Current 3D imaging systems for brain surgery are too slow to be effective in an operating room setting. All current effective methods for demarcation of tumor margins are preoperative, and cannot account for shift and deformation of tissue during resection.

Design of a Hadamard Transform Spectral Imaging System for Brain Tumor Resection Guidance

Paul Holcomb, Tasha Nalywajko, Melissa WaldenAdvisors: Anita Mahadevan-Jansen, Ph.D.; Steven Gebhart

Vanderbilt University Department of Biomedical Engineering

Construct prototype imaging system using digital micro-mirror device and Hadamard transform to verify effectiveness of imaging technique.

Design Objective

Problem Definition

Why is this important?

• Over 18,000 people diagnosed with brain tumors every year; 71% mortality rate

• Correlation between complete resection of tumors and improved prognosis

• Complete resection requires knowing the location of the tumor, especially tumor margins

• Imaging in a clinical setting should be fast

Benign tumor

Primary malignant

Secondary malignant

Cost/Benefit Analysis

• Costs:– OR cost: $10K - $15K per surgery

(depending on length)– ICU: $2152/24 hrs– Floor: $1360/24 hrs– Time spent in surgery– Time spent recovering:

• 1 week in hospital• 4-8 weeks rest before resuming full

activities

Comparison of prognosis based on percentage of tumor resection from low

grade GBM patients

LaCroix et al. J. Neurosurg. Vol. 95 (2001); pp. 190-198.

•Patient benefits:–Increased prognosis–Shorter surgery time–Less time in hospital (ICU or floor)–Less post-surgical treatment required

Time Cost Time CostOperating

Room2.91 hr $14,550 2.25 hr $11,250

ICU bed 2 days $4,304 2 days $4,304 Floor bed 3 days $4,080 2 days $2,720

Totals 6 days $22,934 5 days $18,274 $4,660

$86.2 millionTotal Difference (18,500 patients)Difference per patient

With two pathology tests & preoperative

imaging

With no pathology tests & intraoperative system

Comparison of tumor resection costs with preoperative and intraoperative imagingProof of Principle

•Spectral difference between tumor tissue and healthy tissue

•Point source measurements taken in vitro and in vivo

•Five sites measured by diffuse reflectance and confirmed by pathology as cancerous were missed by MRI

Lin et al. J Photochemistry and Photobiology, Vol. 73 (2001); pp. 396-402.

Demarcation of healthy brain tissue and tumor margins in vivo using point source measurement of diffuse reflectance

Design Criteria

• Must produce an image quickly• Must accurately reproduce area of interest in the brain• Must distinguish healthy versus tumor tissue• Must be small enough to be usable in an operating room setting• Must interface with operating microscope

Hadamard Transform and DMD

Hadamard Matrix Example

Inverse Hadamard Transform

Digital Micro-mirror Device

Comparison of Fourier (left) and Hadamard (right) imaging of a satellite photo.Wuttig and Riesenburg, “Sensitive Hadamard Transform Imaging Spectrometer”

• SNR with Hadamard: √n • SNR with S-Matrix: (√n)/2

System Diagram

1

1

1

1-1

-1-1

-1

Collect reflected light, demagnify to less than 10mm

square, and focus on DMD

(Stage 1)

Illuminate sample with white light

Apply Hadamard matrix (or S Matrix) using DMD

Compress image to 160um x 8.2mm line

(Stage 2)

Disperse light spectrally using spectrograph and collect image using CCD camera

(Stage 3)

Apply inverse Hadamard transform using computer

X

Y

Spectrum

Future Directions

Acknowledgements

We would like to thank Dr. Anita Mahadevan-Jansen, Steve Gebhart, and Dr. Paul King for their support in this endeavor.

This project was made possible through funds provided by the NIH R01 grant CA085989.

• Compression stage needs to be redesigned due to the diffuse nature of the image source

•Spectrograph needs to be modified to collect the desired wavelength range and to interface with a faster CCD camera than currently installed

• System needs to be reduced in size for use in operating room

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Light Source & Test Image

• Diffuse white light source used to illuminate sample

• Light box with 100mm focal length lens aperture used to focus white light and remove stray light interference from white light source

• Initial test image for focusing is a 3mm x 10mm line drawn on white optical flat

Light box (left) containing white light source and lens for focusing light on optical flat with

test image (red circle, right)

Stage 1 Design

• Camera lens (28mm focal length) collects diffuse reflectance from flat at a distance of 8” (203.2mm)

• Black flat installed around camera lens to block stray reflected light from test source

•50mm focal length achromatic doublet lens focuses collected light from the camera lens onto the DMD

Left: Camera lens from Stage 1 (left) integrated into light source & test image setup

Right: Stage 1 setup including camera lens (left), focusing lens (middle) and DMD (right)

DMD & Stage 2 Design

• Digital micro-mirror device integrated into the main system after Stage 1 to apply the Hadamard matrix (or S-matrix)

• Stage 2 image compression system initially designed to function with collimated light, and is currently being redesigned

Digital micro-mirror device and control circuitry for computer interface

Conclusions

• System must be designed to handle diffuse light

• System must be effectively shielded to reduce stray light interference

• Image transformation using DMD is feasible, but compression of signal is difficult to obtain within a small path length