, Cost

Posted in Medical Imaging

Medical hyperspectral imaging, or HSI for short, allows clinicians to see what standard cameras and the human eye cannot. Instead of just capturing static images, HSI records hundreds of light wavelengths, producing a detailed “spectral fingerprint” of tissue. This lets doctors detect early disease changes, guide surgery with greater precision, and monitor wounds more effectively. In clinical studies, medical hyperspectral imaging has achieved over 90% accuracy in detecting cancerous tissue, showing its potential to reduce biopsies and improve outcomes. Furthermore, this technology represents both a medical breakthrough and a fast-growing opportunity in precision diagnostics.

What is Medical Hyperspectral Imaging?

Medical hyperspectral imaging is an advanced optical solution that works as a conjunction of conventional imaging and spectroscopy. Instead of only detecting only three color bands like standard cameras, HSI records hundreds of narrow spectral bands across the ultraviolet (UV), visible (VIS), and near-infrared (NIR) range.

Each pixel in a hyperspectral image contains a full spectrum, creating a 3D dataset or “hypercube.” This provides both spatial and spectral information for clinicians to easily assess how light interacts with tissue through absorption, scattering, and fluorescence.

Since molecules like hemoglobin, melanin, and water have different spectral signatures, medical hyperspectral imaging can highlight subtle physiological and pathological changes that are not visible to the naked eye. 

The method is noninvasive, nonionizing, and usually requires no contrast agents, making it suitable for repeated and real-time use in clinical environments.

Medical Hyperspectral Imaging Market Size and Growth

The global hyperspectral imaging systems market size was estimated at USD 14.13 billion in 2023 and is expected to grow at a CAGR of 10.7% from 2024 to 2030. The rising adoption of hyperspectral imagery systems in various sectors, such as R&D, healthcare, defense, food industry, night vision, and remote sensing, is anticipated to create high demand in the market.

Advantages of Medical Hyperspectral Imaging

• Non-contact imaging: HSI can pick and decipher detailed tissue information without the need for probes or physical contact. This makes physical examinations comfortable for patients, reducing the risk of operator bias.
• Objective measurements: HSI reduces subjectivity in diagnosis and supports more consistent decision-making across clinicians via quantitative maps of oxygenation, perfusion, and biochemical composition.
• Earlier disease detection: The technology identifies biochemical changes in tissues before they are visible through standard imaging or clinical examination. This supports faster diagnosis and earlier intervention.
• Surgical assistance: Intraoperative HSI highlights residual tumor tissue and assesses tissue viability in real time, giving surgeons greater precision and improving outcomes by reducing recurrence and complications.

Use Cases of Medical Hyperspectral Imaging

Cancer Detection and Diagnostics

• Cervical cancer: Medical hyperspectral imaging grasps UV-VIS spectra of cervical tissue and analyzes chromophore absorption patterns to help clinicians distinguish normal from precancerous lesions more accurately.
• Breast cancer: Fluorescence HSI maps oxygenation differences between malignant and healthy tissue during surgery. Surgeons detect residual tumor cells smaller than one millimeter, improving precision while lowering recurrence risk.
• Skin cancer:  Reflectance medical hyperpectral imaging solution measures spectral profiles of melanin and hemoglobin in skin tissue. It supports noninvasive differentiation of melanoma from benign lesions, reducing unnecessary excisions.
• Head and neck cancers: Intraoperative reflectance imaging reveals spectral contrasts between tumor and surrounding tissue, giving surgeons real-time guidance for cleaner resections while preserving healthy structures.
• Colon and gastric cancers: HSI captures spectral differences in mucosal tissue during endoscopy or biopsy, supporting earlier detection of lesions and improving classification accuracy for treatment planning.

Cardiovascular and Vascular Diseases

• Peripheral artery disease (PAD): Oxygen saturation by analyzing oxy- and deoxyhemoglobin levels in skin and muscle provides measurements of ischemia severity for more detail-specific treatment strategies.
• Atherosclerosis: Detecting subtle spectral changes in arterial walls linked to plaque buildup leads to earlier and safer evaluation of arterial disease without invasive angiography.
• Hemorrhagic shock: The solution identifies mottled skin patterns caused by reduced perfusion and oxygenation, giving clinicians an immediate warning of hypoperfusion and enabling faster emergency intervention.

