Medical Dialogues
  • Dermatology
Login Register
This site is intended for healthcare professionals only
Login Register
  • Medical Jobs
  • Medical Matrimony
  • MD Brand Connect
  • MDTV
    • Breaking News
    • Medical News Today
    • Health News Today
    • Latest
    • Journal Club
    • Medico Legal Update
    • Latest Webinars
    • MD Shorts
    • Health Dialogues
Medical Dialogues
  • Medical News & Guidelines
      • Anesthesiology
      • Cardiology and CTVS
      • Critical Care
      • Dentistry
      • Dermatology
      • Diabetes and Endocrinology
      • ENT
      • Gastroenterology
      • Medicine
      • Nephrology
      • Neurology
      • Obstretics-Gynaecology
      • Oncology
      • Ophthalmology
      • Orthopaedics
      • Pediatrics-Neonatology
      • Psychiatry
      • Pulmonology
      • Radiology
      • Surgery
      • Urology
      • Laboratory Medicine
      • Diet
      • Nursing
      • Paramedical
      • Physiotherapy
  • Health news
      • Doctor News
      • Government Policies
      • Hospital & Diagnostics
      • International Health News
      • MCI News
      • Medical Organization News
      • Medico Legal News
      • NBE News
      • NMC News
  • AYUSH
    • Ayurveda
    • Homeopathy
    • Siddha
    • Unani
    • Yoga
  • State News
      • Andaman and Nicobar Islands
      • Andhra Pradesh
      • Arunachal Pradesh
      • Assam
      • Bihar
      • Chandigarh
      • Chattisgarh
      • Dadra and Nagar Haveli
      • Daman and Diu
      • Delhi
      • Goa
      • Gujarat
      • Haryana
      • Himachal Pradesh
      • Jammu & Kashmir
      • Jharkhand
      • Karnataka
      • Kerala
      • Ladakh
      • Lakshadweep
      • Madhya Pradesh
      • Maharashtra
      • Manipur
      • Meghalaya
      • Mizoram
      • Nagaland
      • Odisha
      • Puducherry
      • Punjab
      • Rajasthan
      • Sikkim
      • Tamil Nadu
      • Telangana
      • Tripura
      • Uttar Pradesh
      • Uttrakhand
      • West Bengal
  • Medical Education
      • Ayush Education News
      • Dentistry Education News
      • Medical Admission News
      • Medical Colleges News
      • Medical Courses News
      • Medical Universities News
      • Nursing education News
      • Paramedical Education News
      • Study Aborad
  • Industry
      • Health Investment News
      • Health Startup News
      • Medical Devices News
      • Pharma News
      • Pharmacy Education News
      • Industry Perspective
  • MDTV
      • Health Dialogues MDTV
      • Health News today MDTV
      • Latest Videos MDTV
      • Latest Webinars MDTV
      • MD shorts MDTV
      • Medical News Today MDTV
      • Medico Legal Update MDTV
      • Top Videos MDTV
      • Health Perspectives MDTV
      • Journal Club MDTV
This site is intended for healthcare professionals only
LoginRegister
Medical Dialogues
LoginRegister
  • Home
  • Medical news & Guidelines
    • Anesthesiology
    • Cardiology and CTVS
    • Critical Care
    • Dentistry
    • Dermatology
    • Diabetes and Endocrinology
    • ENT
    • Gastroenterology
    • Medicine
    • Nephrology
    • Neurology
    • Obstretics-Gynaecology
    • Oncology
    • Ophthalmology
    • Orthopaedics
    • Pediatrics-Neonatology
    • Psychiatry
    • Pulmonology
    • Radiology
    • Surgery
    • Urology
    • Laboratory Medicine
    • Diet
    • Nursing
    • Paramedical
    • Physiotherapy
  • Health news
    • Doctor News
    • Government Policies
    • Hospital & Diagnostics
    • International Health News
    • MCI News
    • Medical Organization News
    • Medico Legal News
    • NBE News
    • NMC News
  • AYUSH
    • Ayurveda
      • Ayurveda Giuidelines
      • Ayurveda News
    • Homeopathy
      • Homeopathy Guidelines
      • Homeopathy News
    • Siddha
      • Siddha Guidelines
      • Siddha News
    • Unani
      • Unani Guidelines
      • Unani News
    • Yoga
      • Yoga Guidelines
      • Yoga News
  • State News
    • Andaman and Nicobar Islands
    • Andhra Pradesh
    • Arunachal Pradesh
    • Assam
    • Bihar
    • Chandigarh
    • Chattisgarh
    • Dadra and Nagar Haveli
    • Daman and Diu
    • Delhi
    • Goa
    • Gujarat
    • Haryana
    • Himachal Pradesh
    • Jammu & Kashmir
    • Jharkhand
    • Karnataka
    • Kerala
    • Ladakh
    • Lakshadweep
    • Madhya Pradesh
    • Maharashtra
    • Manipur
    • Meghalaya
    • Mizoram
    • Nagaland
    • Odisha
    • Puducherry
    • Punjab
    • Rajasthan
    • Sikkim
    • Tamil Nadu
    • Telangana
    • Tripura
    • Uttar Pradesh
    • Uttrakhand
    • West Bengal
  • Medical Education
    • Ayush Education News
    • Dentistry Education News
    • Medical Admission News
    • Medical Colleges News
    • Medical Courses News
    • Medical Universities News
    • Nursing education News
    • Paramedical Education News
    • Study Aborad
  • Industry
    • Health Investment News
    • Health Startup News
    • Medical Devices News
    • Pharma News
      • CDSCO (Central Drugs Standard Control Organisation) News
    • Pharmacy Education News
    • Industry Perspective
  • Home
  • Radiology
  • Radiology News
  • Machine learning...

