Head And Neck
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Oral Oncology ◽  
2022 ◽  
Vol 125 ◽  
pp. 105702
Author(s):  
Ryusuke Nakamoto ◽  
Jialin Zhuo ◽  
Kip E. Guja ◽  
Heying Duan ◽  
Stephanie L. Perkins ◽  
...  

Oral Oncology ◽  
2022 ◽  
Vol 125 ◽  
pp. 105709
Author(s):  
Vijay Patil ◽  
Netra Ghandade ◽  
Vanita Noronha ◽  
Nandini Menon ◽  
Kumar Prabhash

Oral Oncology ◽  
2022 ◽  
Vol 125 ◽  
pp. 105710
Author(s):  
Isabel Schausltz Pereira Faustino ◽  
Maria Georgaki ◽  
Alan Roger Santos-Silva ◽  
Pablo Agustin Vargas ◽  
Marcio Ajudarte Lopes

Oral Oncology ◽  
2022 ◽  
Vol 125 ◽  
pp. 105701
Author(s):  
Adrian I. Mendez ◽  
Jacob G.J. Wihlidal ◽  
Dean T. Eurich ◽  
Anthony C. Nichols ◽  
S. Danielle MacNeil ◽  
...  

2022 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Bin Xu ◽  
Maelle Saliba ◽  
Alan Ho ◽  
Kartik Viswanathan ◽  
Bayan Alzumaili ◽  
...  

2022 ◽  
Vol 16 (1) ◽  
Author(s):  
Yusuf Shieba ◽  
Mahmoud Khairy ◽  
Mohamed Elzouk ◽  
Albaraa Ali Mansour

Abstract Background Nodular fasciitis (NF) is a rare non-neoplastic inflammatory tumor and usually presents as a painless, rapidly growing subcutaneous soft tissue mass. The head and neck are relatively common locations for nodular fasciitis, particularly in children. NF in the trachea is rare and may evolve to a fatal condition, especially due to its rapidly growing nature that can cause life-threatening tracheal obstruction. Case presentation We report the case of a 5-year-old child with NF in the trachea and subtotal tracheal obstruction. Bronchoscopy and biopsy proved the diagnosis, and bronchoscopic excision of the tumor was performed. Conclusions NF is a rare airway tumor, occurring mostly in adults, and may presenting with pneumonia-like symptoms. Early detection of the lesion is essential to avoid life-threatening airway obstruction.


2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Jens P.E. Schouten ◽  
Samantha Noteboom ◽  
Roland M. Martens ◽  
Steven W. Mes ◽  
C. René Leemans ◽  
...  

Abstract Background  Accurate segmentation of head and neck squamous cell cancer (HNSCC) is important for radiotherapy treatment planning. Manual segmentation of these tumors is time-consuming and vulnerable to inconsistencies between experts, especially in the complex head and neck region. The aim of this study is to introduce and evaluate an automatic segmentation pipeline for HNSCC using a multi-view CNN (MV-CNN). Methods The dataset included 220 patients with primary HNSCC and availability of T1-weighted, STIR and optionally contrast-enhanced T1-weighted MR images together with a manual reference segmentation of the primary tumor by an expert. A T1-weighted standard space of the head and neck region was created to register all MRI sequences to. An MV-CNN was trained with these three MRI sequences and evaluated in terms of volumetric and spatial performance in a cross-validation by measuring intra-class correlation (ICC) and dice similarity score (DSC), respectively. Results The average manual segmented primary tumor volume was 11.8±6.70 cm3 with a median [IQR] of 13.9 [3.22-15.9] cm3. The tumor volume measured by MV-CNN was 22.8±21.1 cm3 with a median [IQR] of 16.0 [8.24-31.1] cm3. Compared to the manual segmentations, the MV-CNN scored an average ICC of 0.64±0.06 and a DSC of 0.49±0.19. Improved segmentation performance was observed with increasing primary tumor volume: the smallest tumor volume group (<3 cm3) scored a DSC of 0.26±0.16 and the largest group (>15 cm3) a DSC of 0.63±0.11 (p<0.001). The automated segmentation tended to overestimate compared to the manual reference, both around the actual primary tumor and in false positively classified healthy structures and pathologically enlarged lymph nodes. Conclusion An automatic segmentation pipeline was evaluated for primary HNSCC on MRI. The MV-CNN produced reasonable segmentation results, especially on large tumors, but overestimation decreased overall performance. In further research, the focus should be on decreasing false positives and make it valuable in treatment planning.


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