Geometric biopsy plan optimization

Patent metadata

Field	Value
Publication number	US-10751034-B2
Application number	US-201715785825-A
Country	US
Kind code	B2
Filing date	Oct 17, 2017
Priority date	Oct 17, 2016
Publication date	Aug 25, 2020
Grant date	Aug 25, 2020

Abstract

The present invention is directed to a method for calculating tumor detection probability of a biopsy plan and for generating a 3D biopsy plan that maximizes tumor detection probability. A capsule shaped volume is modeled to represent the volume that a biopsy core may sample. An optimization method is used to generate a 3D biopsy plan that maximizes probability of tumor detection for predefined biopsy core numbers and length. Risk of detecting insignificant tumors, also determined by size, and probability of a false negative result is automatically calculated. The present invention also includes a method to determine number and length of biopsy cores required for individual patients determined by the balance of the insignificant/significant probability of detection, prostate size and shape, based upon the previously explained 3D biopsy plan generation method.

First claim

The invention claimed is:

1. A method of biopsy planning comprising:
calculating significant and insignificant tumor detection probability, wherein significance is based on tumor size;
generating a three-dimensional biopsy plan that increases the probability of the significant and insignificant tumor detection probability;
calculating probability of a false negative detection of tumor using the three-dimensional biopsy plan to create a revised three-dimensional biopsy plan; and
determining a number and length of biopsy cores required to execute the revised three-dimensional biopsy plan.

2. The method of claim 1 further comprising implementing the method using a non-transitory computer readable medium.

3. The method of claim 1 further comprising:
setting a bounding box for a tumor detection area and a voxel size to discretize this volume at a predetermined level of resolution;
iterating through all voxels;
checking if a voxel center is within the tumor detection area, and if so add it to a set Γ;
iterating through all voxels of set Γ;
verifying if the voxel center falls within any of the biopsy cores of a set Π;
counting the voxel with a center that falls within any of the biopsy cores of set Π as sampled by adding it to a set Ω; and
calculating tumor prediction probability as the ratio of the number of elements of the Ω and Γ sets.

4. The method of claim 1 further comprising:
setting a volume of a tumor detection area and a voxel size to discretize the volume of the tumor detection area at a predetermined level of resolution to a set of voxels Γ;
defining the tumor detection area of a biopsy core as a capsule surrounding the biopsy core with a cylindrical volume having hemispherical end caps of the diameter of the tumor to be detected;
iterating through all voxels of Γ and checking if a voxel center is within the tumor detection area of the biopsy cores of the plan;
adding the voxel center to the sampled voxel set Ω; and
calculating tumor prediction probability as the ratio of the number of elements of the detected voxel set Ω and tumor search area voxel set Γ.

5. The method of claim 1 further comprising detecting tumors in the prostate gland.

6. The method of claim 1 further comprising detecting tumors in any organ with a boundary that is segmentable as a surface.

7. The method of claim 1 further comprising representing the biopsy cores as a capsule with a cylindrical volume having hemispherical end caps.

8. The method of claim 1 further comprising setting a tumor detection area.

9. The method of claim 1 further comprising generating the three-dimensional biopsy plan for significant tumors for a predefined number of biopsy cores and lengths.

10. The method of claim 1 further comprising generating the three-dimensional biopsy plan for insignificant tumors for a predefined number of biopsy cores and lengths.

11. The method of claim 1 further comprising defining a tumor detection area of a biopsy core as a capsule surrounding the biopsy core with a cylindrical volume having hemispherical end caps of the diameter of a tumor to be detected.

12. A system for biopsy planning comprising:
a source of image data capable of reconstructing a target organ in three-dimensions;
a non-transitory computer readable medium programmed for:
calculating significant and insignificant tumor detection probability from the image data, wherein significance is based on tumor size;
generating a three-dimensional biopsy plan that increases the probability of the significant and insignificant tumor detection probability;
calculating probability of a false negative detection of tumor using the three-dimensional biopsy plan to create a revised three-dimensional biopsy plan; and
determining a number and length of biopsy cores required to execute the revised three-dimensional biopsy plan.

13. The system of claim 12 further comprising a computing device.

14. The system of claim 12 further comprising:
setting a bounding box for a tumor detection area and a voxel size to discretize this volume at a predetermined level of resolution;
iterating through all voxels;
checking if a voxel center is within the tumor detection area, and if so add it to a set Γ;
iterating through all voxels of set Γ;
verifying if the voxel center falls within any of the biopsy cores of a set Π;
counting the voxel with a center that falls within any of the biopsy cores of set Π as sampled by adding it to a set Ω; and
calculating tumor prediction probability as the ratio of the number of elements of the Ω and Γ sets.

15. The system of claim 12 further comprising:
setting a volume of a tumor detection area and a voxel size to discretize the volume of the tumor detection area at a predetermined level of resolution to a set of voxels Γ;
defining the tumor detection area of a biopsy core as a capsule surrounding the biopsy core with a cylindrical volume having hemispherical end caps of the diameter of the tumor to be detected;
iterating through all voxels of Γ and checking if a voxel center is within the tumor detection area of the biopsy cores of the plan;
adding the voxel center to the sampled voxel set Ω; and
calculating tumor prediction probability as the ratio of the number of elements of the detected voxel set Ω and tumor search area voxel set Γ.

16. The system of claim 12 further comprising detecting tumors in the prostate gland.

17. The system of claim 12 further comprising detecting tumors in any organ with a boundary that is segmentable as a surface.

18. The system of claim 12 further comprising representing the biopsy cores as a capsule with a cylindrical volume having hemispherical end caps.

19. The system of claim 12 further comprising setting a tumor detection area.

20. The system of claim 12 further comprising a biopsy device.

Assignees

• Univ Johns Hopkins
• The Johna Hopkins Univ

Inventors

• Stoianovici Dan
• Chang Doyoung
• Han Misop

Classifications

• A61B5/4381

  Prostate evaluation or disorder diagnosis · CPC title

• A61B5/7275

  Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor · CPC title

• A61B2576/02

  specially adapted for a particular organ or body part · CPC title

• A61B2034/107

  Visualisation of planned trajectories or target regions · CPC title

• A61B2034/105

  Modelling of the patient, e.g. for ligaments or bones · CPC title