Percutaneous CT biopsy of chest lesions: an in vitro analysis of the effect of partial volume averaging on needle positioning.
OBJECTIVE
Accurate needle biopsy of chest lesions requires knowledge of both the direction of the needle and the exact location of the tip of the needle. The purpose of this study was to analyze and illustrate the relationships between the location of the nodule, the size of the nodule, the CT slice thickness, and the needle length. An understanding of these relationships should minimize localization errors due to partial volume averaging and thus increase the accuracy of biopsies.


METHODS
Geometric principles were used to determine mathematical relationships between the size of the nodule, the CT slice thickness, the length of the needle, and the direction of the needle. A styrofoam model simulating the patient and the lesion to be sampled was developed so that radiographs and CT scans of the model could be obtained with different needle placements to illustrate the phenomenon of partial volume averaging.


RESULTS
The accuracy of the CT-guided biopsy can be increased by reducing the CT slice thickness, using longer needles, minimizing the distance to be traversed within the patient, and maximizing the portion of the lesion contained in the CT section used for needle tip localization. Mathematical equations developed from the in vitro model can be used to select the most appropriate CT section and the best length and angle of the needle. CT scans of the model illustrate the use of these equations.


CONCLUSIONS
We found these principles helpful in improving the accuracy of CT needle biopsies, particularly when the lesions are very small and when an angled approach is required. Ideally, the smallest possible CT slice thickness and the longest possible needles should be used, but some practical limitations exist.
Yankelevitz
D F
DF
Department of Radiology, New York Hospital-Cornell Medical Center, NY 10021.
Henschke
C I
CI
Davis
S D
SD
D001707:Biopsy, Needle / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D015641:Radiography, Interventional; D013896:Thoracic Diseases / Q000473:pathology*; D014057:Tomography, X-Ray Computed