Surgeon-performed transcutaneous laryngeal ultrasound for vocal cord assessment after total thyroidectomy: a prospective study : Original article.

PURPOSE: Assessing vocal cord mobility is crucial for patients undergoing thyroid surgery. We aimed to evaluate the feasibility and efficacy of surgeon-performed transcutaneous laryngeal ultrasound (TLUS) compared to flexible nasolaryngoscopy. METHOD: From February 2022 to December 2022, we conducted a prospective observational study on patients scheduled for total thyroidectomy at our Institution. All patients underwent TLUS followed by flexible nasolaryngoscopy by a blinded otolaryngologist. Findings were classified as normal or vocal cord movement impairment and then compared. Patients evaluable on TLUS were included in Group A, while those not evaluable were included in Group B, and their features were compared. RESULTS: Group A included 180 patients, while Group B included 21 patients. Male sex (p < 0.001), age (p = 0.034), BMI (p < 0.001), thyroid volume (p = 0.038), and neck circumference (p < 0.001) were associated with Group B. TLUS showed a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 99.4%, 94.4%, 100%, and 99.4%, respectively. Cohen's K value was 0.984. CONCLUSION: TLUS is a valid, easy-to-perform, non-invasive, and painless alternative for evaluating vocal cords in selected patients. It can be used either as a first level exam and as screening tool for selecting cases for flexible nasolaryngoscopy. TLUS should be integrated into routine thyroid ultrasound examination.

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL). METHODS: The AI system was developed, trained and validated on 5362 images of 551 patients from three hospitals. Automated regions of interest (ROI) segmentation algorithm was utilized to construct image-level features. MIL was used to fusion image level results to patient level features, then the extracted features were modeled by seven machine learning algorithms. Finally, we evaluated the image level and patient level results. Additionally, 50 videos of VFL were prospectively gathered to assess the system's real-time diagnostic capabilities. A human-machine comparison database was also constructed to compare the diagnostic performance of otolaryngologists with and without AI assistance. RESULTS: In internal and external validation sets, the maximum area under the curve (AUC) for image level segmentation models was 0.775 (95 % CI 0.740-0.811) and 0.720 (95 % CI 0.684-0.756), respectively. Utilizing a MIL-based fusion strategy, the AUC at the patient level increased to 0.869 (95 % CI 0.798-0.940) and 0.851 (95 % CI 0.756-0.945). For real-time video diagnosis, the maximum AUC at the patient level reached 0.850 (95 % CI, 0.743-0.957). With AI assistance, the AUC improved from 0.720 (95 % CI 0.682-0.755) to 0.808 (95 % CI 0.775-0.839) for senior otolaryngologists and from 0.647 (95 % CI 0.608-0.686) to 0.807 (95 % CI 0.773-0.837) for junior otolaryngologists. CONCLUSIONS: The MIL based AI-assisted diagnosis system can significantly improve the diagnostic performance of otolaryngologists for VFL and help to make proper clinical decisions.

A deep learning pipeline for automated classification of vocal fold polyps in flexible laryngoscopy.

PURPOSE: To develop and validate a deep learning model for distinguishing healthy vocal folds (HVF) and vocal fold polyps (VFP) on laryngoscopy videos, while demonstrating the ability of a previously developed informative frame classifier in facilitating deep learning development. METHODS: Following retrospective extraction of image frames from 52 HVF and 77 unilateral VFP videos, two researchers manually labeled each frame as informative or uninformative. A previously developed informative frame classifier was used to extract informative frames from the same video set. Both sets of videos were independently divided into training (60%), validation (20%), and test (20%) by patient. Machine-labeled frames were independently verified by two researchers to assess the precision of the informative frame classifier. Two models, pre-trained on ResNet18, were trained to classify frames as containing HVF or VFP. The accuracy of the polyp classifier trained on machine-labeled frames was compared to that of the classifier trained on human-labeled frames. The performance was measured by accuracy and area under the receiver operating characteristic curve (AUROC). RESULTS: When evaluated on a hold-out test set, the polyp classifier trained on machine-labeled frames achieved an accuracy of 85% and AUROC of 0.84, whereas the classifier trained on human-labeled frames achieved an accuracy of 69% and AUROC of 0.66. CONCLUSION: An accurate deep learning classifier for vocal fold polyp identification was developed and validated with the assistance of a peer-reviewed informative frame classifier for dataset assembly. The classifier trained on machine-labeled frames demonstrates improved performance compared to the classifier trained on human-labeled frames.

