Considering the emerging advantages related to da Vinci Xi robotic platform, the aim of this study is to compare for the first time the operative outcomes of this tool to the previous da Vinci Si during transoral robotic surgery (TORS), both performed for squamous cell carcinomas (SCC) of the base of tongue (BOT). Intra- and peri-operative outcomes of eight patients with early stage (T1–T2) of the BOT carcinoma and undergoing TORS by means of the da Vinci Xi robotic platform (Xi-TORS) are compared with the da Vinci Si group ones (Si-TORS). With respect to Si-TORS group, Xi-TORS group demonstrated a significantly shorter overall operative time, console time, and intraoperative blood loss, as well as peri-operative pain intensity and length of mean hospital stays and nasogastric tube positioning. Considering recent advantages offered by surgical robotic techniques, the da Vinci Xi Surgical System preliminary outcomes could suggest its possible future routine implementation in BOT squamous cell carcinoma procedures.

Transoral robotic surgery for the base of tongue squamous cell carcinoma: a preliminary comparison between da Vinci Xi and Si.

Recent advancements in bioelectronic devices to interface with the peripheral vestibular system.

As a follow-up to the studies by Vaerenberg et al. (Sci World J 501738:1–12, 2014) and Browning et al. (Cochlear Implant Int 21(3):1–13, 2020), who used questionnaires, we determined whether there are between-centre variations in the fitting of cochlear implants by analysing the methodology, fitting parameters and hearing results of patients from four centres with real data. The purpose of this study is to highlight the lack of streamlined mapping guides and outcome measures with respect to cochlear implant (CI) fittings. A retrospective study with ninety-seven post-lingual adults with a nucleus cochlear implant placed between 2003 and 2013 was included to ensure at least 5 years of follow-up. The studied data were as follows: the methodology, including the fitter’s professional background, the method of activation, the sequence of fitting sessions, the objectives measures and hearing outcomes; and the fitting parameters, including the speech processors, programming strategy, stimulation mode, T and C levels, T-SPL and C-SPL, maxima, pulse width, loudness growth and hearing results. This investigation highlights some common practices across professionals and CI centres: the activation of a CI is behavioural; impedances are systematically measured at each fitting; and some parameters are rarely modified. However, there are also differences, either between centres, such as the sequences of fitting sessions (p < 0.05) or their approach to spectral bands (p < 0.05), or even within centres, such as the policy regarding T and C levels at high frequencies compared to those at low and mid-frequencies. There are important variations between and within centres that reflect a lack of CI-related policies and outcome measures in the fitting of CI. NCT03700268

Variability of fitting parameters across cochlear implant centres.

We determined the effects of intensifying useful frequency and time regions (target frequency and time ranges) and removing detrimental frequency and time regions (conflicting frequency and time ranges) for consonant enhancement. Thirteen normal-hearing listeners participated in two experiments. In the first experiment, we identified target and conflicting frequency and time ranges for each consonant under a quiet, dichotic listening condition by analyzing consonant confusion matrices. The target frequency range was defined as the frequency range that provided the highest performance and decreased 40% from the peak performance from both high- and low-pass filtering schemes. The conflicting frequency range was defined as the frequency range that yielded the peak errors of the most confused consonants and 20% less than the peak error from both filtering schemes. The target time range was defined as a consonant segment that provided the highest performance and decreased 40% from that peak performance when the duration of the consonant was systematically truncated from the onset. The conflicting time ranges were defined on the coincided target time range because, if they temporarily coincide, the conflicting frequency ranges would be the most detrimental factor affecting the target frequency ranges. In the second experiment, consonant recognition was binaurally measured in noise under three signal processing conditions: unprocessed, intensified target ranges by 6 dB gain (target), and combined intensified target and removed conflicting ranges (target-conflicting). Results showed that consonant recognition improved significantly with the target condition but greatly deteriorated with the target-conflicting condition. The target condition helped transmit voicing and manner cues, while the target-conflicting condition limited the transmission of these cues. Confusion analyses showed that the effect of the signal processing on consonant improvement was consonant-specific: the unprocessed condition was the best for /da, pa, ma, sa/; the target condition was the best for /ga, fa, va, za, ʒa/; and the target-conflicting condition was the best for /na, ʃa/. Perception of /ba, ta, ka/ was independent of the signal processing. The results suggest that enhancing the target ranges is an efficient way to improve consonant recognition, while removing conflicting ranges negatively impacts consonant recognition.

