A morphological classification for vocal fold leukoplakia

Chen, Min; Li, Changjiang; Yang, Yue; Cheng, Lei; Wu, Haitao

doi:10.1016/j.bjorl.2018.04.014

Cited by 28 publications

(45 citation statements)

References 38 publications

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“…Then, morphological assessment of the vocal fold leukoplakia was performed according to the three-tier protocol proposed by Chen et al (2019) [7]. The morphological types of leukoplakia were categorized as: (1) flat and smooth, (2) elevated and smooth, and (3) rough.…”

Section: White Light Imaging (Wli)mentioning

confidence: 99%

“…A combination of the four WLI variables-color, texture, size, and hyperemia-has the potential to be a comprehensive system for predicting malignancy [6,32,33]. Finally, in 2019, a new three-tier classification system was proposed [7], which seems more intuitive as it includes the assessment of the most important morphological features of VFL: surface, margin, and texture.…”

Section: Wli Classificationsmentioning

confidence: 99%

“…The annual incidence of the most common vocal fold leukoplakia (VFL) is estimated to be 10.2/100,000 in males and 2.1/100,000 in females [2][3][4]. The clinical term 'leukoplakia' refers to thick whitish or grey patches and is associated with a spectrum of histological diagnoses, from hyperplasia to malignant transformation [3,[5][6][7] The potential for it to transform into laryngeal cancer (LC) is wide and estimated at 1% to 40% [4,8,9]. The most common symptom of VFL is hoarseness.…”

Section: Introductionmentioning

confidence: 99%

“…Since the beginning of the 21st century, the classifications of WLI [7] and NBI imaging [22][23][24] for the assessment of VFL have been optimized to find the best possible tool for malignant transformation prediction. Validating all classifications based on one large group of patients remains an open field for research.…”

Section: Introductionmentioning

confidence: 99%

“…Description of the classifications used with determined cut-off points (IPCLs-intraepithelial papillary capillary loops; VF-vocal fold; ELS-European Laryngological Society)[7,[22][23][24]. Cont.…”

mentioning

confidence: 99%

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Vocal Fold Leukoplakia: Which of the Classifications of White Light and Narrow Band Imaging Most Accurately Predicts Laryngeal Cancer Transformation? Proposition for a Diagnostic Algorithm

Pietruszewska

Morawska

Rosiak

et al. 2021

Cancers

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The management of Vocal Fold Leukoplakia (VFL) remains problematic. There is no consensus on the indications or the timing for surgery. The objective was to select the most accurate classification for predicting low- and high-risk VFL in White Light Imaging (WLI) and Narrow Band Imaging (NBI) and to establish a diagnostic algorithm with a timely referral for treatment. A total of 259 VFL patients were included in the study; 186 lesions were classified as low-grade and 110 as high-grade dysplasia. The results of WLI acc. to the two-tier and the three-tier Chen 2019 classifications and NBI classifications: ELS, Ni 2011, and Ni 2019 with different cut-off points were compared with the pathological examination (HP). In WLI, the greatest agreement was obtained between type 3 of the three-tier classification and high-grade dysplasia (accuracy, specificity, and PPV: 80.4%, 92.0%, and 81.5%, respectively). Assessing VFL periphery in NBI, cut-off point 5 (Ni 2011 type V) demonstrated a higher accuracy, specificity, and PPV than 4 (83.1%, 93.6%, 85.5% and 77.4%, 74.9%, and 65.4%, respectively). In NBI, we observed higher accuracy, sensitivity, and PPV (84.1%, 93.0%, 85.2% vs. 80.7%, 81.3% and 71.3%, respectively) for cut-off point 5 (Ni 2019 type V and VI) in comparison to the cut-off point 4 group (type IV, V, and VI) (80.7%, 81.3%, 71.3%, respectively), and a higher kappa value (0.68 vs. 0.58) was obtained. We have shown that both the plaque image and the microvascular pattern on the leukoplakia periphery are critical in the diagnosis of high-risk VFL. The most accurate predictor of VFL malignant transformation in WLI is type 3 according to the Chen 2019 classification, while in NBI type V and VI according to the Ni 2019 classification.