Artificial intelligence based diagnosis of sulcus: assesment of videostroboscopy via deep learning.

PURPOSE: To develop a convolutional neural network (CNN)-based model for classifying videostroboscopic images of patients with sulcus, benign vocal fold (VF) lesions, and healthy VFs to improve clinicians' accuracy in diagnosis during videostroboscopies when evaluating sulcus. MATERIALS AND METHODS: Videostroboscopies of 433 individuals who were diagnosed with sulcus (91), who were diagnosed with benign VF diseases (i.e., polyp, nodule, papilloma, cyst, or pseudocyst [311]), or who were healthy (33) were analyzed. After extracting 91,159 frames from videostroboscopies, a CNN-based model was created and tested. The healthy and sulcus groups underwent binary classification. In the second phase of the study, benign VF lesions were added to the training set, and multiclassification was executed across all groups. The proposed CNN-based model results were compared with five laryngology experts' assessments. RESULTS: In the binary classification phase, the CNN-based model achieved 98% accuracy, 98% recall, 97% precision, and a 97% F1 score for classifying sulcus and healthy VFs. During the multiclassification phase, when evaluated on a subset of frames encompassing all included groups, the CNN-based model demonstrated greater accuracy when compared with that of the five laryngologists (%76 versus 72%, 68%, 72%, 63%, and 72%). CONCLUSION: The utilization of a CNN-based model serves as a significant aid in the diagnosis of sulcus, a VF disease that presents notable challenges in the diagnostic process. Further research could be undertaken to assess the practicality of implementing this approach in real-time application in clinical practice.

Sound source locations and their roles in Japanese voiceless "glottal" fricative production.

Although [h] is described as a glottal fricative, it has never been demonstrated whether [h] has its source exclusively at the glottis. In this study, sound source locations and their influence on sound amplitudes were investigated by conducting mechanical experiments and airflow simulations. Vocal tract data of [h] were obtained in three phonemic contexts from two native Japanese subjects using three-dimensional static magnetic resonance imaging (MRI). Acrylic vocal tract replicas were constructed, and the sound was reproduced by supplying airflow to the vocal tracts with adducted or abducted vocal folds. The sound source locations were estimated by solving the Navier-Stokes equations. The results showed that the amplitudes of sounds produced by the vocal tracts with an open glottis were in a similar range (±3 dB) to those with a glottal gap of 3 mm in some contexts. The sound sources in these cases were observed in the pharyngeal cavity or near the soft palate. Similar degrees of oral constrictions were observed in the real-time MRI, indicating that the sound traditionally described as [h] is produced, at least in some contexts, with sound sources of turbulent flow generated by a supralaryngeal constriction of the following vowel.

Airway obstruction secondary to vocal cord polyp.

ABSTRACT: Patients with vocal cord polyps commonly present with symptoms of hoarseness. Although rare, large polyps can cause shortness of breath and stridor and should be included in the differential for patients with airway obstruction. Dysphonia or hoarseness can be a symptom of underlying disease, such as head and neck cancer. This case illustrates the importance of prompt and accurate diagnosis in a patient with persistent symptoms and a history of smoking. Obtaining a laryngoscopy is crucial to appropriately evaluate the larynx. Proper visualization of the laryngeal structures will help direct patient care toward further diagnostic imaging and medical or surgical intervention if indicated.

Hypertrophic olivary degeneration associated with bilateral vocal cord adductor dystonia.

