The influence of intraoperative auditory brainstem responses on vibroplasty coupling-quality and analysis of the impact of different fixation steps on the coupling.

PURPOSE: The Vibrant Soundbridge (VSB) is an established active-middle-ear-implant for patients with moderate-to-profound hearing-loss. This surgery is referred to as "Vibroplasty". Sufficient transfer of the VSB's floating-mass-transducers (FMT) energy to the inner ear is a crucial factor influencing the coupling-quality (CQ). However, assessing CQ is hamper by two issues: the method of CQ-assessment itself and the method of FMT-fixation during Vibroplasty. METHODS: This prospective study explored the influence of intraoperative auditory-brainstem-response (+ ABR) measurements and various fixation methods on postoperative CQ after Vibroplasty as compared to matched-patients after Vibroplasty without intraoperative ABR (-ABR). Propensity-score-matching was performed based on preoperative bone-conduction-pure-tone-average-3 (BC-PTA3) at 1-, 2- and 4 kHz. Primary outcome parameters were postoperative CQ-PTA3, intraoperative ABR threshold for various fixation methods and postoperative BC-PTA3. RESULTS: A total of 28 patients were included, of which 14 were + ABR. Preoperative BC-PTA3, sex, age, and number of previous surgeries did not differ significantly between groups (all p > 0.301). Mean postoperative CQ-PTA3 was significantly better for + ABR (1.8 vs. 12.3 dB-HL; p = 0.006). Mean intraoperative ABR threshold was superior for cartilage-counter-bearing and cartilage-housing compared to additional fixation with injectable-platelet-rich- fibrin (53 vs. 56 & 57 dB-HL, respectively; p = 0.04; η2 = 0.33). Mean postoperative BC-PTA3 did not significantly differ between patients (41.4 vs. 41.8 dB-HL; p = 0.77). A total of 7% of the patients required intraoperative readjustment of the FMT based on unsatisfactory intraoperative ABR threshold. CONCLUSION: Intraoperative ABR measurement resulted in significantly better postoperative CQ. Cartilage-counter-bearing and cartilage-housing were observed to have superior CQ. A total of 7% of the patients could be spared revision-Vibroplasty due to intraoperative ABR measurement.

Radiomic Assessment of Radiation-Induced Alterations of Skeletal Muscle Composition in Head and Neck Squamous Cell Carcinoma within the Currently Clinically Defined Optimal Time Window for Salvage Surgery-A Pilot Study.

Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity modulation, the desired radiation-induced effects observed in HNSCC may also be observed as side effects in healthy tissue, e.g., the sternocleidomastoid muscle (SCM). These side effects (e.g., tissue fibrosis) depend on the interval between the completion of RCT and restaging CT. For salvage surgery, the optimal time window for surgery is currently clinically postulated at between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on clinical studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC patients are sparse. The present study quantified tissue alterations in the SCM and paravertebral musculature (PVM) after RCT, applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters, (1) volume, (2) mean positivity of pixels (MPP), and (3) uniformity, were extracted with mint LesionTM in the staging CTs and restaging CTs of 98 HNSCC patients. Of these, 25 were female, the mean age was 62 (±9.6) years, and 80.9% were UICC Stage IV. The mean restaging interval was 55 (±28; range 29-229) days. Only the mean volume significantly decreased after RCT, from 9.0 to 8.4 and 96.5 to 91.9 mL for the SCM and PVM, respectively (both p = 0.007, both Cohen's d = 0.28). In addition, the mean body mass index (BMI) decreased from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p < 0.001; Cohen's d = 0.9). The mean BMI decreased significantly and was correlated with the volume decrease for the SCM (r = 0.27; p = 0.007) and PVM (r = 0.41; p < 0.001). If t-test p-values were adjusted for the BMI decrease, no significant change in volumes for the SCM and PVM was observed (both p > 0.05). The present data support the clinically postulated optimal interval for salvage surgery of 6 to 12 weeks.

Current Applications of Artificial Intelligence to Classify Cervical Lymph Nodes in Patients with Head and Neck Squamous Cell Carcinoma-A Systematic Review.

Locally-advanced head and neck squamous cell carcinoma (HNSCC) is mainly defined by the presence of pathologic cervical lymph nodes (LNs) with or without extracapsular spread (ECS). Current radiologic criteria to classify LNs as non-pathologic, pathologic, or pathologic with ECS are primarily shape-based. However, significantly more quantitative information is contained within imaging modalities. This quantitative information could be exploited for classification of LNs in patients with locally-advanced HNSCC by means of artificial intelligence (AI). Currently, various reviews exploring the role of AI in HNSCC are available. However, reviews specifically addressing the current role of AI to classify LN in HNSCC-patients are sparse. The present work systematically reviews original articles that specifically explore the role of AI to classify LNs in locally-advanced HNSCC applying Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and the Study Quality Assessment Tool of National Institute of Health (NIH). Between 2001 and 2022, out of 69 studies a total of 13 retrospective, mainly monocentric, studies were identified. The majority of the studies included patients with oropharyngeal and oral cavity (9 and 7 of 13 studies, respectively) HNSCC. Histopathologic findings were defined as reference in 9 of 13 studies. Machine learning was applied in 13 studies, 9 of them applying deep learning. The mean number of included patients was 75 (SD ± 72; range 10-258) and of LNs was 340 (SD ± 268; range 21-791). The mean diagnostic accuracy for the training sets was 86% (SD ± 14%; range: 43-99%) and for testing sets 86% (SD ± 5%; range 76-92%). Consequently, all of the identified studies concluded AI to be a potentially promising diagnostic support tool for LN-classification in HNSCC. However, adequately powered, prospective, and randomized control trials are urgently required to further assess AI's role in LN-classification in locally-advanced HNSCC.