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Section: White Light Imaging (Wli)mentioning

confidence: 99%

Section: Wli Classificationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Vocal Fold Leukoplakia: Which of the Classifications of White Light and Narrow Band Imaging Most Accurately Predicts Laryngeal Cancer Transformation? Proposition for a Diagnostic Algorithm

Pietruszewska

Morawska

Rosiak

et al. 2021

Cancers

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The sensitivity of laryngeal findings in predicting high‐grade dysplasia in patients with vocal fold leukoplakia undergoing office‐based biopsies: A retrospective analysis of 100 cases

Hosri,

Aoun,

Yammine

et al. 2024

Laryngoscope Investig Oto

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ObjectiveTo investigate the sensitivity of laryngeal findings in predicting high‐grade dysplasia/carcinoma in situ (CIS) and squamous cell carcinoma (SCC) in patients with vocal fold leukoplakia.MethodsA retrospective review of the medical records and video recordings of the laryngeal examination of patients with vocal fold leukoplakia who underwent un‐sedated office‐based laryngeal biopsy in a tertiary referral center between January 2022 and August 2023 was conducted. Laryngeal findings included the size, surface, projection, and edges of the lesion. Vocal fold leukoplakia was classified according to the WHO as benign, low‐grade dysplasia, high‐grade dysplasia/CIS, and squamous cell carcinoma.ResultsSeventy patients with 100 vocal fold leukoplakia were included. Size was found to have the highest sensitivity with an AUC of 0.730 (95% CI [0.618–0.842], p = 0.002) followed by surface and projection with AUCs of 0.672 (95% CI [0.548–0.795], p = 0.019) and 0.675 (95% CI [0.546–0.804], p = 0.017), respectively. Furthermore, the odds of diagnosing high‐risk lesions (high‐grade dysplasia/CIS and SCC) were the greatest when the lesion was large and rough (OR = 10.28; 95% CI [3.08–34.36]).ConclusionThe morphological features of vocal fold leukoplakia may assist the physician in predicting the risk of malignancy. Large and rough lesions were more likely to harbor high‐grade dysplasia/CIS and SCC compared to small and smooth lesions.

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Defining the Performance of Clinician's Ability to Screen for Laryngeal Mass From Voice

Wandell

Law

Maxin

et al. 2023

Otolaryngol.--head neck surg.

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Objective. Defining a clinician's ability to perceptually identify mass from voice will inform the feasibility, design priorities, and performance standards for tools developed to screen for laryngeal mass from voice. This study defined clinician ability of and examined the impact of expertise on screening for laryngeal mass from voice.Study Design. Task comparison study between experts and nonexperts rating voices for the probability of a laryngeal mass.Setting. Online, remote.Methods. Experts (voice-focused speech-language pathologists and otolaryngologists) and nonexperts (general medicine providers) rated 5-s/i/voice samples (with pathology defined by laryngoscopy) for the probability of laryngeal mass via an online survey. The intraclass correlation coefficient (ICC) estimated interrater and intrarater reliability. Diagnostic performance metrics were calculated. A linear mixed effects model examined the impact of expertise and pathology on ratings.Results. Forty clinicians (21 experts and 19 nonexperts) evaluated 344 voice samples. Experts outperformed nonexperts, with a higher area under the curve (70% vs 61%), sensitivity (49% vs 36%), and specificity (83% vs 77%) (all comparisons p < .05). Interrater reliability was fair for experts and poor for nonexperts (ICC: 0.48 vs 0.34), while intrarater reliability was excellent and good, respectively (ICC: 0.9 and 0.6). The main effects of expertise and underlying pathology were significant in the linear model (p < .001). Conclusion.Clinicians demonstrate inadequate performance screening for laryngeal mass from voice to use auditory perception for dysphonia triage. Experts' superior performance indicates that there is acoustic information in a voice that may be utilized to detect laryngeal mass based on voice.

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A morphological classification for vocal fold leukoplakia

Cited by 28 publications

References 38 publications

Vocal Fold Leukoplakia: Which of the Classifications of White Light and Narrow Band Imaging Most Accurately Predicts Laryngeal Cancer Transformation? Proposition for a Diagnostic Algorithm

Vocal Fold Leukoplakia: Which of the Classifications of White Light and Narrow Band Imaging Most Accurately Predicts Laryngeal Cancer Transformation? Proposition for a Diagnostic Algorithm

The sensitivity of laryngeal findings in predicting high‐grade dysplasia in patients with vocal fold leukoplakia undergoing office‐based biopsies: A retrospective analysis of 100 cases

Defining the Performance of Clinician's Ability to Screen for Laryngeal Mass From Voice

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