BACKGROUND: Hypertrophic olivary degeneration (HOD) is a rare condition caused by lesions within the dentato-rubro-olivary pathway, resulting in ocular nystagmus and palatal myoclonus (oculopalatal tremor) but not usually dystonia. Dystonia is an uncommon association, and we present the first reported association of hypertrophic olivary degeneration with bilateral vocal cord dystonia. CASE PRESENTATION: A 33 year old male presented initially with acute hydrocephalus on the background of previous ventriculoperitoneal (VP) shunting for previously treated medulloblastoma. After revision of the VP shunt, the patient developed progressive hiccups and stridor leading to respiratory failure requiring intubation. Ocular pendular nystagmus and palatal myoclonus at 3 Hz was observed. Flexible nasendoscopy (FNE) demonstrated bilateral tonic adduction of the vocal folds with 3 Hz coarse supraglottic, pharyngeal and palatal rhythmic myoclonus. MRI imaging demonstrated T2 hyperintensity within the bilateral inferior olivary nuclei consistent with stage 3 radiological HOD. CONCLUSIONS: Dystonia is a rarely reported phenomenon in HOD but is not unexpected with the inferior olivary nucleus implicated in dystonic disorders. We report the association of HOD with bilateral vocal cord adductor dystonia, a potentially life threatening condition.

A Prospective Study Evaluating the Feasibility and Accuracy of Post-operative Laryngeal Ultrasonography (LUSG) in Assessment of Vocal Cord Function After Esophagectomy.

BACKGROUND: Vocal cord paresis (VCP) is a serious complication after esophagectomy. Conventional diagnosis of VCP relies on flexible laryngoscopy (FL), which is invasive. Laryngeal ultrasonography (LUSG) is non-invasive and convenient. It has provided accurate VC evaluation after thyroidectomy but it is unclear if it is just as accurate following esophagectomy. This prospective study evaluated the feasibility and accuracy of LUSG in VC assessment on day-1 after esophagectomy. METHODS: Consecutive patients from a tertiary teaching hospital who underwent elective esophagectomy were prospectively recruited. All received pre-operative FL, and post-operative LUSG and FL on Day-1, each performed by a blinded, independent assessor. The primary outcomes were feasibility and accuracy of LUSG in the diagnosis of VCP on Day-1 post-esophagectomy. The accuracy of voice assessment (VA) was analyzed. RESULTS: Twenty-six patients were eligible for analysis. The median age was 70 years (66-73). Majority were male (84.6%). Twenty-five (96.2%) received three-phase esophagectomy. Twenty-four (96%) had same-stage anastomosis at the neck. Three (11.5%) developed temporary and one (3.8%) developed permanent unilateral VCP. Overall VC visualization rate by LUSG was 100%; sensitivity, specificity, positive predictive value, negative predictive value (NPV) and accuracy of LUSG were 75.0%, 100%, 100%, 98.0%, 98.1% respectively, and superior to VA. Combining LUSG with VA findings could pick up all VCPs i.e. improved sensitivity and NPV to 100%. CONCLUSION: LUSG is a highly feasible, accurate and non-invasive method to evaluate VC function early after esophagectomy. Post-operative FL may be avoided in patients with both normal LUSG and voice.

Vocal cord dysfunction/inducible laryngeal obstruction-2022 Melbourne Roundtable Report.

Vocal cord dysfunction/inducible laryngeal obstruction (VCD/ILO), is a common condition characterized by breathlessness associated with inappropriate laryngeal narrowing. Important questions remain unresolved, and to improve collaboration and harmonization in the field, we convened an international Roundtable conference on VCD/ILO in Melbourne, Australia. The aims were to delineate a consistent approach to VCD/ILO diagnosis, appraise disease pathogenesis, outline current management and model(s) of care and identify key research questions. This report summarizes discussions, frames key questions and details recommendations. Participants discussed clinical, research and conceptual advances in the context of recent evidence. The condition presents in a heterogenous manner, and diagnosis is often delayed. Definitive diagnosis of VCD/ILO conventionally utilizes laryngoscopy demonstrating inspiratory vocal fold narrowing >50%. Computed tomography of the larynx is a new technology with potential for swift diagnosis that requires validation in clinical pathways. Disease pathogenesis and multimorbidity interactions are complex reflecting a multi-factorial, complex condition, with no single overarching disease mechanism. Currently there is no evidence-based standard of care since randomized trials for treatment are non-existent. Recent multidisciplinary models of care need to be clearly articulated and prospectively investigated. Patient impact and healthcare utilization can be formidable but have largely escaped inquiry and patient perspectives have not been explored. Roundtable participants expressed optimism as collective understanding of this complex condition evolves. The Melbourne VCD/ILO Roundtable 2022 identified clear priorities and future directions for this impactful condition.

Ultrasound Elastography Detects Age-Related Changes in Adult False Vocal Folds.