Ophthalmology

• Diabetic retinopathy and glaucoma: Detection of oxygen saturation across retinal vessels within seconds spots early vascular changes that allow intervention before vision is permanently affected.
• Age-related macular degeneration (AMD): HSI highlights ischemic regions and oxygen imbalances in the retina, supporting closer monitoring of disease progression and enabling timely treatment decisions.
  

Wound Care and Diabetic Ulcers

• Diabetic foot ulcers: Measuring hemoglobin saturation and perfusion in ulcer tissue helps HSI to predict healing potential with over 90% accuracy. Clinicians can select the right intervention, lowering amputation risk.
  
• Chronic wounds: Sequential imaging with HSI tracks perfusion changes over time, providing objective data on healing progress and guiding physicians to adjust therapies earlier.

Image-Guided Surgery

• Breast surgery: Intraoperative medical hyperspectral imaging visualizes spectral differences between malignant and healthy tissue, confirming complete tumor removal and reducing recurrence and reoperation rates.
• Gallbladder surgery: Near-infrared HSI maps biliary anatomy beneath tissue layers, preventing duct injuries by giving surgeons a clear view of critical structures.
• Renal and abdominal surgery: Continuous monitoring of oxygenation and ischemia with HSI helps surgeons preserve viable tissue and reduce complications related to inadequate blood supply.

Implementing Hyperspectral Imaging in Medical Settings

Below is the process that shows how to bring medical hyperspectral imaging into hospitals from planning to real clinical use:

Step 1: Assess Clinical Needs and Budget

Start by identifying the medical application and its use; whether it is for diagnostics (e.g., cancer detection) or intraoperative use (e.g., tumor margin visualization). Reflectance HSI suits surface analysis, such as skin cancer, while fluorescence works for deeper tissues. 

Setting a budget helps bring it from ideation to life as systems range from $10,000 for basic cameras to $500,000 for surgical-grade setups with advanced optics. Engage stakeholders like surgeons and administrators to align goals.

Step 2: Select the Right Hardware

HSI systems include 3 core components: 

• A broadband light source (LED or halogen)
• Spectral dispersion device (prisms, gratings, or tunable filters like LCTF)
• Detector (CCD for visible/NIR or InGaAs for SWIR)

Choose based on application, snapshot systems for real-time surgery or pushbroom for static diagnostics.

Step 3: Set Up and Calibrate

Install medical hyperspectral imaging in a controlled environment, like an operating room or diagnostic lab, where there is sterility and proper lighting. 

Calibrate with known spectral standards, as even minor deviations can skew biomarker detection. Integrate with hospital systems like PACS for data storage and retrieval, addressing cybersecurity to protect patient data.

Step 4: Build a Data Processing Pipeline

HSI generates massive datasets, gigabytes per image, that require sturdy processing. Use software for preprocessing (noise reduction), spectral unmixing to isolate chromophores like hemoglobin, and classification via AI algorithms (e.g., SVM or deep learning). 

GPU-accelerated platforms handle large hypercubes efficiently, enabling real-time analysis critical for surgery. Open-source tools or vendor software can streamline this.

Step 5: Train Staff and Validate Clinically

Train clinicians on HSI operation and interpretation via simulations and vendor-led workshops, costing $2,000-$5,000 per user. Conduct pilot studies to validate performance, such as detecting tumor margins with 95% accuracy. 

Build spectral databases for specific biomarkers (e.g., oxygenation levels) to increase diagnostic reliability. Ensure compliance with FDA or CE regulations for medical devices.

Step 6: Monitor and Optimize

Regularly maintain hardware and update software for improved algorithms. Collect feedback from clinicians to refine workflows, addressing challenges like motion artifacts in live imaging, which snapshot systems mitigate. HSI can reduce procedure times by 15-20%, cutting costs.

