Performance de l´imagerie par résonnance magnétique dans l´approche histopathologique des tumeurs parotidiennes

Masmoudi, Mohamed; Hasnaoui, Mehdi; Guizani, Rihab; Lahmar, Rihab; Jerbi, Saïda; Mighri, Khalifa

doi:10.11604/pamj.2021.39.10.27813

Cited by 3 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some authors suggest the combination of cytology and MRI (ref. 28,29 ). However, the availability of MRI in a reasonable time frame for all patients with parotid gland mass may pose difficulties.…”

Section: Discussionmentioning

confidence: 99%

Utility of fine-needle aspiration biopsy (FNAB) in parotid pleomorphic adenoma diagnosis and management

Fíková¹,

Novák²,

Kalfeřt³

et al. 2024

Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub

View full text Add to dashboard Cite

Purpose. Pleomorphic adenoma (PA), the most common benign tumour of the parotid gland, requires accurate preoperative diagnosis owing to its capacity for malignant transformation. The aim of this study was to evaluate our experience with ultrasound-guided fine-needle aspiration biopsy (FNAB) in the diagnostic algorithm for patients with PA and to assess clinical outcomes for those with different surgical approaches. Material and Methods. We carried out a retrospective analysis of patients treated for parotid gland mass between 2010 and 2016. These had had preoperative FNAB and had undergone subsequent surgery. Results. 165 patients had FNAB with the result of PA and the definitive histology confirmed PA in 159 cases (96.4%). On the other hand, in 179 patients, the definitive histology showed PA and the preoperative FNAB result corresponded in 159 cases (88.9%). The measured sensitivity, specificity and accuracy of ultrasound-guided FNAB in the diagnosis of PA were, respectively, 88.83%, 96.23% and 92.31%. Most of the patients underwent superficial or partial superficial parotidectomy, followed by extracapsular dissection which was associated with statistically lower risk of facial nerve injury (P=0.04). Conclusion.Ultrasound-guided FNAB is simple, accurate and valuable in the diagnosis of PA and provides results that can lead to the choice of less invasive operative treatment.

show abstract

Section: Discussionmentioning

confidence: 99%

Utility of fine-needle aspiration biopsy (FNAB) in parotid pleomorphic adenoma diagnosis and management

Fíková¹,

Novák²,

Kalfeřt³

et al. 2024

Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub

View full text Add to dashboard Cite

show abstract

“…Lloyd et al [17] found in a sample of 246 patients with sinonasal tumour (98% of cases). A possible explanation of these variations in sensitivity and specificity rates could be the existence of indeterminate or atypical pathology specimens that were variably considered as benign or malignant by various authors [18]. Nevertheless, CT scan seems to strongly correlate with histology of sinonasal tumours.…”

Section: Discussionmentioning

confidence: 99%

Correlation between Computed Tomography and Histopathology Findings of Sinonasal Tumors

Mouangue-Mbonjo,

Samaké,

Choffor

et al. 2023

IJOHNS

View full text Add to dashboard Cite

Background: A diverse range of pathologies affect the sinonasal cavities, because of the nonspecific nature of the symptoms, most patients with sinonasal masses are diagnosed late when the disease is at an advanced stage. The diagnostic challenge of identifying the nature of sinonasal masses before treatment would guide therapeutic strategies. Our objective was to evaluate the accuracy of computed tomography in the preoperative diagnosis of sinus masses at the Central Hospital of Yaoundé. Method: A retrospective chart review was conducted; CT scan reports and pathology reports of patients operated for sinonasal masses between January 2012 and November 2022 were compared. Results: Forty-five patients met the inclusion criteria for the study. The average age was 39.98 ± 18.34 years, with extremes of 15 and 87 years. The sex ratio H/F is 0.76 with a female predominance. The median time to consultation was 14 [12 -18] months, with extremes of 11 and 36 months. The most frequently encountered histological type was benign tumors with sinonasal polyposis (PNS) in the lead, i.e. 34.1% of cases. The types adenocarcinoma, adenoid cystic carcinoma and non-Hodgkin's lymphoma were represented equally in 6.8% of cases. Management was dominated by Caldwell-Luc surgery, i.e. 59.1% of cases. The frequency of disease recurrence after surgical treatment was 18.2%. As for the mortality rate, it was 11.4%. The concordance rate of the character of malignancy on imaging compared to histology was 90.9%. This level of concordance was statistically significant according to the Gamma test (p < 0.

show abstract

“…The features of MRI sequences are critical in the diagnosis of parotid neoplasms. 27 , 28 , 29 , 30 The present study is innovative in terms of utilizing a newly designed CNN to classify parotid gland tumors. Briefly, the first two layers of the pre‐trained Resnet‐18 were selected to extract the overall image features based on the concept of learning transfer.…”

Section: Discussionmentioning

confidence: 99%

A Deep Learning Model for Classification of Parotid Neoplasms Based on Multimodal Magnetic Resonance Image Sequences

et al. 2022

View full text Add to dashboard Cite

Objective: To design a deep learning model based on multimodal magnetic resonance image (MRI) sequences for automatic parotid neoplasm classification, and to improve the diagnostic decision-making in clinical settings.Methods: First, multimodal MRI sequences were collected from 266 patients with parotid neoplasms, and an artificial intelligence (AI)-based deep learning model was designed from scratch, combining the image classification network of Resnet and the Transformer network of Natural language processing. Second, the effectiveness of the deep learning model was improved through the multi-modality fusion of MRI sequences, and the fusion strategy of various MRI sequences was optimized. In addition, we compared the effectiveness of the model in the parotid neoplasm classification with experienced radiologists.Results: The deep learning model delivered reliable outcomes in differentiating benign and malignant parotid neoplasms. The model, which was trained by the fusion of T2-weighted, postcontrast T1-weighted, and diffusion-weighted imaging (b = 1000 s/mm 2 ), produced the best result, with an accuracy score of 0.85, an area under the receiver operator characteristic (ROC) curve of 0.96, a sensitivity score of 0.90, and a specificity score of 0.84. In addition, the multi-modal paradigm exhibited reliable outcomes in diagnosing the pleomorphic adenoma and the Warthin tumor, but not in the identification of the basal cell adenoma.Conclusion: An accurate and efficient AI based classification model was produced to classify parotid neoplasms, resulting from the fusion of multimodal MRI sequences. The effectiveness certainly outperformed the model with single MRI images or single MRI sequences as input, and potentially, experienced radiologists.

show abstract

Performance de l´imagerie par résonnance magnétique dans l´approche histopathologique des tumeurs parotidiennes

Cited by 3 publications

References 15 publications

Utility of fine-needle aspiration biopsy (FNAB) in parotid pleomorphic adenoma diagnosis and management

Utility of fine-needle aspiration biopsy (FNAB) in parotid pleomorphic adenoma diagnosis and management

Correlation between Computed Tomography and Histopathology Findings of Sinonasal Tumors

A Deep Learning Model for Classification of Parotid Neoplasms Based on Multimodal Magnetic Resonance Image Sequences

Contact Info

Product

Resources

About