OBJECTIVES: Capture the human inner-ear malformation types in 3D by segmenting the inner-ear structures from clinical CT (computed tomography) and MR (magnetic resonance) image datasets. Volumetric analysis was done to find the variations in the volume of cochlear part alone from complete inner-ear followed by 3D printing from the 3D segmented models. MATERIALS and METHODS: Using 3D slicer freeware, the complete inner-ear structures were segmented from anonymized CT and MR image by setting a tight grey-scale threshold to avoid capturing unwanted structures followed by volumetric analysis of the cochlear part alone. 3D printing was done using Form labs desktop 3D printer. RESULTS: We identified 2x normal anatomy (NA) cochlea, 1x enlarged vestibular aqueduct syndrome (EVAS), 3x incomplete partition (IP) type-I, 4x IP type-II, 3x IP type-III, 5x common cavity (CC) and 5x cochlear hypoplasia (CH). 3D segmented models along with the 3D printed models showed huge variation in size, shape and the anatomy among the image data-sets analyzed. Volumetric analysis showed that on average, volume of CC was above 150mm3, volume of CH fell below 80mm3, Volume of NA, EVAS and IP-I were all around 85-105mm3 whereas the volume of IP-II was around 50mm3. CONCLUSION: Visualizing human inner-ear malformation types in 3D both as computer models and as 3D printed models is a whole-new experience as demonstrated in this study. The volumetric analysis showed a huge variation among the volume of cochlear part alone among the malformation types. Cite this article as: Dhanasingh A, Dietz A, Jolly C, Roland P. Human Inner-ear Malformation Types Captured in 3D. J Int Adv Otol 2019; 15(1): 77-82.

Purpose: To evaluate the insertion results and hearing preservation of a novel slim modiolar electrode (SME) in patients with residual hearing. Methods: We retrospectively collected the data from the medical files of 17 patients (18 ears) implanted with a SME. All patients had functional low frequency hearing (PTA _{(0.125–0.5 kHz)} ≤ 80 dB HL). The insertion results were re-examined from the postoperative cone-beam computed tomography scans. Postoperative thresholds were obtained at the time of switch-on of the sound processors (mean 43 days) and at latest follow-up (mean 582 days). The speech recognition in noise was measured with the Finnish matrix sentence test preoperatively and at follow-up. Results: The mean insertion depth angle (IDA) was 395°. Neither scala dislocations nor tip fold over were detected. There were no total hearing losses. Functional low-frequency hearing was preserved in 15/18 (83%) ears at switch-on and in 14/17 (82%) ears at follow-up. According to HEARRING classification, 55% (10/18) had complete HP at switch-on and 41% (7/17) still at follow-up. Thirteen patients (14 ears) were initially fitted with electric–acoustic stimulation and seven patients (8 ears) continued to use it after follow-up. Conclusions: The preliminary hearing preservation results with the SME were more favorable than reported for other perimodiolar electrodes. The results show that the array may also be feasible for electro-acoustic stimulation; it is beneficial in that it provides adequate cochlear coverage for pure electrical stimulation in the event of postoperative or progressive hearing loss.

The Finnish Matrix Test is the first sentence test in noise for the Finnish language. It was developed according to the HearCom standards and provides reliable speech intelligibility measurements with highly comparable results with the other international matrix tests. The aim of the study was to develop an accurate speech intelligibility test in noise for the Finnish language that is comparable across different languages. We chose a matrix sentence test, which comprises a base matrix of 10 names, verbs, numerals, adjectives and nouns. Test lists were formed from this matrix quasi randomly, providing test sentences of the same syntactical structure. The speech material corresponds to everyday spoken language and the phoneme distribution is representative of the Finnish language. The test was optimized by determining the speech recognition thresholds of the individual words and subsequently by applying level corrections of up to ±3 dB. Evaluation measurements were performed to check the equivalence of the different test lists with respect to speech intelligibility and to provide reference values for further clinical applications. After training, the mean speech recognition threshold (SRT) and the slope of the final test lists were -10.1 ± 0.1 dB signal-to-noise-ratio (SNR)and 16.7 ± 1.2%/dB, respectively (measurements at constant level; inter-list variability). The mean SRT and the slope of the test subjects were -10.1 ± 0.7 dB SNR and 17.5 ± 2.2%/dB (measurements at constant level; inter-subject variability). The expected SRT range for normal-hearing young adults for adaptive measurements is -9.7 ± 0.7 dB SNR.