Faculty Bibliography

PURPOSE/OBJECTIVE:F]FDG positron emission tomography/magnetic resonance imaging (PET/MRI) model for breast cancer diagnosis incorporating imaging biomarkers of breast tumors and contralateral healthy breast tissue. METHODS:F]FDG-PET; and for the contralateral healthy breast, background parenchymal enhancement (BPE) and amount of fibroglandular tissue (FGT) on DCE-MRI, ADCmean on DWI, and SUVmax. Histopathology served as standard of reference. Uni-, bi-, and multivariate logistic regression analyses were performed to assess the relationships between malignancy and imaging features. Predictive discrimination of benign and malignant breast lesions was examined using area under the receiver operating characteristic curve (AUC). RESULTS:There were 100 malignant and 41 benign lesions (size: median 1.9, range 0.5-10 cm). The multivariate regression model incorporating significant univariate predictors identified tumor enhancement kinetics (P = 0.0003), tumor ADCmean (P < 0.001), and BPE of the contralateral healthy breast (P = 0.0019) as independent predictors for breast cancer diagnosis. Other biomarkers did not reach significance. Combination of the three significant biomarkers achieved an AUC value of 0.98 for breast cancer diagnosis. CONCLUSION/CONCLUSIONS:F]FDG PET/MRI diagnostic model incorporating both qualitative and quantitative parameters of the tumor and the healthy contralateral tissue aids breast cancer diagnosis.

BACKGROUND:H-MRS) has been largely based on choline metabolites; however, other relevant metabolites can be detected and monitored. PURPOSE:H-MRS can be used for the noninvasive differentiation of benign and malignant breast tumors, differentiation among molecular breast cancer subtypes, and prediction of long-term survival outcomes. STUDY TYPE:Retrospective. SUBJECTS:In all, 168 women, aged ≥18 years. FIELD STRENGTH/SEQUENCE:H-MRS: PRESS with TR/TE = 2000/135 msec, water suppression, and 128 scan averages, in addition to 16 reference scans without water suppression. ASSESSMENT:MRS quantitative analysis of lipid resonances using the LCModel was performed. Histopathology was the reference standard. STATISTICAL TESTS:Categorical data were described using absolute numbers and percentages. For metric data, means (plus 95% confidence interval [CI]) and standard deviations as well as median, minimum, and maximum were calculated. Due to skewed data, the latter were more adequate; unpaired Mann-Whitney U-tests were performed to compare groups without and with Bonferroni correction. ROC analyses were also performed. RESULTS:. Six lipid metabolite peaks were quantified: L09, L13 + L16, L21 + L23, L28, L41 + L43, and L52 + L53. Malignant lesions showed lower L09, L21 + L23, and L52 + L53 than benign lesions (P = 0.022, 0.027, and 0.0006). Similar results were observed for Luminal A or Luminal A/B vs. other molecular subtypes. At follow-up, patients were split into two groups based on median values for the six peaks; recurrence-free survival was significantly different between groups for L09, L21 + L23, and L28 (P = 0.0173, 0.0024, and 0.0045). DATA CONCLUSION:H-MRS assessment of lipid metabolism may provide an additional noninvasive imaging biomarker to guide therapeutic decisions in breast cancer. LEVEL OF EVIDENCE:3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:239-249.

MRI of the breast is the most sensitive test for breast cancer detection and outperforms conventional imaging with mammography, digital breast tomosynthesis, or ultrasound. However, the long scan time and relatively high costs limit its widespread use. Hence, it is currently only routinely implemented in the screening of women at an increased risk of breast cancer. To overcome these limitations, abbreviated dynamic contrast-enhanced (DCE)-MRI protocols have been introduced that substantially shorten image acquisition and interpretation time while maintaining a high diagnostic accuracy. Efforts to develop abbreviated MRI protocols reflect the increasing scrutiny of the disproportionate contribution of radiology to the rising overall healthcare expenditures. Healthcare policy makers are now focusing on curbing the use of advanced imaging examinations such as MRI while continuing to promote the quality and appropriateness of imaging. An important cornerstone of value-based healthcare defines value as the patient's outcome over costs. Therefore, the concept of a fast, abbreviated MRI exam is very appealing, given its high diagnostic accuracy coupled with the possibility of a marked reduction in the cost of an MRI examination. Given recent concerns about gadolinium-based contrast agents, unenhanced MRI techniques such as diffusion-weighted imaging (DWI) are also being investigated for breast cancer diagnosis. Although further larger prospective studies, standardized imaging protocol, and reproducibility studies are necessary, initial results with abbreviated MRI protocols suggest that it seems feasible to offer screening breast DCE-MRI to a broader population. This article aims to give an overview of abbreviated and fast breast MRI protocols, their utility for breast cancer detection, and their emerging role in the new value-based healthcare paradigm that has replaced the fee-for-service model.