PURPOSE: To investigate the feasibility of ultrasound elastography for assessing the symmetry in stiffness values and movements of both false vocal folds (FVFs). METHODS: After Institutional Review Board's approval and written informed consent obtained, we measured ultrasound strain and shear wave velocity (SWV) of the bilateral FVF in vocal fold abduction and adduction in 30 participants using a linear array transducer (4-10 MHz). Twenty-eight participants met inclusion criteria as healthy subjects for analysis. Mean strain of FVF produced by FVF movement from abduction to adduction was analyzed using 2D speckle-tracking software offline. A SWV ratio ([SWVadduction - SWabduction ]/SWabduction ) was developed to test the contractibility of FVF. Statistical analysis included one-way ANOVA to test the difference in mean strain, SWV (adduction and abduction), and SWV ratio among the three age groups; linear regression to analyze correlations of stiffness and movement between the right and left FVF; and intraclass correlation coefficient (ICC) to examine intra- and interobserver reliability in performing shear wave elastography (SWE) of FVF. RESULTS: The 28 healthy participants were divided into 3 age groups (10 of young 20-44 years; 9 of mid-age 45-64 years; and 9 of senior ≥65 years). The SWV in FVF abduction was higher and the SWV ratio was lower in seniors compared to young participants (P < .05). Good to excellent correlation of mean strain and SWV between both FVFs (R2 > 0.89). The reliability of performing SWE of FVF was moderate to excellent. CONCLUSION: Ultrasound elastography is feasible to assess the stiffness, dynamic movement, and symmetry of adult FVF, and healthy seniors may exhibit increased FVF stiffness.

Support of deep learning to classify vocal fold images in flexible laryngoscopy.

PURPOSE: To collect a dataset with adequate laryngoscopy images and identify the appearance of vocal folds and their lesions in flexible laryngoscopy images by objective deep learning models. METHODS: We adopted a number of novel deep learning models to train and classify 4549 flexible laryngoscopy images as no vocal fold, normal vocal folds, and abnormal vocal folds. This could help these models recognize vocal folds and their lesions within these images. Ultimately, we made a comparison between the results of the state-of-the-art deep learning models, and another comparison of the results between the computer-aided classification system and ENT doctors. RESULTS: This study exhibited the performance of the deep learning models by evaluating laryngoscopy images collected from 876 patients. The efficiency of the Xception model was higher and steadier than almost the rest of the models. The accuracy of no vocal fold, normal vocal folds, and vocal fold abnormalities on this model were 98.90 %, 97.36 %, and 96.26 %, respectively. Compared to our ENT doctors, the Xception model produced better results than a junior doctor and was near an expert. CONCLUSION: Our results show that current deep learning models can classify vocal fold images well and effectively assist physicians in vocal fold identification and classification of normal or abnormal vocal folds.

Comparison of convolutional neural networks for classification of vocal fold nodules from high-speed video images.

OBJECTIVES: Deep learning is in this study used through convolutional neural networks (CNN) to the determination of vocal fold nodules. Through high-speed video (HSV) images and computer-assisted tools, a comparison of convolutional neural network models and their accuracy will be presented. METHODS: The data have been collected by an Ear Nose Throat (ENT) specialist with a 90° rigid scope in the years from 2007 to 2019, where 15.732 high-speed videos have been collected from 7909 patients. A total of 4000 images have been carefully selected, 2000 images were of normal vocal folds and 2000 images were of vocal folds with varying degrees of vocal fold nodules. These images were then split into training-, validation-, and testing-data set, for use with a CNN model with 5 layers (CNN5) and compared to other models: VGG19, MobileNetV2, and Inception-ResNetV2. To compare the neural network models, the following evaluation metrics have been calculated: accuracy, sensitivity, specificity, precision, and negative predictive values. RESULTS: All the trained CNN models have shown high accuracy when applied to the test set. The accuracy is 97.75%, 83.5%, 91.5%, and 89.75%, for CNN5, VGG19, MobileNetV2, and InceptionResNetV2, respectively. CONCLUSIONS: Precision was identified as the most relevant performance metric for a study that focuses on the classification of vocal fold nodules. The highest performing model was MobilNetV2 with a precision of 97.7%. The average accuracy across all 4 neural networks was 90.63% showing that neural networks can be used for classifying vocal fold nodules in a clinical setting.

