OBJECTIVE: The aim of this study was to measure the apparent diffusion coefficient (ADC) value at the region with the highest FDG uptake using sequential (18)F-FDG PET and MRI, and to correlate it with the histological grade of invasive ductal carcinoma (IDC) of the breast. METHODS: A retrospective study was conducted on 75 untreated patients with IDC. First, a PET/CT scan and subsequent breast MRI were done and the SUVmax of the each breast tumor was recorded. Then, a PET image and ADC map were co-registered. On the axial slice containing the pixel with SUVmax, we drew multiple circular ROIs within the tumor and measured the mean ADC value of each ROI. The average (ADC-mean) and minimum (ADC-min) of the mean ADC values for all ROIs within the tumor were calculated, respectively. Then, a circular ROI was placed at the corresponding location to the pixel with the highest SUV and the mean ADC value of the ROI was denoted as ADC-PET. We compared the averages of the ADC parameters and assessed the correlations among SUVmax and ADC parameters. ROC curve and logistic regression analyses were performed to assess the utility of ADC and SUVmax for detecting histological grade 3. RESULTS: ADC-min was significantly lower than the ADC-mean or ADC-PET. All of the ADC parameters showed a negative correlation with SUVmax. The area under the ROC curve for identifying histological grade 3 using ADC-PET, ADC-min, ADC-mean and SUVmax was 0.684, 0.660, 0.633 and 0.639, respectively. By multivariate analysis, ADC-PET was a significant, independent predictor of histological grade 3 (p = 0.004). CONCLUSIONS: We estimated the ADC value at the breast tumor region with the highest FDG uptake using sequential (18)F-FDG PET and MRI. This new ADC parameter distinguished high-grade IDC, supporting the feasibility of the combined PET-MRI system in patients with breast cancer.
OBJECTIVE: The aim of this study was to measure the apparent diffusion coefficient (ADC) value at the region with the highest FDG uptake using sequential (18)F-FDG PET and MRI, and to correlate it with the histological grade of invasive ductal carcinoma (IDC) of the breast. METHODS: A retrospective study was conducted on 75 untreated patients with IDC. First, a PET/CT scan and subsequent breast MRI were done and the SUVmax of the each breast tumor was recorded. Then, a PET image and ADC map were co-registered. On the axial slice containing the pixel with SUVmax, we drew multiple circular ROIs within the tumor and measured the mean ADC value of each ROI. The average (ADC-mean) and minimum (ADC-min) of the mean ADC values for all ROIs within the tumor were calculated, respectively. Then, a circular ROI was placed at the corresponding location to the pixel with the highest SUV and the mean ADC value of the ROI was denoted as ADC-PET. We compared the averages of the ADC parameters and assessed the correlations among SUVmax and ADC parameters. ROC curve and logistic regression analyses were performed to assess the utility of ADC and SUVmax for detecting histological grade 3. RESULTS: ADC-min was significantly lower than the ADC-mean or ADC-PET. All of the ADC parameters showed a negative correlation with SUVmax. The area under the ROC curve for identifying histological grade 3 using ADC-PET, ADC-min, ADC-mean and SUVmax was 0.684, 0.660, 0.633 and 0.639, respectively. By multivariate analysis, ADC-PET was a significant, independent predictor of histological grade 3 (p = 0.004). CONCLUSIONS: We estimated the ADC value at the breast tumor region with the highest FDG uptake using sequential (18)F-FDG PET and MRI. This new ADC parameter distinguished high-grade IDC, supporting the feasibility of the combined PET-MRI system in patients with breast cancer.
Authors: Jason Ostenson; Akshat C Pujara; Artem Mikheev; Linda Moy; Sungheon G Kim; Amy N Melsaether; Komal Jhaveri; Sylvia Adams; David Faul; Christopher Glielmi; Christian Geppert; Thorsten Feiweier; Kimberly Jackson; Gene Y Cho; Fernando E Boada; Eric E Sigmund Journal: Magn Reson Med Date: 2016-10-25 Impact factor: 4.668
Authors: Mariarosaria Incoronato; Anna Maria Grimaldi; Carlo Cavaliere; Marianna Inglese; Peppino Mirabelli; Serena Monti; Umberto Ferbo; Emanuele Nicolai; Andrea Soricelli; Onofrio Antonio Catalano; Marco Aiello; Marco Salvatore Journal: Eur J Nucl Med Mol Imaging Date: 2018-04-25 Impact factor: 9.236
Authors: Yong-Il Kim; Gi Jeong Cheon; Seo Young Kang; Jin Chul Paeng; Keon Wook Kang; Dong Soo Lee; June-Key Chung Journal: EJNMMI Res Date: 2018-01-10 Impact factor: 3.138
Authors: Maren Marie Sjaastad Andreassen; Pål Erik Goa; Torill Eidhammer Sjøbakk; Roja Hedayati; Hans Petter Eikesdal; Callie Deng; Agnes Østlie; Steinar Lundgren; Tone Frost Bathen; Neil Peter Jerome Journal: MAGMA Date: 2019-09-27 Impact factor: 2.310