ABSTRACT
OBJECTIVES: Modern radiotherapy (RT) techniques require careful delineation of the target. There is no particular RT contouring guideline for patients receiving neoadjuvant chemotherapy (NACT). In this study, we examined the distribution of pre-chemotherapy clinically positive nodal metastases. METHODS: We explored the coverage rate of the RTOG breast contouring guideline by deformable fusion of 18-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) scan. We retrospectively evaluated neoadjuvant chemotherapy patients. All PET-CT images were imported into the planning software. We combined the planning CT and the CT images of PET-CT with rigid and then a deformable registration. We manually contoured positive lymph nodes on the CT component of the PET-CT data set and transferred them to planning CT after fusion. We evaluated whether previously contoured lymphatic CTVs, according to the RTOG breast atlas, include GTV-LNs. RESULTS: All breast cancer patients between October 2018 and February 2021 were evaluated from the electronic database. There were 142 radiologically defined positive lymph nodes in 31 patients who were irradiated after NACT. Most LNs (70%) were in the level I axilla. Only 71.1% (n:101) of the whole lymph nodes in 10 patients were totally covered, 22.5% (n:32) partially covered and 6.4% %(n:9) totally undercovered. CONCLUSIONS: The extent of regional nodal areas in the RTOG atlas may be insufficient to cover positive lymph nodes adequately. For patients with nodal involvement undergoing neoadjuvant chemotherapy, PET-CT image fusions can be helpful to be sure that positive lymph nodes are in the treatment volume. ADVANCES IN KNOWLEDGE: RTOG contouring atlas may be insufficient to cover all involved lymph nodes after NACT. For patients with nodal involvement undergoing neoadjuvant chemotherapy, PET-CT image fusions may help to be sure that positive lymph nodes are in the treatment volume.
Subject(s)
Breast Neoplasms , Positron Emission Tomography Computed Tomography , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , Breast Neoplasms/radiotherapy , Female , Fluorodeoxyglucose F18 , Humans , Lymph Nodes/diagnostic imaging , Lymph Nodes/pathology , Lymphatic Metastasis/diagnostic imaging , Lymphatic Metastasis/pathology , Positron Emission Tomography Computed Tomography/methods , Positron-Emission Tomography , Radiopharmaceuticals , Retrospective StudiesABSTRACT
PURPOSE: The aim of this study is 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. METHOD: In this institutional review board-approved retrospective study, we improved our previously published artificial intelligence model, by retraining it with newly collected images and testing its performance on images containing benign lymph nodes affected by COVID-19 vaccination. All the images were acquired and selected by specialized breast-imaging radiologists and the nature of each node (benign or malignant) was assessed through a strict clinical protocol using ultrasound-guided biopsies. RESULTS: 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. CONCLUSIONS: The results obtained in this study show the potential of the proposed techniques to differentiate between malignant lymph nodes and benign nodes affected by reactive changes due to COVID-19 vaccination. These techniques could be useful to non-invasively diagnose lymph node status in patients with suspicious reactive nodes, although larger multicenter studies are needed to confirm and validate the results.
Subject(s)
Breast Neoplasms , COVID-19 , Artificial Intelligence , Axilla , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , COVID-19/prevention & control , COVID-19 Vaccines , Female , Humans , Lymph Nodes/diagnostic imaging , Lymph Nodes/pathology , Lymphatic Metastasis/diagnostic imaging , Lymphatic Metastasis/pathology , Retrospective Studies , Sensitivity and Specificity , VaccinationABSTRACT
INTRODUCTION: The present analysis aims to evaluate the consequences of a 2-month interruption of mammographic screening on breast cancer (BC) stage at diagnosis and upfront treatments in a region of Northern Italy highly affected by the severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) virus. METHODS: This retrospective single-institution analysis compared the clinical pathological characteristics of BC diagnosed between May 2020 and July 2020, after a 2-month screening interruption, with BC diagnosed in the same trimester of 2019 when mammographic screening was regularly carried out. RESULTS: The 2-month stop in mammographic screening produced a significant decrease in in situ BC diagnosis (-10.4%) and an increase in node-positive (+11.2%) and stage III BC (+10.3%). A major impact was on the subgroup of patients with BC at high proliferation rates. Among these, the rate of node-positive BC increased by 18.5% and stage III by 11.4%. In the subgroup of patients with low proliferation rates, a 9.3% increase in stage III tumors was observed, although node-positive tumors remained stable. Despite screening interruption, procedures to establish a definitive diagnosis and treatment start were subsequently carried out without delay. CONCLUSION: Our data showed an increase in node-positive and stage III BC after a 2-month stop in BC screening. These findings support recommendations for a quick restoration of BC screening at full capacity, with adequate prioritization strategies to mitigate harm and meet infection prevention requirements.
