Your browser doesn't support javascript.
FDG PET/CT radiomics as a tool to differentiate between reactive axillary lymphadenopathy following COVID-19 vaccination and metastatic breast cancer axillary lymphadenopathy: a pilot study.
Eifer, Michal; Pinian, Hodaya; Klang, Eyal; Alhoubani, Yousef; Kanana, Nayroz; Tau, Noam; Davidson, Tima; Konen, Eli; Catalano, Onofrio A; Eshet, Yael; Domachevsky, Liran.
  • Eifer M; Department of Diagnostic Imaging, Chaim Sheba Medical Center, 2 Sheba Road, 5266202, Ramat Gan, Israel. michaleifer@gmail.com.
  • Pinian H; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. michaleifer@gmail.com.
  • Klang E; Department of Diagnostic Imaging, Chaim Sheba Medical Center, 2 Sheba Road, 5266202, Ramat Gan, Israel.
  • Alhoubani Y; Department of Diagnostic Imaging, Chaim Sheba Medical Center, 2 Sheba Road, 5266202, Ramat Gan, Israel.
  • Kanana N; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
  • Tau N; ARC Center for Digital Innovation, Chaim Sheba Medical Center, Ramat Gan, Israel.
  • Davidson T; Department of Diagnostic Imaging, Chaim Sheba Medical Center, 2 Sheba Road, 5266202, Ramat Gan, Israel.
  • Konen E; Department of Diagnostic Imaging, Chaim Sheba Medical Center, 2 Sheba Road, 5266202, Ramat Gan, Israel.
  • Catalano OA; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
  • Eshet Y; Department of Diagnostic Imaging, Chaim Sheba Medical Center, 2 Sheba Road, 5266202, Ramat Gan, Israel.
  • Domachevsky L; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Eur Radiol ; 32(9): 5921-5929, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1990616
ABSTRACT

OBJECTIVES:

To evaluate if radiomics with machine learning can differentiate between F-18-fluorodeoxyglucose (FDG)-avid breast cancer metastatic lymphadenopathy and FDG-avid COVID-19 mRNA vaccine-related axillary lymphadenopathy. MATERIALS AND

METHODS:

We retrospectively analyzed FDG-positive, pathology-proven, metastatic axillary lymph nodes in 53 breast cancer patients who had PET/CT for follow-up or staging, and FDG-positive axillary lymph nodes in 46 patients who were vaccinated with the COVID-19 mRNA vaccine. Radiomics features (110 features classified into 7 groups) were extracted from all segmented lymph nodes. Analysis was performed on PET, CT, and combined PET/CT inputs. Lymph nodes were randomly assigned to a training (n = 132) and validation cohort (n = 33) by 5-fold cross-validation. K-nearest neighbors (KNN) and random forest (RF) machine learning models were used. Performance was evaluated using an area under the receiver-operator characteristic curve (AUC-ROC) score.

RESULTS:

Axillary lymph nodes from breast cancer patients (n = 85) and COVID-19-vaccinated individuals (n = 80) were analyzed. Analysis of first-order features showed statistically significant differences (p < 0.05) in all combined PET/CT features, most PET features, and half of the CT features. The KNN model showed the best performance score for combined PET/CT and PET input with 0.98 (± 0.03) and 0.88 (± 0.07) validation AUC, and 96% (± 4%) and 85% (± 9%) validation accuracy, respectively. The RF model showed the best result for CT input with 0.96 (± 0.04) validation AUC and 90% (± 6%) validation accuracy.

CONCLUSION:

Radiomics features can differentiate between FDG-avid breast cancer metastatic and FDG-avid COVID-19 vaccine-related axillary lymphadenopathy. Such a model may have a role in differentiating benign nodes from malignant ones. KEY POINTS • Patients who were vaccinated with the COVID-19 mRNA vaccine have shown FDG-avid reactive axillary lymph nodes in PET-CT scans. • We evaluated if radiomics and machine learning can distinguish between FDG-avid metastatic axillary lymphadenopathy in breast cancer patients and FDG-avid reactive axillary lymph nodes. • Combined PET and CT radiomics data showed good test AUC (0.98) for distinguishing between metastatic axillary lymphadenopathy and post-COVID-19 vaccine-associated axillary lymphadenopathy. Therefore, the use of radiomics may have a role in differentiating between benign from malignant FDG-avid nodes.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Breast Neoplasms / Lymphadenopathy / COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid / Vaccines Limits: Female / Humans Language: English Journal: Eur Radiol Journal subject: Radiology Year: 2022 Document Type: Article Affiliation country: S00330-022-08725-3

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Breast Neoplasms / Lymphadenopathy / COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid / Vaccines Limits: Female / Humans Language: English Journal: Eur Radiol Journal subject: Radiology Year: 2022 Document Type: Article Affiliation country: S00330-022-08725-3