Implementation of Fiducial-Based Image Registration in the Cyberknife Robotic System

Image-guided marking techniques in interventional radiology: A review of current evidence

Precise marking of lesions using image-guided techniques is essential, as imprecise targeting of a tumor can result in either insufficient excision/treatment with an increased risk of recurrence, or excessive removal of healthy tissue. Most frequent indications include localization of nonpalpable lesions before surgical resection (i.e., hook-wire localization of pulmonary nodules before video-assisted thoracoscopy) and definite marking of liver metastasis before neoadjuvant therapy. Other indications include marking of hepatocellular carcinomas that are not visible on ultrasound and unenhanced computed tomography before thermal ablation, of bone lesions before surgical excision, and of different visceral tumors before stereotactic radiotherapy. This review presents the different existing indications, assesses their usefulness, gives systematic details on the technique and lastly analyzes the current literature with emphasis on results and complications.

Estimating intrafraction tumor motion during fiducial-based liver stereotactic radiotherapy via an iterative closest point (ICP) algorithm

BACKGROUND

Tumor motion may compromise the accuracy of liver stereotactic radiotherapy. In order to carry out a precise planning, estimating liver tumor motion during radiotherapy has received a lot of attention. Previous approach may have difficult to deal with image data corrupted by noise. The iterative closest point (ICP) algorithm is widely used for estimating the rigid registration of three-dimensional point sets when these data were dense or corrupted. In the light of this, our study estimated the three-dimensional (3D) rigid motion of liver tumors during stereotactic liver radiotherapy using reconstructed 3D coordinates of fiducials based on the ICP algorithm.

METHODS

Four hundred ninety-five pairs of orthogonal kilovoltage (KV) images from the CyberKnife stereo imaging system for 12 patients were used in this study. For each pair of images, the 3D coordinates of fiducial markers inside the liver were calculated via geometric derivations. The 3D coordinates were used to calculate the real-time translational and rotational motion of liver tumors around three axes via an ICP algorithm. The residual error was also investigated both with and without rotational correction.

RESULTS

The translational shifts of liver tumors in left-right (LR), anterior-posterior (AP),and superior-inferior (SI) directions were 2.92 ± 1.98 mm, 5.54 ± 3.12 mm, and 16.22 ± 5.86 mm, respectively; the rotational angles in left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 3.95° ± 3.08°, 4.93° ± 2.90°, and 4.09° ± 1.99°, respectively. Rotational correction decreased 3D fiducial displacement from 1.19 ± 0.35 mm to 0.65 ± 0.24 mm (P<0.001).

CONCLUSIONS

The maximum translational movement occurred in the SI direction. Rotational correction decreased fiducial displacements and increased tumor tracking accuracy.

Automatic tracking of gold seed markers from CBCT image projections in lung and prostate radiotherapy

PURPOSE

To construct a method and software to track gold seed implants in prostate and lung patients undergoing radiotherapy using CBCT image projections.

METHODS

A mathematical model was developed in the MatLab (Mathworks, Natick, USA) environment which uses a combination of discreet cosine transforms and filtering to enhance several edge detection methods for identifying and tracking gold seed fiducial markers in images obtained from Varian (Varian Medical Systems, Palo Alto, USA) and Elekta (Kungstensgatan, Sweden) CBCT projections.

RESULTS

Organ motion was captured for 16 prostate patients and 1 lung patient.

CONCLUSION

Image enhancement and edge detection is capable of automatically tracking markers for up to 98% (Varian) and 79% (Elekta) of CBCT projections for prostate and lung markers however inclusion of excessive bony anatomy (LT and RT LAT) inhibit the ability of the model to accurate determine marker location.