Subject(s)
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , Breast Neoplasms/therapy , COVID-19 , Mass Screening/organization & administration , Aged , Breast Neoplasms/epidemiology , Breast Neoplasms, Male/diagnostic imaging , Female , Humans , Italy/epidemiology , Lymphatic Metastasis/diagnostic imaging , Male , Mammography/statistics & numerical data , Mastectomy , Middle Aged , Neoadjuvant Therapy , Retrospective Studies , Time FactorsABSTRACT
COVID-19 is the viral infection caused by SARS-CoV-2 declared by the World Health Organization (WHO) as a pandemic. Patients with cancer have a higher risk to acquire the infection and worse prognosis as they have to attend more medical visits in healthcare institutions, receive medical and surgical treatments, and be subjected to diagnostic studies such as PET/CT in nuclear medicine services where the infection may be an incidental finding. We present here F18-FDG PET/CT (Positron Emission Tomography and Computed Tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose), images with findings of COVID-19 from patients with different oncological conditions but no respiratory symptoms.
La COVID-19 es la infección viral causada por el SARS-CoV-2 y declarada por la Organización Mundial de la Salud (OMS) como pandemia. Los pacientes con cáncer tienen un mayor riesgo de adquirir la infección y un peor pronóstico, ya que deben asistir a visitas médicas en diferentes centros hospitalarios, reciben tratamientos médicos y quirúrgicos y deben someterse a estudios diagnósticos como la PET/CT en servicios de medicina nuclear, lo que es ocasión para el hallazgo incidental de la infección. Se presentan las imágenes de tomografías computarizadas por emisión de positrones con 18-fluorodesoxiglucosa (F18) (Positron Emission Tomography and Computed Tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose, PET/CT F18-FDG) en las que se evidenció la COVID-19 en pacientes con diversas enfermedades oncológicas, pero sin sintomatología respiratoria.
Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/diagnostic imaging , Incidental Findings , Neoplasms/complications , Pneumonia, Viral/diagnostic imaging , Positron Emission Tomography Computed Tomography , Adult , Aged , Asymptomatic Diseases , COVID-19 , COVID-19 Testing , Carcinoma, Signet Ring Cell/complications , Carcinoma, Signet Ring Cell/diagnostic imaging , Carcinoma, Signet Ring Cell/secondary , Clinical Laboratory Techniques , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Female , Fluorine Radioisotopes , Fluorodeoxyglucose F18 , Humans , Lymphatic Metastasis/diagnostic imaging , Lymphoma, Non-Hodgkin/complications , Lymphoma, Non-Hodgkin/diagnostic imaging , Male , Middle Aged , Neoplasms/diagnostic imaging , Pandemics , Pleural Effusion/diagnostic imaging , Pleural Effusion/etiology , Pneumonia, Viral/complications , Radiopharmaceuticals , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2 , Seminoma/complications , Seminoma/diagnostic imaging , Seminoma/secondary , Stomach NeoplasmsABSTRACT
BACKGROUND: COVID-19 pandemic required a marked re-allocation of healthcare resources, including at Breast Units. A patient-tailored program was developed to assess its efficacy regarding prevention of COVID-19 infection among patients with breast cancer undergoing surgery and healthcare workers (HCWs). PATIENTS AND METHODS: From March 9th to April 9th 2020, 91 patients were selected for elective surgery by means of: i) Pre-hospital screening aimed at avoiding hospitalization of symptomatic or suspicious COVID-19 patients, and ii) prioritisation of surgical procedure according to specific disease features. RESULTS: Eighty-five patients (93.4%) were fit for surgery, while five patients (5.5%) were temporarily excluded through 'telephone triage'; another two patients were excluded at in-hospital triage. A total of 71 out of 85 patients (83.5%) were diagnosed with invasive cancer, most of whom were undergoing breast-conserving surgery (61 out of 85 patients, 71.8%). The mean in-hospital stay was 2.2 days (SD=0.7 days). After hospital discharge, no patient needed re-admission due to post-operative complications; moreover, no COVID-19 infection among patients or HCWs was detected. CONCLUSION: Safe breast cancer surgery was accomplished for both patients and HCWs by means of a careful preoperative selection of patients and in-hospital preventative measures. This screening program can be transferred to high-volume Breast Units and it may be useful in implementing European Community recommendations for prevention of COVID-19 infection.