Normative data for certain vocal fold biomarkers among young normophonic adults using ultrasonography.

PURPOSE: The current study aimed to profile vocal fold morphology, vocal fold symmetry, gender and task-specific data for vocal fold length (VFL) and vocal fold displacement velocity (VFDV) in young normophonic adults in the age range of 18-30 years using ultrasonography (USG). METHODS: Participants underwent USG across quiet breathing, /a/ phonation and /i/ phonation tasks, and acoustic analysis was conducted to explore the relationship between USG and acoustic measures. RESULTS: The study found that males have longer vocal folds than females, and overall greater velocities were observed in /a/ phonation, followed by /i/ phonation, with the lowest velocity observed in the quiet breathing task. CONCLUSIONS: The obtained norms can be used as a quantitative benchmark for analyzing the vocal fold behavior in young adults.

Dynamic changes of vocal tract dimensions with sound pressure level during messa di vocea).

The messa di voce (MdV), which consists of a continuous crescendo and subsequent decrescendo on one pitch is one of the more difficult exercises of the technical repertoire of Western classical singing. With rising lung pressure, regulatory adjustments both on the level of the glottis and the vocal tract are required to keep the pitch stable. The dynamic changes of vocal tract dimensions with the bidirectional variation of sound pressure level (SPL) during MdV were analyzed by two-dimensional real-time magnetic resonance imaging (25 frames/s) and synchronous audio recordings in 12 professional singer subjects. Close associations in the respective articulatory kinetics were found between SPL and lip opening, jaw opening, pharynx width, uvula elevation, and vertical larynx position. However, changes in vocal tract dimensions during plateaus of SPL suggest that perceived loudness could have been varied beyond the dimension of SPL. Further multimodal investigation, including the analysis of sound spectra, is needed for a better understanding of the role of vocal tract resonances in the control of vocal loudness in human phonation.

Automated detection of glottic laryngeal carcinoma in laryngoscopic images from a multicentre database using a convolutional neural network.

OBJECTIVE: Little is known about the efficacy of using artificial intelligence (AI) to identify laryngeal carcinoma from images of vocal lesions taken in different hospitals with multiple laryngoscope systems. This multicentre study aimed to establish an AI system and provide a reliable auxiliary tool to screen for laryngeal carcinoma. STUDY DESIGN: Multicentre case-control study. SETTING: Six tertiary care centres. PARTICIPANTS: Laryngoscopy images were collected from 2179 patients with vocal fold lesions. OUTCOME MEASURES: An automatic detection system of laryngeal carcinoma was established and used to distinguish malignant and benign vocal lesions in 2179 laryngoscopy images acquired from 6 hospitals with 5 types of laryngoscopy systems. Pathological examination was the gold standard for identifying malignant and benign vocal lesions. RESULTS: Out of 89 cases in the malignant group, the classifier was able to correctly identify laryngeal carcinoma in 66 patients (74.16%, sensitivity). Out of 640 cases in the benign group, the classifier was able to accurately assess the laryngeal lesion in 503 cases (78.59%, specificity). Furthermore, the region-based convolutional neural network (R-CNN) classifier achieved an overall accuracy of 78.05%, with a 95.63% negative predictive value and a 32.51% positive predictive value for the testing data set. CONCLUSION: This automatic diagnostic system has the potential to assist clinical laryngeal carcinoma diagnosis which may improve and standardise the diagnostic capacity of laryngologists using different laryngoscopes.

[Polypositional transcutaneous ultrasound assessment of vocal folds mobility. Ultrasonographic sign of laryngeal dysfunction]. / Polipozitsionnoe ul'trazvukovoe issledovanie golosovykh skladok v diagnostike narushenii podvizhnosti gortani.