Medical Hyperspectral Imaging: Challenges and Solutions

Here is a list of some common roadblocks faced, along with their proposed solutions: 

1. Limited Penetration Depth

Light, especially in the visible spectrum, scatters and is absorbed by biological tissue, restricting HSI to a depth of only a few millimeters.

Solution: Researchers are exploring the use of near-infrared (NIR) light, which can penetrate deeper into tissue. Combining HSI with endoscopy or ultrasound can also provide both surface-level spectral data and structural information from deeper tissues.

2. Tissue Heating

Intense illumination needed for HSI can potentially heat and damage delicate biological tissue.

Solution: This can be addressed with pulse-mode illumination that delivers brief, intense bursts of light with cool-down periods in between. Additionally, systems can incorporate thermal management solutions like cooling plates to dissipate heat away from the tissue.

3. High Cost 

HSI systems are often expensive and require specialized components, which hinders their widespread adoption.

Solution: The development of miniaturized and more affordable sensors using mass-produced components is making HSI more accessible. Creating multi-purpose systems that can be integrated into existing hospital equipment can also reduce costs.

4. High Data Volume 

The large amount of spectral data generated by HSI systems (known as a “hypercube”) requires significant storage and processing power.

Solution: Dimensionality reduction techniques like Principal Component Analysis (PCA) compress the data by identifying and removing redundant spectral bands. Using edge computing and cloud-based processing can offload the data analysis, allowing for faster, more efficient workflows.

Costs of Medical Hyperspectral Imaging

Medical hyperspectral imaging systems vary widely in price. It typically ranges from USD 10,000 to over USD 100,000. The exact cost depends on several factors, some of which are explained below: 

Factors Influencing Cost

Hyperspectral Camera

• The hyperspectral camera is usually the single biggest cost driver. Prices vary depending on the sensor technology used, the resolution, and the spectral range. 
• Systems designed for visible and near-infrared (VNIR, 400: 1000 nm) are generally less expensive than those operating in the short-wave infrared (SWIR, 900: 2500 nm) range, which require more advanced detectors and cooling systems. 
• Higher resolution and higher sensitivity sensors also increase costs substantially.

System Components

• Beyond the camera, complete HSI systems include broadband or tunable light sources, high-quality lenses, motorized scanning units or filter modules, and powerful data processing software. 
• Each of these components adds to the total system price. Software packages are especially important in clinical or research use, as they must handle large volumes of spectral data and include advanced algorithms for analysis, classification, and visualization.

Technical Specifications 

• Systems that offer high spatial resolution, high sensitivity, and broad spectral coverage are priced higher than entry-level configurations. 
• Faster acquisition systems, such as snapshot cameras designed for real-time imaging in surgical settings, typically cost more than scanning-based systems intended for laboratory use.

Research and Industrial vs. Portable Systems 

• Research-grade systems developed for laboratory, industrial, or medical applications are the most costly, often exceeding USD 50,000-100,000 depending on specifications. 
• Compact and portable HSI systems designed for field applications, education, or preliminary research can be priced closer to USD 10,000-20,000, though they usually come with compromises in resolution, sensitivity, or spectral range.

The high cost of hyperspectral imaging systems is the most significant issue when it comes to widespread adoption in medicine. Hospitals and clinics, particularly those in low- and middle-income countries, may find it difficult to justify such capital expenditure without clear reimbursement pathways or long-term cost savings. 

This makes HSI more common in research and specialized centers than in everyday clinical practice.

Examples of Current Costs

• Entry-level systems: Basic portable or educational HSI systems are available starting at USD 10,000: 15,000.
  
• Research and clinical systems: Advanced systems with higher resolution and broader spectral coverage are typically priced between USD 50,000 and USD 100,000.
  
• Hyperspectral cameras alone: A standalone hyperspectral camera can cost USD 12,000 for an entry-level VNIR model, while advanced models designed for SWIR imaging or surgical applications may exceed USD 50,000.