OBJECTIVES/OBJECTIVE:Increasing awareness of potential side effects from gadolinium-based contrast agents has underlined the need for contrast-free magnetic resonance imaging (MRI). Numerous recent articles evaluated the risk of potential brain deposits, with the result that research is putting the focus more on alternative unenhanced imaging techniques. The aim of this study was to determine the need for contrast media for chest MRI in primary staging and follow-up care of lymphoma. METHODS:This monocentric, retrospective study encompassed patients under 25 years of age who had undergone histopathological examination of thoracic lymph nodes and at least one chest MRI examination with unenhanced and contrast-enhanced sequences. Seven different thoracic lymph node stations including mediastinal, hilar, periclavicular, and axillary regions were evaluated by two readers regarding lesion diameter, number, shape, necrosis, and infiltration of surrounding structures. Findings were categorized into suspicious (> 1 cm; round; necrosis; infiltration) or non-suspicious. RESULTS:Fifty-one patients (mean age, 16.0 ± 3.7 yrs) with thoracic Hodgkin (70.6%) and non-Hodgkin lymphoma (25.5%) and lymphadenopathy (3.9%) were retrospectively included. Most lymph nodes categorized as suspicious were located in the mediastinal station (86.4%). High agreement (κ = 0.81) between unenhanced and contrast-enhanced sequences was found for both suspicious and non-suspicious lymph nodes. Significant (p < 0.001), but small difference (1 mm) was observed only in sizing mediastinal lymph nodes (all other p > 0.05). No significant difference (smallest p = 0.08) was shown for the use of five different types of contrast media. CONCLUSION/CONCLUSIONS:MRI in young patients with thoracic lymphoma can safely be done without the use of contrast agent. KEY POINT/CONCLUSIONS:• Thoracic magnetic resonance imaging in young lymphoma patients can safely be done without gadolinium-based contrast agents.

OBJECTIVE:The purpose of this study was to compare radiation dose and image quality of single- and dual-energy CT (SECT, DECT) examinations of the chest in matched cohorts for second and third-generation dual-source CT (DSCT) systems. MATERIALS AND METHODS:We analyzed 200 patients (100 men; mean age, 61.7 ± 14.8 years old; 100 women, mean age, 59.4 ± 15.1 years old), matched by sex and body mass index, who had undergone clinically indicated contrast-enhanced chest CT. Four study groups, each consisting of 50 patients, were evaluated. Contrast-enhanced chest CT was performed using vendor-preset second-generation DSCT (group A, 120-kV SECT; group C, 80/Sn140-kV DECT) or third-generation DSCT (group B, 90-kV SECT; group D, 90/Sn150-kV DECT) protocols. Radiation dose assessment was normalized to a scan range of 27.5 cm. Image quality was objectively analyzed using dose-independent figure-of-merit (FOM) contrast-to-noise ratio (CNR) calculations and subjectively evaluated by three independent radiologists. RESULTS:Direct comparison of effective radiation dose for second-generation DSCT groups A and C showed statistically significant lower radiation dose values for DECT compared with SECT acquisition (3.2 ± 1.2 mSv vs 2.3 ± 0.6 mSv, p ≤ 0.004), but differences between third-generation SECT and DECT were not significant (1.2 ± 0.9 mSv vs 1.3 ± 0.6 mSv, p = 0.412). FOM CNR analysis revealed highest values for third-generation DECT (p ≤ 0.043). Differences in subjective image quality between the four groups were not statistically significant (p ≥ 0.179). CONCLUSION:Contrast-enhanced DECT examinations of the chest can be performed routinely with second- and third-generation DSCT systems without either increased radiation exposure or decreased image quality compared with SECT acquisition.

BACKGROUND:-weighted imaging are most strongly associated with a breast cancer diagnosis. PURPOSE/HYPOTHESIS:-weighted imaging, and DWI with apparent diffusion coefficient (ADC) mapping. STUDY TYPE:Retrospective. SUBJECTS:In all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwent mpMRI from December 2010 to September 2014. FIELD STRENGTH/SEQUENCE:IR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBE Volume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography with stochastic Trajectories. ASSESSMENT:/sec for differentiation between benign and malignant lesions. Histopathology was the standard of reference. STATISTICAL TESTS:test, Fisher's exact test, Kruskal-Wallis test, Pearson correlation coefficient, multivariate logistic regression analysis, Hosmer-Lemeshow test of goodness-of-fit, receiver operating characteristics analysis. RESULTS:-weighted imaging does not significantly contribute to breast cancer diagnosis. LEVEL OF EVIDENCE:3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:864-874.