Fiberoptic laryngoscopy is a standard procedure for evaluation of vocal folds immobility. However, this method is invasive, requires special qualifications and technical equipment, which limits its routine use. Therefore, in daily practice, the vast majority of laryngoscopy are performed by an indirect way, the accuracy of which depends on the specialist experience and the patient compliance. On the other hand, a large number of patients require for a convenient, non-invasive and inexpensive approach to assess the vocal folds mobility. The transcutaneous laryngeal ultrasonography can be such a method. However, the disadvantage of this technique is low informative value. OBJECTIVE: To increase the effectiveness of the diagnosis of laryngeal dysfunction using transcutaneous laryngeal ultrasonography. MATERIAL AND METHODS: Patients underwent laryngeal ultrasonography and videolaryngoscopy before and after thyroid or parathyroid surgery. Ultrasound was performed polypositionally in the transverse and oblique planes. Functional tests with breathing and breath holding were used. Qualitative (the smile or flying bird signs, the vertical closing line of the vocal folds, synchronicity and symmetry movement of the arytenoid cartilages) and quantitative (the length contraction of the vocal cord, the rotation angle of the arytenoid cartilage) ultrasonic parameters determin the normal vocal folds mobility. RESULTS: 996 patients were included in the study. Vocal folds paresis was detected in 106 (10.6%) patients. In 72 (7.2%) cases partial impaired mobility of the vocal folds (laryngeal dyskinesia) were detected. The echographic patterns of these patients were analyzed. Qualitative ultrasound signs of laryngeal dysfunction were identified: a crooked smile or falling bird signs, a closing line deformation of the vocal folds, an arytenoid immobility. Quantitative ultrasound signs included: a decrease in the length contraction of the vocal cord and a reduction of rotation angle of the arytenoid cartilage. Unilateral laryngeal paresis was diagnosed in 101 (10.1%) patients. In unilateral disorders the rotation angle of the arytenoid on the affected side was 0-14° and the length contraction of the vocal cord was 0-1.8 mm. A crooked smile or falling bird signs, a closing line deformation of the vocal folds and immobility of the arytenoid cartilages were also determined. In 5 (0.5%) cases bilateral laryngeal paresis was revealed, in which on both sides the rotation angles of the arytenoid were 0-14°, and the length contraction of the vocal cords was 0-1.8 mm. At the same time there was no a smile or flying bird signs and a closing line of the vocal folds. Laryngeal dyskinesia was characterized by a crooked smile or falling bird signs and a closing line deformation of the vocal folds. At the same time, partial mobility of the arytenoid cartilage was noted in comparison with the contralateral side (there was a difference in the rotation angle of the arytenoid between the right and left sides of 15 ° or more degrees). CONCLUSION: The sensitivity and specificity polypositional ultrasound of the vocal folds in women were 100% and 99.8%, in men - 85.7% and 99.2%, respectively.

Vocal cord dysfunction detected by a three-dimensional image of dynamic change in respiratory resistance in a patient with difficult-to-treat asthma: a case report.

INTRODUCTION: Vocal cord dysfunction (VCD) often coexists with asthma and exacerbates respiratory symptoms. A noninvasive method could be considered beneficial for the detection and follow-up of VCD complicated by asthma. Here, we report a case of VCD complicated by asthma, highlighting the effectiveness of colored three-dimensional (3-D) imaging of respiratory impedance using a broadband frequency forced oscillation technique (MostGraph). CASE STUDY: A 74-year-old woman with difficult-to-treat asthma, in whom mepolizumab treatment was ineffective, was referred to our hospital. Stridulous sounds were loudest over the anterior neck. Pulmonary function tests' results were normal; however, a flattening of the inspiratory flow-volume curve was detected. RESULTS: Remarkably, prominent spikes were observed in the inspiratory phase in the colored 3-D imaging of respiratory resistance, which was superimposed on increased respiratory resistance in the expiratory phase. Flexible laryngoscopy revealed the adduction of vocal cords on inspiration. The patient was diagnosed with asthma complicated by VCD. After successful treatment of VCD by speech therapy, inspiratory spikes of respiratory resistance disappeared, and normal vocal cord movement was observed on laryngoscopy. CONCLUSION: The present case report indicates the effectiveness of forced oscillometry in evaluating dynamic changes in respiratory resistance for detecting and monitoring VCD complicated by asthma.

Using Intra-Operative Laryngeal Ultrasonography as a Real-Time Tool in Assessing Vocal Cord Function During Radiofrequency Ablation of the Thyroid Gland.