Effect of the Target and Conflicting Frequency and Time Ranges on Consonant Enhancement in Normal-Hearing Listeners

Cochlear implants (CIs) are the treatment of choice for patients with severe to profound hearing loss. The hearing results, however, considerably vary across patients. This may partly be due to variability in the CI fitting. We investigated the effect of FOX, a software tool to program CIs using artificial intelligence (AI), on hearing outcomes.Forty-seven experienced CI patients who came to our tertiary CI center for their annual follow-up between 2017 and 2020 were recruited for this study. They received a new CI map created by the AI software tool. CI parameters and auditory outcomes obtained with this new map were compared with those of the initial manual map after 15 days of take-home experience. Within-patient differences were assessed. At the end of the study, the patients were offered a choice to continue using the AI map or to revert to their old manual map.Several auditory outcomes improved with the AI map, namely, pure tone audiometric threshold at 6,000 Hz (median improvement 10 dB, range = -20 to 50 dB, Z = -2.608, p = 0.008), phonemic discrimination scores (median improvement 10%, range = 0% to 30%, Z = -4.061, p = 0.001), and soft-intensity (median improvement of 10%, range = -20% to 90%, Z = -4.412, p < 0.001) to normal-intensity (median improvement of 10%, range = -30% to 60%, Z = -3.35, p < 0.001) speech audiometric scores.The AI-assisted CI mapping model as a potential assistive tool may improve audiological outcomes for experienced CI patients, including high-frequency pure tone audiometry and audiometric speech scores at low and normal presentation levels.Clinical trial registration: NCT03700268. 

Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients

Objective: To assess whether CI programming by means of a software application using artificial intelligence (AI), FOX®, may improve cochlear implant (CI) performance. Patients: Two adult CI recipients who had mixed auditory results with their manual fitting were selected for an AI-assisted fitting. Even after 17 months CI experience and 19 manual fitting sessions, the first subject hadn't developed open set word recognition. The second subject, after 9 months of manual fitting, had developed good open set word recognition, but his scores remained poor at soft and loud presentation levels. Main outcome measure(s): Cochlear implant fitting parameters, pure tone thresholds, bisyllabic word recognition, phonemic discrimination scores and loudness scaling curves. Results: For subject 1, a first approach trying to optimize the home maps by means of AI-proposed adaptations was not successful whereas a second approach based on the use of Automaps (an AI approach based on universal, i.e. population based group statistics) during 3 months allowed the development of open set word recognition. For subject 2, the word recognition scores improved at soft and loud intensities with the AI suggestions. The AI-suggested modifications seem to be atypical. Conclusions: The two case studies illustrate that adults implanted with manual CI fitting may experience an improvement in their auditory results with AI-assisted fitting.

From manual to artificial intelligence fitting: Two cochlear implant case studies.

We present the case of an individual with congenital prosopagnosia or "face blindness", a disorder where the ability to recognize faces is impaired. We studied the lip-reading ability and audiovisual perception of this subject using a DVD with four conditions (audiovisual congruent, auditory, visual, and audiovisual incongruent) and compared results with a normal patient cohort. The patient had no correct responses in the visual lip-reading task; whereas, he improved in the audiovisual congruent task. In the audiovisual incongruent task, the patient provided one response; thus, he was able to lip-read. (He was able to use lip-reading/to use labial informations) This patient perceived only global dynamic facial movements, not the fine ones. He had a sufficient complementary use of lip-reading in audiovisual tasks, but not visual ones. These data are consistent with abnormal development of the pathways used for visual speech perception and associated with second-order face processing disorders and normal development of the audiovisual network for speech perception.

Lip-reading abilities in a subject with congenital prosopagnosia.

Objective: A prospective, longitudinal, randomized controlled trial with an original crossover design for 1 year was conducted to compare manual fitting to artificial intelligence-based fitting in newly implanted patients. Design: Twenty-four patients who received their first cochlear implant (CI) were randomly assigned to the manual or Fitting to Outcome eXpert (FOX) arm; they followed the corresponding fitting procedures for 1 year. After 1 year, each patient was switched to another arm. The number of fittings, auditory outcomes (pure-tone thresholds, loudness scaling curves, spectral discrimination scores, bisyllabic word recognition in quiet and noise, and speech tracking), fitting session questionnaire, and CI parameters (T level, C level, Threshold Sound Pressure Level (T-SPL), Comfortable Sound Pressure Level (C-SPL), and loudness growth value) were compared between the two groups. Differences between the two groups were analyzed using the Mann-Whitney test, and Holm corrections were applied for multiple statistical tests. At the end of the crossover session, patients were offered the choice to continue with their old or new map. Results: As early as 3 mo postactivation, the FOX group showed less variability and significantly better speech intelligibility in quiet conditions at 40 and 55 dB SPL and noise (p < 0.05) with median phoneme scores of 50%, 70%, and 50% at 55, 70, and 85 dB SPL compared with 45%, 50%, and 40%, respectively. This group showed better results at 12 mo postactivation (p < 0.05). In the manual group, 100% of the patients decided to keep the new FOX map, and 82% performed better with the FOX map. In the FOX group, 63% of the patients decided to keep the manual map, although the measurable outcome had not improved. In this group, participants reported to prefer the manual map because it felt more comfortable, even if the FOX map gave better measured outcome. Conclusion: Although the study size remains relatively small, the AI-FOX approach was equivalent to or even outperformed the manual approach in hearing performance, comfort, and resources. Furthermore, FOX is a tool capable of continuous improvement by comparing its predictions with observed results and is continuously learning from clinicians’ practice, which is why this technology promises major advances in the future.

Justine Wathour

Papers

From manual to artificial intelligence fitting: Two cochlear implant case studies.

Variability of fitting parameters across cochlear implant centres.

Lip-reading abilities in a subject with congenital prosopagnosia.

Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients

Prospective Comparison Between Manual and Computer-Assisted (FOX) Cochlear Implant Fitting in Newly Implanted Patients