AI-Imaging Solution – PACScribe by Folio3 Digital Health 

Folio3 Digital Health’s PACScribe is an AI-powered medical imaging solution designed to improve diagnostic accuracy and efficiency. By leveraging advanced AI algorithms during our medical imaging software development, we not only make solutions that analyze images with speed and precision but also generate automated reports. It ensures HIPAA compliance and offers seamless integration with existing healthcare systems through standards like DICOM and HL7. By presenting itself as both innovative and practical, PACScribe shows how a well-positioned solution can address clinical challenges while fitting smoothly into real-world hospital workflows.

Closing Note 

Medical hyperspectral imaging is moving from research laboratories into hospitals. Its ability to noninvasively reveal detailed biochemical information makes it one of the most powerful diagnostic and surgical support tools available today. 

While challenges in cost, standardization, and integration are there, this section is still seeing an upward trajectory. As hardware becomes cheaper and AI-driven analysis faster, HSI will play a central role in precision medicine.

Frequently Asked Questions 

What is medical hyperspectral imaging and its role in the USA healthcare? 

Medical hyperspectral imaging gathers spectral data of multiple wavelengths to analyze organs/tissue noninvasively. It has shown particular success in cancer detection, wound care, and surgical precision without radiation. Its adoption in hospitals like Mayo Clinic supports minimally invasive diagnostics, aligning with the US healthcare’s focus on advanced technology.

What are the main hyperspectral imaging in medical applications? 

Hyperspectral imaging in medical applications includes cancer detection (e.g., skin and breast tumors), diabetic wound assessment, and retinal disease monitoring. It aids surgeries by identifying tumor margins and supports vascular care. Leading institutions like Johns Hopkins use it for real-time, noninvasive diagnostics.

What FDA-approved medical hyperspectral imaging devices are available in the USA? 

FDA-approved medical hyperspectral imaging devices include:

• HyperView™ (cleared in 2016 for tissue oxygenation) 
• Spectral AI’s DeepView SnapShot® (Class I, 2023, for wound imaging). 
• Hypervision Surgical’s HSS is in the FDA’s Safer Technologies Program (2024).

How does medical hyperspectral imaging work in clinical settings?

It uses broadband light and detectors to capture tissue spectral data, processed by AI for real-time analysis. In clinics, it integrates with endoscopes for label-free imaging, compliant with FDA standards. It maps biomarkers like hemoglobin, aiding diagnostics and surgery.

What are the benefits of hyperspectral imaging in medical diagnostics? 

Hyperspectral imaging offers over 90% accuracy in US diagnostics, reducing biopsies and costs. It enables noninvasive, real-time tissue analysis, supporting Medicare’s value-based care. In the USA, it improves outcomes in oncology and wound care with FDA-approved safety.

What are the costs of implementing medical hyperspectral imaging in the hospitals of the USA?

Costs for medical hyperspectral imaging in US hospitals range from USD 10,000 to USD 500,000, plus maintenance and training. ROI is achieved in 1-2 years through reduced procedure times. NIH grants and vendor partnerships help offset costs for US facilities.

How to get FDA approval for a new hyperspectral imaging device? 

To gain FDA approval, submit a 510(k) notification or apply to the Safer Technologies Program, including clinical trial data. Ensure compliance with 21 CFR Part 820 for safety and cybersecurity. The process, guided by the FDA’s CDRH, takes 90-180 days.

Is medical hyperspectral imaging safe and regulated in the USA?

Medical hyperspectral imaging is safe, using nonionizing light with no radiation risks. FDA regulates it through 510(k) clearances and Class I/II designations, ensuring compliance. HIPAA protects patient data, making HSI reliable in US healthcare.

What future trends are expected for hyperspectral imaging in US healthcare by 2030? 

By 2030, hyperspectral imaging in US healthcare will see AI-driven diagnostics with 95% accuracy and portable devices for telemedicine. Multimodal integration with MRI and affordable units under USD 100,000 will expand access. The market is expected to reach USD 1.95 billion, per FDA trends.

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