PURPOSE OF REVIEW/UNASSIGNED:Breast density, or the amount of fibroglandular tissue in the breast, has become a recognized and independent marker for breast cancer risk. Public awareness of breast density as a possible risk factor for breast cancer has resulted in legislation for risk stratification purposes in many US states. This review will provide a comprehensive overview of the currently available imaging modalities for qualitative and quantitative breast density assessment and the current evidence on breast density and breast cancer risk assessment. RECENT FINDINGS/UNASSIGNED:To date, breast density assessment is mainly performed with mammography and to some extent with magnetic resonance imaging. Data indicate that computerized, quantitative techniques in comparison with subjective visual estimations are characterized by higher reproducibility and robustness. SUMMARY/UNASSIGNED:Breast density reduces the sensitivity of mammography due to a masking effect and is also a recognized independent risk factor for breast cancer. Standardized breast density assessment using automated volumetric quantitative methods has the potential to be used for risk prediction and stratification and in determining the best screening plan for each woman.

OBJECTIVE:To investigate if histogram analysis and visually assessed heterogeneity of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping can predict molecular subtypes of invasive breast cancers. MATERIALS AND METHODS:In this retrospective study, 91 patients with invasive breast carcinoma who underwent preoperative magnetic resonance imaging (MRI) with DWI at our institution were included. Two radiologists delineated a 2-D region of interest (ROI) on ADC maps in consensus. Tumors were also independently classified into low and high heterogeneity based on visual assessment of DWI. First-order statistics extracted through histogram analysis within the ROI of the ADC maps (mean, 10th percentile, 50th percentile, 90th percentile, standard deviation, kurtosis, and skewness) and visually assessed heterogeneity were evaluated for associations with tumor receptor status (ER, PR, and HER2 status) as well as molecular subtype. RESULTS:=0.040), with AUCs of 0.605, 0.592, and 0.652, respectively, than HER2-negative lesions. No significant differences were found in the histogram values for ER and PR statuses. Neither quantitative histogram analysis based on ADC maps nor qualitative visual heterogeneity assessment of DWI images was able to significantly differentiate between molecular subtypes, i.e., luminal A versus all other subtypes (luminal B, HER2-enriched, and triple negative) combined, luminal A and B combined versus HER2-enriched and triple negative combined, and triple negative versus all other types combined. CONCLUSION:Histogram analysis and visual heterogeneity assessment cannot be used to differentiate molecular subtypes of invasive breast cancer.

OBJECTIVE:The aim of this study was to investigate a novel version of a computer-aided diagnosis (CAD) system developed for automated bone age (BA) assessment in comparison to the Greulich and Pyle method, regarding its accuracy and the influence of carpal bones on BA assessment. METHODS:Total BA, BA of the left distal radius, and BA of carpal bones in 305 patients were determined independently by 3 blinded radiologists and assessed by the CAD system. Pearson product-moment correlation, Bland-Altman plot, root-mean-square deviation, and further agreement analyses were computed. RESULTS:Mean total BA and BA of the distal radius showed high correlation between both approaches (r = 0.985 and r = 0.963). There was significantly higher correlation between values of total BA and BA of the distal radius (r = 0.969) compared with values of total BA and BA of carpal bones (r = 0.923). The assessment of carpal bones showed significantly lower interreader agreement compared with measurements of the distal radius (κ = 0.79 vs κ = 0.98). CONCLUSION/CONCLUSIONS:A novel version of a CAD system enables highly accurate automated BA assessment. The assessment of carpal bones revealed lower precision and interreader agreement. Therefore, methods determining BA without analyzing carpal bones may be more precise and accurate.

Within the field of oncology, "omics" strategies-genomics, transcriptomics, proteomics, metabolomics-have many potential applications and may significantly improve our understanding of the underlying processes of cancer development and progression. Omics strategies aim to develop meaningful imaging biomarkers for breast cancer (BC) by rapid assessment of large datasets with different biological information. In BC the paradigm of omics technologies has always favored the integration of multiple layers of omics data to achieve a complete portrait of BC. Advances in medical imaging technologies, image analysis, and the development of high-throughput methods that can extract and correlate multiple imaging parameters with "omics" data have ushered in a new direction in medical research. Radiogenomics is a novel omics strategy that aims to correlate imaging characteristics (i. e., the imaging phenotype) with underlying gene expression patterns, gene mutations, and other genome-related characteristics. Radiogenomics not only represents the evolution in the radiology-pathology correlation from the anatomical-histological level to the molecular level, but it is also a pivotal step in the omics paradigm in BC in order to fully characterize BC. Armed with modern analytical software tools, radiogenomics leads to new discoveries of quantitative and qualitative imaging biomarkers that offer hitherto unprecedented insights into the complex tumor biology and facilitate a deeper understanding of cancer development and progression. The field of radiogenomics in breast cancer is rapidly evolving, and results from previous studies are encouraging. It can be expected that radiogenomics will play an important role in the future and has the potential to revolutionize the diagnosis, treatment, and prognosis of BC patients. This article aims to give an overview of breast radiogenomics, its current role, future applications, and challenges.