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Oral Oncology ◽  
2022 ◽  
Vol 125 ◽  
pp. 105684
Author(s):  
Shikhar Sawhney ◽  
Shivakumar Thiagarajan ◽  
Arun Balaji ◽  
Pranav Sathe ◽  
Siddhanth Jain ◽  
...  

Author(s):  
Yun-Huan (Barry) Hsieh ◽  
Nidal Al Deek ◽  
Fu-Chan Wei

2021 ◽  
Vol 28 ◽  
Author(s):  
Kai Zhang ◽  
Junlong Da ◽  
Xiaoyao Liu ◽  
Xinpeng Liu ◽  
Jianqun Wang ◽  
...  

2021 ◽  
Author(s):  
Sarthak Tandon ◽  
Parveen Ahlawat ◽  
Sunil Pasricha ◽  
Sandeep Purohit ◽  
David K. Simson ◽  
...  

Author(s):  
Sophie Deneuve ◽  
Olivia Pérol ◽  
Emmanuelle Dantony ◽  
Anne‐Valérie Guizard ◽  
Nadine Bossard ◽  
...  

2021 ◽  
Vol 11 ◽  
Author(s):  
Caterina Giannitto ◽  
Giuseppe Mercante ◽  
Luca Disconzi ◽  
Riccardo Boroni ◽  
Elena Casiraghi ◽  
...  

BackgroundA surgical margin is the apparently healthy tissue around a tumor which has been removed. In oral cavity carcinoma, a negative margin is considered ≥ 5 mm, a close margin between 1 and 5 mm, and a positive margin ≤ 1 mm. Currently, the intraoperative surgical margin status is based on the visual inspection and tissue palpation by the surgeon and intraoperative histopathological assessment of the resection margins by frozen section analysis (FSA). FSA technique is limited and susceptible to sampling errors. Definitive information on the deep resection margins requires postoperative histopathological analysis.MethodsWe described a novel approach for the assessment of intraoperative surgical margins by examining a surgical specimen oriented through a 3D-printed specific patient tongue with real-time Magnetic Resonance Imaging (MRI). We reported the preliminary results of a case series of 10 patients, prospectively enrolled, with oral tongue carcinoma who underwent surgery between February 2020 and April 2021. Two radiologists with 5 and 10 years of experience, respectively, in Head and Neck radiology in consensus evaluated specimen MRI and measured the distance between the tumor and the specimen surface. We performed intraoperative bedside FSA. To compare the performance of bedside FSA and MRI in predicting definitive margin status we computed the weighted sensitivity (SE), specificity (SP), accuracy (ACC), area under the ROC curve (AUC), F1-score, Positive Predictive Value (PPV), and Negative Predictive Value (NPV). To express the concordance between FSA and ex-vivo MRI we reported the jaccard index.ResultsIntraoperative bedside FSA showed SE of 90%, SP of 100%, F1 of 95%, ACC of 0.9%, PPV of 100%, NPV (not a number), and jaccard of 90%, and ex-vivo MRI showed SE of 100%, SP of 100%, F1 of 100%, ACC of 100%, PPV of 100%, NPV of 100%, and jaccard of 100%. These results needed to be validated in a larger sample size of 21- 44 patients.ConclusionThe presented method allows a more accurate evaluation of surgical margin status, and the first clinical experiences underline the high potential of integrating FSA with ex-vivo MRI of the fresh surgical specimen.


Author(s):  
V.L. Brasileiro Junior ◽  
C.F.W. Nonaka ◽  
A.K.G. Gonzaga ◽  
C.C. de Oliveira Ramos ◽  
L. Pereira Pinto ◽  
...  

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