Magnetic Resonance Imaging In Breast Cancer Research Articles

Three-compartment spectral diffusion analysis for breast cancer magnetic resonance imaging

Rationale and objectivesTo examine the diagnostic performance of a three-compartment diffusion model with the fixed cut-off diffusion coefficient (D) using magnetic resonance spectral diffusion analysis for differentiating between invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) and compare the conventional apparent D (ADC), and mean kurtosis (MK), with the tissue D (DIVIM), perfusion D (D*IVIM), and perfusion fraction (fIVIM) calculated by conventional intravoxel incoherent motion. Patients and methodsThis retrospective study included women who underwent breast MRI with eight b-value diffusion-weighted imaging between February 2019 and March 2022. Spectral diffusion analysis was performed; very-slow, cellular, and perfusion compartments were defined using cut-off Ds of 0.1 × 10−3 and 3.0 × 10−3 mm2/s (static water D). The mean D (Ds, Dc, Dp, respectively) and fraction F (Fs, Fc, Fp, respectively) for each compartment were calculated. ADC and MK values were also calculated; receiver operating characteristic analyses were performed. ResultsHistologically confirmed 132 ICD and 62 DCIS (age range 31–87 [53 ± 11] years) were evaluated. The areas under the curve (AUCs) for ADC, MK, DIVIM, D*IVIM, fIVIM, Ds, Dc, Dp, Fs, Fc, and Fp were 0.77, 0.72, 0.77, 0.51, 0.67, 0.54, 0.78, 0.51, 0.57, 0.54, and 0.57, respectively. The AUCs for the model combining very-slow and cellular compartments and the model combining the three compartments were 0.81 each, slightly and significantly higher than for ADC, DIVIM, and Dc (P = 0.09–0.14); and MK (P < 0.05), respectively. ConclusionThree-compartment model analysis using the diffusion spectrum accurately differentiated IDC from DCIS; however, it was not superior to ADC and DIVIM. The diagnostic performance of MK was lower than that of the three-compartment model.

Patient-Specific 3D-Printed Low-Cost Models in Medical Education and Clinical Practice

3D printing has been increasingly used for medical applications with studies reporting its value, ranging from medical education to pre-surgical planning and simulation, assisting doctor-patient communication or communication with clinicians, and the development of optimal computed tomography (CT) imaging protocols. This article presents our experience of utilising a 3D-printing facility to print a range of patient-specific low-cost models for medical applications. These models include personalized models in cardiovascular disease (from congenital heart disease to aortic aneurysm, aortic dissection and coronary artery disease) and tumours (lung cancer, pancreatic cancer and biliary disease) based on CT data. Furthermore, we designed and developed novel 3D-printed models, including a 3D-printed breast model for the simulation of breast cancer magnetic resonance imaging (MRI), and calcified coronary plaques for the simulation of extensive calcifications in the coronary arteries. Most of these 3D-printed models were scanned with CT (except for the breast model which was scanned using MRI) for investigation of their educational and clinical value, with promising results achieved. The models were confirmed to be highly accurate in replicating both anatomy and pathology in different body regions with affordable costs. Our experience of producing low-cost and affordable 3D-printed models highlights the feasibility of utilizing 3D-printing technology in medical education and clinical practice.

Correlation study between the magnetic resonance imaging features of breast cancer and expression of immune molecular subtypes.

