Minimally Invasive Cochlear Implantation Assisted by Bi-planar Device: An Exploratory Feasibility Study in vitro

Drilling accuracy evaluation of a mouldable surgical targeting system for minimally invasive access to anatomic targets in the temporal bone

PURPOSE

Minimally invasive cochlear implant surgery using a micro-stereotactic surgical targeting system with on-site moulding of the template aims for a reliable, less experience-dependent access to the inner ear under maximal reduction of trauma to anatomic structures. We present an accuracy evaluation of our system in ex-vivo testing.

METHODS

Eleven drilling experiments were performed on four cadaveric temporal bone specimens. The process involved preoperative imaging after affixing the reference frame to the skull, planning of a safe trajectory preserving relevant anatomical structures, customization of the surgical template, execution of the guided drilling and postoperative imaging for determination of the drilling accuracy. Deviation between the drilled and desired trajectories was measured at different depths.

RESULTS

All drilling experiments were successfully performed. Other than purposely sacrificing the chorda tympani in one experiment, no other relevant anatomy, such as facial nerve, chorda tympani, ossicles or external auditory canal were harmed. Deviation between the desired and achieved path was found to be 0.25 ± 0.16 mm at skulls' surface and 0.51 ± 0.35 mm at the target level. The closest distance of the drilled trajectories' outer circumference to the facial nerve was 0.44 mm.

CONCLUSIONS

We demonstrated the usability for drilling to the middle ear on human cadaveric specimen in a pre-clinical setting. Accuracy proved to be suitable for many applications such as procedures within the field of image-guided neurosurgery. Promising approaches to reach sufficient submillimetre accuracy for CI surgery have been outlined.

Fully automated segmentation in temporal bone CT with neural network: a preliminary assessment study

BACKGROUND

Segmentation of important structures in temporal bone CT is the basis of image-guided otologic surgery. Manual segmentation of temporal bone CT is time- consuming and laborious. We assessed the feasibility and generalization ability of a proposed deep learning model for automated segmentation of critical structures in temporal bone CT scans.

METHODS

Thirty-nine temporal bone CT volumes including 58 ears were divided into normal (n = 20) and abnormal groups (n = 38). Ossicular chain disruption (n = 10), facial nerve covering vestibular window (n = 10), and Mondini dysplasia (n = 18) were included in abnormal group. All facial nerves, auditory ossicles, and labyrinths of the normal group were manually segmented. For the abnormal group, aberrant structures were manually segmented. Temporal bone CT data were imported into the network in unmarked form. The Dice coefficient (DC) and average symmetric surface distance (ASSD) were used to evaluate the accuracy of automatic segmentation.

RESULTS

In the normal group, the mean values of DC and ASSD were respectively 0.703, and 0.250 mm for the facial nerve; 0.910, and 0.081 mm for the labyrinth; and 0.855, and 0.107 mm for the ossicles. In the abnormal group, the mean values of DC and ASSD were respectively 0.506, and 1.049 mm for the malformed facial nerve; 0.775, and 0.298 mm for the deformed labyrinth; and 0.698, and 1.385 mm for the aberrant ossicles.

CONCLUSIONS

The proposed model has good generalization ability, which highlights the promise of this approach for otologist education, disease diagnosis, and preoperative planning for image-guided otology surgery.

Image-guided cochlear access by non-invasive registration: a cadaveric feasibility study

Image-guided cochlear implant surgery is expected to reduce volume of mastoidectomy, accelerate recovery, and improve safety. The purpose of this study was to investigate the safety and effectiveness of image-guided cochlear implant surgery by a non-invasive registration method, in a cadaveric study. We developed a visual positioning frame that can utilize the maxillary dentition as a registration tool and completed the tunnels experiment on 5 cadaver specimens (8 cases in total). The accuracy of the entry point and the target point were 0.471 ± 0.276 mm and 0.671 ± 0.268 mm, respectively. The shortest distance from the margin of the tunnel to the facial nerve and the ossicular chain were 0.790 ± 0.709 mm and 1.960 ± 0.630 mm, respectively. All facial nerves, tympanic membranes, and ossicular chains were completely preserved. Using this approach, high accuracy was achieved in this preliminary study, suggesting that the non-invasive registration method can meet the accuracy requirements for cochlear implant surgery. Based on the above accuracy, we speculate that our method can also be applied to neurosurgery, orbitofacial surgery, lateral skull base surgery, and anterior skull base surgery with satisfactory accuracy.

Influence of patient-specific anatomy on medical computed tomography and risk evaluation of minimally invasive surgery at the otobasis

PURPOSE

With the increasing use of new minimally invasive approaches in temporal bone surgery, the need arises for evaluation of the risk of injury to sensitive anatomical structures. The factors that influence the measurement uncertainty (variation in representation of position and shape of anatomical structures) of imaging are of relevance. We investigate the effect of patients' anatomy on the measurement uncertainty of medical CT.

METHODS

Six formalin-fixed temporal bones were used, fiducial markers were bone-implanted, and 20 CT scans of each temporal bone were generated. Surgically threatened anatomical structures of importance were defined. Manual segmentation was performed to create 3D surface models, and different Gaussian filters were applied. Analysis points were established along the border of the superior semicircular canal to determine the deviation between the 3D images of the labyrinth. The standard uncertainty was calculated, and one-way analysis of variance was performed (significance level = 5%) to evaluate the effect of certain factors (patient, side, Gaussian filter) on the measurement uncertainty.

RESULTS

The influence of patient-specific anatomy on the measurement uncertainty of medical CT (p = 0.049) was demonstrated for the first time. The applied Gaussian filter (p = 0.622) and the patient's side (p = 0.341) showed no significant effect.

CONCLUSION

The applied method and the results of the statistical analysis suggest that the patient's individual anatomical conditions affect the measurement uncertainty of medical CT. Thus, the patient's anatomy must be considered as an important influencing factor during risk evaluation concerning minimally invasive and image-guided surgery.