Design, implementation and accuracy of a prototype for medical augmented reality.

OBJECTIVE: This paper is focused on prototype development and accuracy evaluation of a medical Augmented Reality (AR) system. The accuracy of such a system is of critical importance for medical use, and is hence considered in detail. We analyze the individual error contributions and the system accuracy of the prototype. MATERIALS AND METHODS: A passive articulated arm is used to track a calibrated end-effector-mounted video camera. The live video view is superimposed in real time with the synchronized graphical view of CT-derived segmented object(s) of interest within a phantom skull. The AR accuracy mostly depends on the accuracy of the tracking technology, the registration procedure, the camera calibration, and the image scanning device (e.g., a CT or MRI scanner). RESULTS: The accuracy of the Microscribe arm was measured to be 0.87 mm. After mounting the camera on the tracking device, the AR accuracy was measured to be 2.74 mm on average (standard deviation = 0.81 mm). After using data from a 2-mm-thick CT scan, the AR error remained essentially the same at an average of 2.75 mm (standard deviation = 1.19 mm). CONCLUSIONS: For neurosurgery, the acceptable error is approximately 2-3 mm, and our prototype approaches these accuracy requirements. The accuracy could be increased with a higher-fidelity tracking system and improved calibration and object registration. The design and methods of this prototype device can be extrapolated to current medical robotics (due to the kinematic similarity) and neuronavigation systems.

Development and human factors analysis of neuronavigation vs. augmented reality.

This paper is focused on the human factors analysis comparing a standard neuronavigation system with an augmented reality system. We use a passive articulated arm (Microscribe, Immersion technology) to track a calibrated end-effector mounted video camera. In real time, we superimpose the live video view with the synchronized graphical view of CT-derived segmented object(s) of interest within a phantom skull. Using the same robotic arm, we have developed a neuronavigation system able to show the end-effector of the arm on orthogonal CT scans. Both the AR and the neuronavigation systems have been shown to be within 3mm of accuracy. A human factors study was conducted in which subjects were asked to draw craniotomies and answer questions to gage their understanding of the phantom objects. The human factors study included 21 subjects and indicated that the subjects performed faster, with more accuracy and less errors using the Augmented Reality interface.

Diagnosis of Wilms' tumor using near-infrared Raman spectroscopy.

PURPOSE: Raman spectroscopy has distinguished malignant from normal tissues in several types of cancer. This is the first report of applying Raman spectroscopy to the diagnosis of Wilms' tumor. METHODS: Specimens of normal kidney, Wilms' tumor, xanthogranuloma, nephrogenic rests, and rhabdoid tumor were collected fresh from the operating room. Specimens of Wilms' tumor, normal kidney, and congenital mesoblastic nephroma were retrieved from the cryobank and thawed to room temperature. At least 12 Raman spectra were collected from each tissue sample. Histologic slides of each specimen were reviewed by pediatric pathologists. A computer algorithm based on discriminant function analysis (DFA) classified the Raman spectra of Wilms' tumor and the normal sample. RESULTS: Four hundred sixty-seven spectra were collected from 41 specimens. Using DFA, Raman spectroscopy differentiated Wilms' tumor from normal with 100% sensitivity and specificity and treated from untreated Wilms' tumor with 100% sensitivity and specificity. Using a DFA model built from cryopreserved specimens but applied to fresh Wilms' and normal samples, the sensitivity and specificity were 93.3% and 90.9%, respectively. CONCLUSION: Raman spectroscopy is an accurate technique for differentiating Wilms' tumor from normal kidney and treated from untreated Wilms' tumor. It has potential to diagnose in minutes what currently takes several hours to days.

Raman spectroscopy detects and distinguishes neuroblastoma and related tissues in fresh and (banked) frozen specimens.

BACKGROUND: Raman spectroscopy has been shown to accurately distinguish different neural crest-derived pediatric tumors. This study tests the ability of Raman spectroscopy to accurately identify cryopreserved tissue specimens using a classification algorithm designed from fresh tumor data and vice versa. METHODS: Fresh specimens of neuroblastoma and other pediatric neural crest tumors were analyzed with Raman spectroscopy. After analysis, the specimens were stored at -80 degrees C. At a later date, the specimens were thawed and reanalyzed by Raman spectroscopy. A computer algorithm was used to classify the spectra from the frozen tissue against a computer model built on the fresh tissue data. This classification process was then reversed, testing fresh spectra against a model built from frozen data. RESULTS: We collected 1114 spectra (862 fresh and 252 frozen) from 62 tissue samples, including 8 normal adrenal glands, 29 neuroblastomas, 14 ganglioneuromas, 8 nerve sheath tumors, and 3 pheochromocytomas. At the tissue level, frozen neuroblastoma, ganglioneuroma, nerve sheath tumor, and pheochromocytoma were distinguished from normal adrenal tissue with 100% sensitivity and specificity. Fresh tissue had the same results except for the misclassification of one specimen of nerve sheath tumor. CONCLUSIONS: The representative spectra show a high correlation between fresh and frozen tissue, and a clear difference between pathologic conditions. Spectra from frozen tissue can be accurately classified against spectra from fresh tissue and vice versa. This modality makes it possible to determine in a few minutes a result that often takes 12 to 36 hours for tissue processing and consideration by a trained pathologist to achieve.

Postimplantation pressure testing and characterization of laser bonded glass/polyimide microjoints.

The stability of the laser bonded titanium coated glass/polyimide microjoints were studied in vivo by implanting on a rat brain surface for 10 days. In the current state, the strength of the joints were measured by a specially designed instrument called "pressure test" equipment where the samples were subjected to a variable pressure load (using high pressure nitrogen) controlled by a pressure regulator. The strength of the joints seems to degrade by about 28% as a result of soaking in rat brain. The bond degradation in rat brain implants is similar compared with those soaked in artificial cerebrospinal fluid (CSF) solution. Polyimide uptakes water through existing pores in it and also water gets in the joint region through the edges of the samples. Water might have caused oxidation of the chemical bonds which are thought to have formed by the laser fabrication process. A separate set of samples were created using same parameters for testing the hermeticity of the laser bonds. The samples were also exposed to rat brain CSF and were tested for hermiticity at the end of 10 days exposure time. It was observed that the implanted samples retained their hermeticity although the bond strength degraded by about 28%.

Raman spectroscopy for neoplastic tissue differentiation: a pilot study.

BACKGROUND: Several changes occur during the transformation of normal tissue to neoplastic tissue. Such changes in molecular composition can be detected by Raman spectroscopy. Raman spectroscopy is a nondestructive method of measuring these changes, which suggests the possibility of real-time diagnosis during medical procedures. METHODS: This study seeks to evaluate the ability of Raman spectra to distinguish tissues. The Raman signatures of normal kidney, lung, and liver tissue samples from pigs and rats were characterized in vitro. Further, a human neuroblastoma and a hepatoblastoma, obtained at resection were also studied. RESULTS: The Raman spectra of the animal samples of kidney, liver, and lung are distinctly different in the intensity distribution of the Raman peaks. Further, the spectra of a given organ from pigs and rats, although similar, were different enough to distinguish between the 2 animals. In the patient tissues, the Raman spectra of normal liver, viable tumor, and fibrotic hepatoblastoma were very different. Fibrotic tissue showed a greater concentration of carotenoids, whereas viable tissue was rich in proteins and nucleic acids. The normal tissue showed both components. Similar differences were also seen in the neuroblastoma tissue. CONCLUSIONS: The results of this study show the potential use of Raman spectroscopy in clinical diagnosis.