Machine learning methods can differentiate malignancy from reactive benign changes due to COVID-19 shot

Medha BaranwalWritten by Medha Baranwal Published On 2022-09-16T19:30:50+05:30  |  Updated On 2022-09-16T19:30:55+05:30
Machine learning methods can differentiate malignancy from reactive benign changes due to COVID-19 shot

Spain: Machine learning methods can differentiate between malignant and benign lymph nodes that react as a side effect of COVID-19 vaccination, suggests a recent study in the European Journal of Radiology. These techniques can be used for the non-invasive diagnosis of lymph node status in patients with suspicious reactive nodes. The institutional review board-approved retrospective study...

Spain: Machine learning methods can differentiate between malignant and benign lymph nodes that react as a side effect of COVID-19 vaccination, suggests a recent study in the European Journal of Radiology. These techniques can be used for the non-invasive diagnosis of lymph node status in patients with suspicious reactive nodes. 

The institutional review board-approved retrospective study was conducted by David Coronado-Gutiérrez, Hospital Clínic de Barcelona (University of Barcelona) and Hospital Sant Joan de Deu, Barcelona, Spain, and colleagues with the objective to assess the potential of quantitative image analysis and machine learning techniques to differentiate between malignant lymph nodes and benign lymph nodes affected by reactive changes due to COVID-19 vaccination.

The researchers improved their previously published artificial intelligence model by retraining it with newly collected images. They tested the performance on images containing benign lymph nodes affected by COVID-19 vaccination. Specialized breast-imaging radiologists acquired and selected all the images. The nature of each node (benign or malignant) was assessed through a strict clinical protocol using ultrasound-guided biopsies. 

The findings of the study were as follows:

· A total of 180 new images from 154 different patients were recruited: 71 images (10 cases and 61 controls) were used to retrain the old model and 109 images (36 cases and 73 controls) were used to evaluate its performance.

· The achieved accuracy of the proposed method was 92.7% with 77.8% sensitivity and 100% specificity at the optimal cut-off point.

· In comparison, the visual node inspection made by radiologists from ultrasound images reached 69.7% accuracy with 41.7% sensitivity and 83.6% specificity.

"Image analysis and machine learning methods can be used to differentiate between malignant lymph nodes affected by metastatic breast cancer and benign lymph nodes affected by reactive changes due to COVID-19 vaccination," wrote the authors.

"These techniques are useful for the non-invasive diagnosis of lymph node status in patients with and without diagnosed breast cancer with suspicious reactive nodes," they concluded. "Larger, multicenter studies are required to confirm and validate the results of our study."

Reference:

Coronado-Gutiérrez D, Ganau S, Bargalló X, Úbeda B, Porta M, Sanfeliu E, Burgos-Artizzu XP. Quantitative ultrasound image analysis of axillary lymph nodes to differentiate malignancy from reactive benign changes due to COVID-19 vaccination. Eur J Radiol. 2022 Sep;154:110438. doi: 10.1016/j.ejrad.2022.110438. Epub 2022 Jul 7. PMCID: PMC9259511.

European Journal of Radiology ultrasound machine learning breast cancer 
Source : European Journal of Radiology
Medha Baranwal
Medha Baranwal

    MSc. Biotechnology

    Medha Baranwal joined Medical Dialogues as an Editor in 2018 for Speciality Medical Dialogues. She covers several medical specialties including Cardiac Sciences, Dentistry, Diabetes and Endo, Diagnostics, ENT, Gastroenterology, Neurosciences, and Radiology. She has completed her Bachelors in Biomedical Sciences from DU and then pursued Masters in Biotechnology from Amity University. She has a working experience of 5 years in the field of medical research writing, scientific writing, content writing, and content management. She can be contacted at  editorial@medicaldialogues.in. Contact no. 011-43720751

    Show Full Article
    Next Story
    Similar Posts
    NO DATA FOUND

    Editorial

    Journal Club Today

    Health News Today

    © 2022 All Rights Reserved.
    Powered By: Hocalwire
    X
    X
    We use cookies for analytics, advertising and to improve our site. You agree to our use of cookies by continuing to use our site. To know more, see our Cookie Policy and Cookie Settings.Ok