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CT-based radiomics deep learning to predict lymph node metastasis in tumors

Written By : Dr. Kamal Kant Kohli Published On 2024-01-25T17:30:17+05:30  |  Updated On 25 Jan 2024 5:30 PM IST
CT-based radiomics deep learning to predict lymph node metastasis in tumors
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Tsukuba, Japan- Nonfunctional pancreatic neuroendocrine tumors, while rare, are primarily treated through surgery.

The presence or absence of lymph node metastasis considerably influences the selection of surgical and other treatment approaches.

Particularly controversial is the necessity of surgery for tumors smaller than 2 cm as current clinical guidelines provide no clear consensus. Existing methods for preoperative diagnosis of lymph node metastasis are inadequate.

To address the aforementioned challenge, the Tsukuba team has created a predictive model by integrating radiomics features extracted from CT and MRI images using artificial intelligence deep-learning techniques. This model has demonstrated an 89% success rate in predicting lymph node metastasis, a rate that rises to 91% when the model is validated with data from an external hospital. Furthermore, the performance of the model remains consistent, irrespective of the tumor size being larger or smaller than 2 cm.

In conclusion, the model can help predict lymph node metastasis. Moreover, the model equips surgeons with a crucial tool for selecting the most appropriate surgical procedures and treatment strategies, potentially transforming patient outcomes in the challenging medical field.

References: Wenchao Gu o, Yingli Chen o, Haibin Zhu o, Haidi Chen, Zongcheng Yang, Shaocong Mo, et al. Open AccessPublished:October 19, 2023DOI:https://doi.org/10.1016/j.eclinm.2023.102269

EClinicalMedicinemedical imagingtomographyRadiology
Source : EClinicalMedicine
Dr. Kamal Kant Kohli
Dr. Kamal Kant Kohli

Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751

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