BACKGROUND: Inadvertent injury of the recurrent laryngeal nerve can occur during radiofrequency ablation (RFA) of thyroid nodules. Methods to avoid permanent injury have not been described. Laryngeal ultrasonography (LUSG) can assess the function of vocal cords (VCs) in real time. The present study aimed to evaluate the feasibility and accuracy of LUSG in assessing real-time VC function during RFA of benign thyroid nodules. METHODS: Consecutive patients undergoing RFA for benign thyroid nodules under local anesthesia were included. Spontaneous VC movements were checked with intra-operative LUSG (iLUSG) following each transverse ablation plane. In case of reduced VC movement, the ablation was stopped immediately. Post-ablation VC function was rechecked by LUSG on day-0 and flexible laryngoscopy (FL) on day-7. A concordance with day-0 LUSG or day-7 FL was a "true positive" or "true negative" depending on the presence or absence of VC palsy (VCP). Accuracy was calculated as the sum of all true positives and negatives divided by total nerves-at-risk. RESULTS: Of 65 eligible patients, 56 (86.2%) were females. Twelve (18.5%) patients had bilateral lobe RFA, while 53 (81.5%) had unilateral RFA. The total number of nerves-at-risk was 77. Three unilateral VCPs (3.9%) were initially detected on iLUSG and confirmed by day-0 LUSG. All recovered fully within one week. The overall accuracy of iLUSG was 100%. CONCLUSION: iLUSG is a highly accurate method that permits real-time feedback on the function of the VCs during RFA procedure. Real-time detection of VCP may prevent permanent injury. Methodological routine use of iLUSG is recommended during thyroid RFA.

Sub-millisecond 2D MRI of the vocal fold oscillation using single-point imaging with rapid encoding.

OBJECTIVE: The slow spatial encoding of MRI has precluded its application to rapid physiologic motion in the past. The purpose of this study is to introduce a new fast acquisition method and to demonstrate feasibility of encoding rapid two-dimensional motion of human vocal folds with sub-millisecond resolution. METHOD: In our previous work, we achieved high temporal resolution by applying a rapidly switched phase encoding gradient along the direction of motion. In this work, we extend phase encoding to the second image direction by using single-point imaging with rapid encoding (SPIRE) to image the two-dimensional vocal fold oscillation in the coronal view. Image data were gated using electroglottography (EGG) and motion corrected. An iterative reconstruction with a total variation (TV) constraint was used and the sequence was also simulated using a motion phantom. RESULTS: Dynamic images of the vocal folds during phonation at pitches of 150 and 165 Hz were acquired in two volunteers and the periodic motion of the vocal folds at a temporal resolution of about 600 µs was shown. The simulations emphasize the necessity of SPIRE for two-dimensional motion encoding. DISCUSSION: SPIRE is a new MRI method to image rapidly oscillating structures and for the first time provides dynamic images of the vocal folds oscillations in the coronal plane.

Laryngeal Ultrasound Detects Vocal Fold Immobility in Adults: A Systematic Review.

Laryngeal ultrasound (US) is becoming widely accepted for assessing true vocal fold immobility (TVFI), a potential complication of laryngeal and thyroid surgery. The objective of this project is to perform a systematic review and meta-analysis of pooled evidence surrounding laryngeal US as a modality for diagnosing TVFI in adults at risk for the condition in comparison to laryngoscopy as a gold standard. Medical subject heading terms were used to search MEDLINE, Embase, Google Scholar, Web of Science, and the Cochrane Library for relevant citations from January 1, 2000, to June 30, 2020. Studies were included if they involved patients 16 years and older, where laryngeal US was compared to laryngoscopy for TVFI. Studies were excluded if there were insufficient data to compute a sensitivity/specificity table after attempting to contact the authors. Case reports, and case series were also excluded. The initial search returned 1357 citations. Of these, 109 were selected for review utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Thirty citations describing 6033 patients were included in the final meta-analysis. A bivariate random effects meta-analysis was performed, revealing a pooled sensitivity for laryngeal US of 0.95 (95% confidence interval [CI] 0.88-0.98), a specificity of 0.99 (95% CI 0.97-0.99), and a diagnostic odds ratio of 1328.2 (95% CI 294.0-5996.5). The area under the curve of the hierarchical summary receiver operating characteristic curve was 0.99 (95% CI 0.98-1.00). Laryngeal US demonstrates high sensitivity and specificity for detecting VFI in the hands of clinicians directly providing care to patients.