The role of radiomics in tongue cancer: A new tool for prognosis prediction

Abstract

Background: Radiomics represents an emerging field of precision-medicine. Its application in head and neck is still at the beginning. Methods: Retrospective study about magnetic resonance imaging (MRI) based radiomics in oral tongue squamous cell carcinoma (OTSCC) surgically treated (2010-2019; 79 patients). All preoperative MRIs include different sequences (T1, T2, DWI, ADC). Tumor volume was manually segmented and exported to radiomic-software, to perform feature extraction. Statistically significant

Radiomics analysis of intraoral ultrasound images for prediction of late cervical lymph node metastasis in patients with tongue cancer

“…7 The machine learning model with radiomics features yielded better results for the prediction of cervical lymph node metastasis compared with the deep learning model using ultrasonographic images or measurements of the longest diameter and thickness in previous reports. Most studies using radiomics analysis have used CT 14 or MRI, 12 and few have used ultrasonographic images, mainly been due to uncertainty regarding the obtained images. Recently, however, some radiomics studies using ultrasonographic images have been reported, including several studies involving comprehensive liver tumor evaluations, including differential diagnosis and clinical prognosis, 27 and prediction of lymph node metastasis in breast cancer 28 and in the head and neck region.…”

“…Most studies using radiomics analysis have used CT 14 or MRI, 12 and few have used ultrasonographic images, mainly been due to uncertainty regarding the obtained images. Recently, however, some radiomics studies using ultrasonographic images have been reported, including several studies involving comprehensive liver tumor evaluations, including differential diagnosis and clinical prognosis, 27 and prediction of lymph node metastasis in breast cancer 28 and in the head and neck region.…”

“…Previous studies have performed radiomics analysis using medical images to extract image features for lesion diagnosis and prognosis prediction, a widely used method in recent years. [12][13][14][15][16] Various studies on prognostic prediction in patients with head and neck cancer used magnetic resonance imaging (MRI) 12 or positron emission tomography (PET)/computed tomography (CT) images, 13 predicted occult lymph node metastasis using CT images, 14 evaluated the response to radiotherapy, 15 and predicted adverse events after radiotherapy. 16 In the present study, we aimed to investigate the association between late cervical lymph node metastasis and imaging features using radiomics analysis and machine learning models on ultrasonographic images of the tongue in patients with tongue cancer.…”

“…Previous studies have performed radiomics analysis using medical images to extract image features for lesion diagnosis and prognosis prediction, a widely used method in recent years 12–16 . Various studies on prognostic prediction in patients with head and neck cancer used magnetic resonance imaging (MRI) 12 or positron emission tomography (PET)/computed tomography (CT) images, 13 predicted occult lymph node metastasis using CT images, 14 evaluated the response to radiotherapy, 15 and predicted adverse events after radiotherapy 16 …”

Radiomics-Based Analysis in the Prediction of Occult Lymph Node Metastases in Patients with Oral Cancer: A Systematic Review

“…In recent years, due to the development of ML algorithms coupled with more accessible digital data, more and more researchers have begun to focus on predicting molecular biomarkers, therapeutic responses, and survival prognostic factors in patients with head and neck (HN) carcinomas by extracting radiomics information features (e.g., shape description, intensity, or texture characteristics) from different imaging patterns (e.g., CT, MRI, PET, ultrasound images) [11]; in Mossinelli's [12] retrospective study on 79 patients with oral tongue squamous cell carcinoma (OTSCC) MRI-based radiomics represents a promising noninvasive method of precision medicine, improving prognosis prediction before surgery.…”