This talk was given as the keynote at the 2009 CSCBC (Fourth Canadian Student Conference on Biomecical Computing.)
In the beginning, there were X-rays. They were the mainstay of medical imaging till the 70s, although ultrasound started in the 50’s, it didn’t take off for a while. MRI appeared in the 80’s. Tomography in 1973.
Of course, all of this required computers. [A bit of the history of computing.]
Computer Tomography. The fundamentals go back to 1917 – “The Radon Transform”, which are the mathematical underpinnings of CT.
Ronald Bracewell made contributions in 1956, with Radio Astronomer used this to reconstruct radio sources. He recognized that fourier transform relation between signals and reconstruction. He developed math very similar to what’s used for CT reconstruction.. he was working on a calculator (3 instructions /min)!
Sir Godfrey Hounsfield, Nobel prize winner in 1979. He was an engineer for EMI (the music producer!) Surprisingly, it was the profit of the Beatle’s albums that funded this research.
Dr Peters himself began working on CT in the late 1960’s. “Figure out a way sof measuring bone-density in the forearm using ultrasound….” (in the lab of Richard Bates, 1929-1990). That approach was a total disaster, so turned to X-ray. Everything in Dr. Bates lab started with Fourier transforms, so his research interests gave him a natural connection with Bracewell at Stanford… The same math that Bracewell was working on made the jump to CT.
The first “object” they used to do was with sheep bones – in New Zealand – what else??
The first reconstruction required 20 radiographs, a densitometer scan, a manual digitization, and 20 minutes on an IBM 360. “Pretty pictures but they will never replace radiographs” – NZ Radiologizt 1972.
The following months, Hounsfiled reports on invention of EMI scanner – scooping Dr. Peters PhD project. However, there were still lots of things to work on. “If you find you’re scooped, don’t give up there are plenty of problems to be solved…” “Don’t be afraid to look outside your field.”
How does CT work? The central slice Theorem. Take an X-ray projection, fourier transform it, so instead of inverting the matrix, you can do the whole thing in the fourier transform space.
Filtered Back Projection: FT -> | rho | -> Inv FT.
This all leads to the clinical acceptance of CT. Shows us the first CT image ever. His radiology colleagues were less than enthusiastic. However, Dr. James Ambrose in London, saw the benefits of the EMI scanner. Of course, EMI only though there will ever be a need for 6 CT machines.
First CT was just for the head. It took about 80 seconds of scanning, and about the same to recreate the image.
His first job was to “build a CT scanner”, with a budget of $20,000, in 1975-78.
in 1974: 80×80 2009 : 1024×1024
3mm pixels less than .5mm pixels
13mm thick slices
less than 1mm thick slices
What good is CT scanning? Good for scanning density. Great for bones, good for high constrast, not so good in brain (poor contrast between white and grey matter), high spacial resolution,
tradeoff, high cost of radiation dose to patient.
Use for image-guidance for modeling and for pre-operative patients. Not used during surgery, however.
CT Angiography is one example of the power of the technique. You can use contrast dyes, and then collect images to observe many details, and reconstruct vessels. You can even look for occlusions in the heart in blood vessels.
Where is this going? Now working on robotically assisted CABG. Stereo visualization systems.
Currently working to optimize robot tools + CT combination. Improper thoracic port placement, and optimize patient selection.
Pre-operative imaging can be used to measure distances and optimize locations of cuts. This allows the doctor to work without opening the rib cage. They can now use a laser to locate and identify where the cuts should be made, in a computer controlled manner.
Has roots in physics and chemistry labs. NMR imaging built on mathematical foundations similar to CT. Some “nifty tricks” can be used to make images from it. Dropped “N” because nuclear wasn’t politically correct.
In 1975, Paul Lautebur presented “Zeumatography”. Magnets, water, tubes… confusing everyone! Seemed very far away from CT scanning. Most people thought he was WAY out there. He ended up sharing a Nobel Prize.
Sr Peter Mansfield in 1980 produced an MRI of a human using this method – although it didn’t look much better than the first CT.
[Explanation of how NMR works – and how Fourier transforms and gradients are applied.]
More than anything else, MRI combines more scientific disciplines than anything else he can think of.
We are now at 35 years of MRI. Originally said that MRI would never catch on. We now generate high resolution 7 Tesla images. [Very impressive pictures]
Discussion of Quenching of the magnets… yes, boiling off the liquid helium is bad. Showing image of how a modern MRI works.
What good is MRI? Well, the best signals come from water (protons), looking at T1 and T2 relaxation times. Have good soft tissue contrast – including white and grey matter brain cells. High spatial resolution, high temporal resolution. No radiation dose, great use for image-guidance.
(As far as we can tell, the human body does not react negatively to the magnetic fields we generate.)
Can also be used for inter-operative techniques, however everything used must be non-magnetic. Several neat MRI scanners exist for this purpose, including robots that can do MRI using just the “fringe fields” from a nearby MRI machine.
Can be used for:
- MRA – Angiography (vascular system),
- MRS – Spectroscopy (images of brain and muscle metabolism)
- fMRI – Functional magnetic resonance imagine (image of brain function)
- PW MRI – Perfusion-Weighted imaging. (Blood flow in ischemia and stroke)
- DW MRI – Diffusion-Weighted imaging (water flow along nerve pathways – images of nerve bundles).
FMRI: Looks at regions that demand more oxygen. Can differentiate 1% changes, and then can correlate signal intensity with some task (recognition, or functional) Can be used to avoid critical areas during surgery.
Diffusion Tensor: looks at the diffusion of water, resulting in technique of “Tractography”, which can be used to identify all of the nerve pathways, which can then be avoided during surgery.
There are applications for helping to avoid the symptoms of Parkinson’s. Mapped hundreds of patients to find best location, and now can use this information to tell them exactly where to place the electrodes in new patients.
[Showing an image in which they use X windows for their computer imaging – go *nix.]
Two minutes of Ultrasound: [How it works.] Typical sonar, and then reconstruct. “Reflections along line of sight.” Now, each ultrasound uses various focal lengths, several transducers, etc, etc. All done electronically now.
The beam has an interesting shape – not conical, as I had always though.
Original Ultrasound used an oscilloscope with long persistence, and they’d use a Polaroid camera to take pictures of it. The ultrasound head used joints to know where it was to graph points on the oscilloscope. (Long before computers were available.)
Advantage: Images interfaces between tissues, inexpensive, portable, realtime 2D/3D, does not pass through air or bone. Can be used to measure changes of reflective frequency, so blood flow direction and speed. Can be used for image-guidance – can be much more useful when combined with MRI, etc.
Disadvantage: difficult to interpret.
In the last year, 3d, dynamic ultrasound is now available. You can put a probe in the ultrasound and watch the heart valves.
For intra-cardiac intervention: Create model from pre-op imaging, register model to patient, use trans-esophogeal ultrasound for real-time image guidance, introduce instruments through chest/heart wall, magnetically track ultrasound and instruments, display in VR environment.
[Very cool demonstrations of the technology.] [Now showing another VR environment using windows XP. Bleh.]
Other modalities: PET – positron emission tomography, SPECT,
One important tool, now, is the fusion of several of these techniques: MRI-PET, CT-MRI, US-MRI.
Conclusion: CT and MRI provide high resolution 3d/4d data, but can’t be used well in operating room. US is inexpensive and 2d/3d imaging, but really hard to get context.
Future: image-guided procedures, deformable models with US synchronization. Challenges: tracking intra-op imaging devices and real-time registration. Deformation of pre-op models to intra-op anatomy.