Sperling Prostate Center

By: Dan Sperling, M.D.

 When a new treatment method or technology is introduced, there is a term for the physicians who first begin to use it with patients. They are called “early adopters” because they are breaking new ground, often long before there is much published data. For example, the breast surgeons who originally began performing breast lumpectomies instead of radical mastectomies were early adopters who took a leap of faith well before there was long term evidence supporting this move. Yet they forever changed women’s medicine.

As an early adopter of image-guided Focal Laser Ablation to treat prostate tumors, it is my responsibility to seek out as much scientific evidence as I can that this treatment is safe, effective, and able to preserve male function on all levels. Although Focal Laser Ablation began in response to the need to target brain tumors, its use in the prostate has not been used long enough or widely enough to produce data on its long term efficacy. Similar to the first breast lumpectomies, the early results are incredibly promising and exciting. However, I continually seek out the work that others are doing by attending conferences and reading peer-reviewed journals. There is a growing body of work on Focal Laser Ablation, and ongoing clinical trials, as the technology itself is being developed.

One way to improve tissue ablation is to create excellent planning software. This can be done by understanding the physics of Focal Laser Ablation, which converts light waves (in this case, laser) into sufficiently intense heat to destroy bodily tissue. It also means grasping the biology of different kinds of bodily tissues. This raises the following planning challenges:

  1. How to deliver the laser to the target
  2. How much heat is being generated (dosimetry)
  3. How to develop the correct shape and size of the heat (conformability)
  4. How to limit the heat so it does not destroy healthy tissue

A French team of researchers1 developed a computer model to simulate the dosimetry and conformation of Focal Laser Ablation in a certain volume of tissue. They assessed the accuracy of the treatment volume calculated by the simulation by comparing it with actual treatment results in laboratory rats, as seen on MRI.

Based on previously published research, as well as their own observations, the authors were aware that the effects of laser on living tissue are affected by the wavelength of the laser, its power and pulse duration, how much blood is present and flowing, and properties of the tissue itself. Thus, planning models for different organs will be complex, plus the treatment must be able to be monitored while it is occurring. Previously published mathematical models have been less than satisfactory.

For the French study, 10 rats were implanted with prostate cancer, which subsequently developed into imageable prostate tumors. For pretreatment planning (placing the laser fiber), they placed each rat under a powerful (7T) MRI unit to capture images of the tumors.

To project their treatment model of thermal destruction, the authors developed complex equations based on the desired physical properties of the laser they would use, and the biological properties of rat prostate glands. They calculated the dosimetry and conformation using the computer model, with the anticipated zone and volume of necrosis (tissue death).

The final step was the comparison of what the simulation predicted and the actual laser effect on the rats’ tumors, as shown on MRI. The areas of correspondence were encouraging, so it was a positive step toward developing a planning program for prostate cancer treatment by Focal Laser Ablation. The authors point out that even a good plan does not guarantee a good treatment, no matter which ablation modality is used.

The authors conclude that Focal Laser Ablation is a promising treatment modality to add to the armamentarium of tumor ablation.



1 Marqa M-F, Colin P, Nevoux P et al. Focal laser ablation of prostate cancer: numerical simulation of temperature and damage distribution. Biomed Eng Online 2011;10:45.

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