To investigate the correlation between breast cancer magnetic resonance imaging features and immune molecular subtypes. A total of 129 breast cancer patients were selected as the research object. All the patients were diagnosed by histopathology. All of them had breast magnetic resonance imaging and examination data of immunohistochemical (IHC) ER, PR, HER-2, and Ki-67. The correlation of breast cancer magnetic resonance imaging features with different immune molecular subtypes was retrospectively analyzed. Breast cancer is divided into different molecular subtypes. There were 72 cases with Luminal A type (55.81%), 20 cases with Luminal B type (15.50%), 14 cases with HER-2+ type (HER-2 type for over-expression) (10.85%), 23 cases with TNBC type (ER, PR and HER-2 were negative) (17.84%). The magnetic resonance imaging features of breast cancer were included, the post-enhanced morphology, margins, internal enhancement features, time-signal intensity curve (TIC) and molecular subtype expression of lesions were significantly correlated with the immune molecular subtypes (C=0.602, 0.439, 0.350 and 0.407, p=0.000, 0.000, 0.006 and 0.000). Lesion morphology: Luminal A type was mainly oval, accounting for 76.39% (55/76). Luminal B type and HER-2+ type was mainly irregular, accounting for 75.00% (15/20) and 64.29% (9/14) respectively. TNBC type was mainly shown as lobulation, accounting for 60.87% (14/23). Margin of the lesion: Luminal A type was mainly smooth margin, accounting for 73.61% (53/72). Luminal B type and TNBC type were mainly irregular margin, accounting for 70.00% (14/20) and 56.52% (13/23) respectively. The margin of HER-2+ type was mainly spiculation, accounting for 64.29% (9/14). The internal enhancement features: Luminal A type was mainly even enhancement, accounting for 62.50% (45/72). Luminal B type and HER-2+ type were mainly heterogeneous enhancement, accounting for 65.00% (13/20) and 64.29% (9/14) respectively. TNBC type was mainly annular enhancement, accounting for 73.91% (17/23). TIC type: Luminal A type was mainly Type II, accounting for 66.67% (48/72). Luminal B, HER-2+ type and TNBC type was mainly Type III, accounting for 70.00% (14/20), 64.29% (9/14) and 60.87% (14/23) respectively. The clinical signs include painless breast lumps, bloody breast discharge, and orange peel-like skin changes, nipple retraction and nipple elevation. There is no significant correlation between the above signs and the expression of molecular subtypes (C=0.014, 0.129, 0.154, 0.097 and 0.057, p=0.999, 0.533, 0.447, 0.747 and 0.935 respectively), the difference is not statistically significant (p>0.05). The characteristics of breast cancer magnetic resonance imaging was certainly correlated with the expression of immune molecular subtypes. The breast cancer molecular subtypes can be predicted by the imaging signs, which can provide valuable information for preoperative neoadjuvant treatment of breast cancer.

Preoperative Magnetic Resonance Imaging in Breast Cancer

The role of breast magnetic resonance imaging (MRI) in women newly diagnosed with breast cancer (BC) is controversial. This meta-analysis examines the effect of preoperative MRI compared with standard preoperative assessment on surgical outcomes, focusing on studies that used a controlled design. Using random-effects logistic meta-regression modeling, we estimated the proportion of women with each outcome in the MRI versus no-MRI groups, and calculated the odds ratio (OR) and adjusted OR (adjusted for study-level median age, and, where appropriate, for temporal effect) for each model. There were 9 eligible studies (2 randomized trials; 7 comparative cohorts). Outcomes in 3112 patients with BC (any histological tumor type) for MRI versus no-MRI (referent) were as follows: initial mastectomy 16.4% versus 8.1% [OR, 2.22 (P < 0.001); adjusted OR, 3.06 (P < 0.001)]; re-excision after initial breast conservation 11.6% versus 11.4% [OR, 1.02 (P = 0.87); adjusted OR, 0.95 (P = 0.71)]; overall mastectomy 25.5% versus 18.2% [OR, 1.54 (P < 0.001); adjusted OR, 1.51 (P < 0.001)]. In 766 patients with invasive lobular cancer (ILC), outcomes were as follows: initial mastectomy 31.1% versus 24.9% [OR, 1.36 (P = 0.056); adjusted OR, 2.12 (P = 0.008)]; re-excision after initial breast conservation 10.9% versus 18.0% [OR, 0.56 (P = 0.031); adjusted OR, 0.56 (P = 0.09)]; overall mastectomy 43.0% versus 40.2% [OR, 1.12 (P = 0.45); adjusted OR, 1.64 (P = 0.034)]. Our summary of the evidence showed that MRI significantly increased mastectomy rates and suggests an unfavorable harm-benefit ratio for routine use of preoperative MRI in BC. We found weak evidence that MRI reduced re-excision surgery in patients with ILC -although this was at the expense of increased mastectomies-and overall patient benefit from MRI in ILC is not clear from this study.

Comparative detectability of bone metastases and impact on therapy of magnetic resonance imaging and bone scintigraphy in patients with breast cancer

Objective: to evaluate the comparative impact of magnetic resonance imaging and bone scintigraphy in bone metastases of breast cancer. Methods and patients: in 81 patients with histologically proven breast cancer magnetic resonance imaging of the axial skeleton and whole-body bone scintigraphy had been performed. Images were retrospectively reviewed and compared for detection of metastases, extent of metastatic disease and therapeutic implications according to the patients’ records. Results: about 54/81 (67%) patients revealed bone metastases. In 7/54 (13%) patients with bone metastases, scintigraphy was false negative. In one patient a solitary sternal metastases was seen. In 26/53 [49%] patients with spinal metastases, magnetic resonance imaging showed more extensive disease. Local radiotherapy or surgery was indicated in ten patients with metastases not evident in bone scintigraphy, in 20 patients with positive results by both imaging modalities and in six patients with metastases of pelvis imaged by bone scintigraphy only. Conclusion: magnetic resonance imaging of the axial skeleton and pelvis appears superior for staging as only one patient had metastases merely outside the axial skeleton and local therapy was indicated even in spinal regions negative in bone scintigraphy.