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      Predicting nodal metastasis progression of oral tongue cancer using a hidden Markov model in MRI

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          Abstract

          Objectives

          The presence of occult nodal metastases in patients with oral tongue squamous cell carcinomas (OTSCCs) has implications for treatment. More than 30% of patients will have occult nodal metastases, yet a considerable number of patients undergo unnecessary invasive neck dissection to confirm nodal status. In this work, we propose a probabilistic model for lymphatic metastatic spread that can quantify the risk of microscopic involvement at the lymph node level (LNL) given the location of macroscopic metastases and the tumor stage using the MRI method.

          Materials and methods

          A total of 108 patients of OTSCCs were included in the study. A hidden Markov model (HMM) was used to compute the probabilities of transitions between states over time based on MRI. Learning of the transition probabilities was performed via Markov chain Monte Carlo sampling and was based on a dataset of OTSCC patients for whom involvement of individual LNLs was reported.

          Results

          Our model found that the most common involvement was that of level I and level II, corresponding to a high probability of ๐‘b1 = 0.39 ยฑ 0.05, ๐‘b2 = 0.53 ยฑ 0.09; lymph node level I had metastasis, and the probability of metastasis in lymph node II was high (93.79%); lymph node level II had metastasis, and the probability of metastasis in lymph node III was small (7.88%). Lymph nodes progress faster in the early stage and slower in the late stage.

          Conclusion

          An HMM can produce an algorithm that is able to predict nodal metastasis evolution in patients with OTSCCs by analyzing the macroscopic metastases observed in the upstream levels, and tumor category.

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          Most cited references29

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008.

            Estimates of the worldwide incidence and mortality from 27 cancers in 2008 have been prepared for 182 countries as part of the GLOBOCAN series published by the International Agency for Research on Cancer. In this article, we present the results for 20 world regions, summarizing the global patterns for the eight most common cancers. Overall, an estimated 12.7 million new cancer cases and 7.6 million cancer deaths occur in 2008, with 56% of new cancer cases and 63% of the cancer deaths occurring in the less developed regions of the world. The most commonly diagnosed cancers worldwide are lung (1.61 million, 12.7% of the total), breast (1.38 million, 10.9%) and colorectal cancers (1.23 million, 9.7%). The most common causes of cancer death are lung cancer (1.38 million, 18.2% of the total), stomach cancer (738,000 deaths, 9.7%) and liver cancer (696,000 deaths, 9.2%). Cancer is neither rare anywhere in the world, nor mainly confined to high-resource countries. Striking differences in the patterns of cancer from region to region are observed. Copyright © 2010 UICC.
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              NCCN Guidelines Insights: Head and Neck Cancers, Version 1.2018

              The NCCN Guidelines for Head and Neck (H&N) Cancers provide treatment recommendations for cancers of the lip, oral cavity, pharynx, larynx, ethmoid and maxillary sinuses, and salivary glands. Recommendations are also provided for occult primary of the H&N, and separate algorithms have been developed by the panel for very advanced H&N cancers. These NCCN Guidelines Insights summarize the panel's discussion and most recent recommendations regarding evaluation and treatment of nasopharyngeal carcinoma.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2612133Role: Role: Role: Role: Role: Role: Role:
                Role: Role: Role:
                Role: Role:
                URI : https://loop.frontiersin.org/people/2127363Role: Role: Role:
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                06 June 2024
                2024
                : 14
                : 1360253
                Affiliations
                [1] 1Department of Radiology, Southern Medical University Nanfang Hospital , Guangzhou, China
                [2] 2Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital , Heidelberg, Germany
                Author notes

                Edited by: Alla Reznik, Lakehead University, Canada

                Reviewed by: Yee Kai Tee, Tunku Abdul Rahman University, Malaysia

                Mirza Pojskic, University Hospital of Giessen and Marburg, Germany

                Zhao Jian, Chinese Peopleโ€™s Liberation Army General Hospital, China

                *Correspondence: Ke Zhang, ke.zhang@ 123456uni-heidelberg.de
                Article
                10.3389/fonc.2024.1360253
                11191577
                38912064
                d22a17ef-44ad-4754-9c56-dcee0d384f66
                Copyright ยฉ 2024 Gang, Feng, Kauczor and Zhang

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 December 2023
                : 16 May 2024
                Page count
                Figures: 8, Tables: 2, Equations: 0, References: 30, Pages: 11, Words: 5083
                Funding
                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
                Categories
                Oncology
                Original Research
                Custom metadata
                Head and Neck Cancer

                Oncology & Radiotherapy
                oral cavity squamous cell carcinoma,lymph node metastases,artificial intelligence,hidden markov model,level of metastatic lymph nodes

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