Perceptions of radiologists on structured reporting for cancer imaging-a survey by the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To assess radiologists' current use of, and opinions on, structured reporting (SR) in oncologic imaging, and to provide recommendations for a structured report template. MATERIALS AND METHODS: An online survey with 28 questions was sent to European Society of Oncologic Imaging (ESOI) members. The questionnaire had four main parts: (1) participant information, e.g., country, workplace, experience, and current SR use; (2) SR design, e.g., numbers of sections and fields, and template use; (3) clinical impact of SR, e.g., on report quality and length, workload, and communication with clinicians; and (4) preferences for an oncology-focused structured CT report. Data analysis comprised descriptive statistics, chi-square tests, and Spearman correlation coefficients. RESULTS: A total of 200 radiologists from 51 countries completed the survey: 57.0% currently utilized SR (57%), with a lower proportion within than outside of Europe (51.0 vs. 72.7%; p = 0.006). Among SR users, the majority observed markedly increased report quality (62.3%) and easier comparison to previous exams (53.5%), a slightly lower error rate (50.9%), and fewer calls/emails by clinicians (78.9%) due to SR. The perceived impact of SR on communication with clinicians (i.e., frequency of calls/emails) differed with radiologists' experience (p < 0.001), and experience also showed low but significant correlations with communication with clinicians (r = - 0.27, p = 0.003), report quality (r = 0.19, p = 0.043), and error rate (r = - 0.22, p = 0.016). Template use also affected the perceived impact of SR on report quality (p = 0.036). CONCLUSION: Radiologists regard SR in oncologic imaging favorably, with perceived positive effects on report quality, error rate, comparison of serial exams, and communication with clinicians. CLINICAL RELEVANCE STATEMENT: Radiologists believe that structured reporting in oncologic imaging improves report quality, decreases the error rate, and enables better communication with clinicians. Implementation of structured reporting in Europe is currently below the international level and needs society endorsement. KEY POINTS: • The majority of oncologic imaging specialists (57% overall; 51% in Europe) use structured reporting in clinical practice. • The vast majority of oncologic imaging specialists use templates (92.1%), which are typically cancer-specific (76.2%). • Structured reporting is perceived to markedly improve report quality, communication with clinicians, and comparison to prior scans.

Development and evaluation of a computer-based decision support system for diffuse lung diseases at high-resolution computed tomography.

BACKGROUND: High-resolution computed tomography (HRCT) is essential in narrowing the possible differential diagnoses of diffuse and interstitial lung diseases. PURPOSE: To investigate the value of a novel computer-based decision support system (CDSS) for facilitating diagnosis of diffuse lung diseases at HRCT. MATERIAL AND METHODS: A CDSS was developed that includes about 100 different illustrations of the most common HRCT signs and patterns and describes the corresponding pathologies in detail. The logical set-up of the software facilitates a structured evaluation. By selecting one or more CT patterns, the program generates a ranked list of the most likely differential diagnoses. Three independent and blinded radiology residents initially evaluated 40 cases with different lung diseases alone; after at least 12 weeks, observers re-evaluated all cases using the CDSS. RESULTS: In 40 patients, a total of 113 HRCT patterns were evaluated. The percentage of correctly classified patterns was higher with CDSS (96.8%) compared to assessment without CDSS (90.3%; P < 0.01). Moreover, the percentage of correct diagnosis (81.7% vs. 64.2%) and differential diagnoses (89.2% vs. 38.3%) were superior with CDSS compared to evaluation without CDSS (both P < 0.01). CONCLUSION: Addition of a CDSS using a structured approach providing explanations of typical HRCT patterns and graphical illustrations significantly improved the performance of trainees in characterizing and correctly identifying diffuse lung diseases.

Radiomics of high-resolution computed tomography for the differentiation between cholesteatoma and middle ear inflammation: effects of post-reconstruction methods in a dual-center study.

OBJECTIVES: To evaluate the performance of radiomic features extracted from high-resolution computed tomography (HRCT) for the differentiation between cholesteatoma and middle ear inflammation (MEI), and to investigate the impact of post-reconstruction harmonization and data resampling. METHODS: One hundred patients were included in this retrospective dual-center study: 48 with histology-proven cholesteatoma (center A: 23; center B: 25) and 52 with MEI (A: 27; B: 25). Radiomic features (co-occurrence and run-length matrix, absolute gradient, autoregressive model, Haar wavelet transform) were extracted from manually defined 2D-ROIs. The ten best features for lesion differentiation were selected using probability of error and average correlation coefficients. A multi-layer perceptron feed-forward artificial neural network (MLP-ANN) was used for radiomics-based classification, with histopathology serving as the reference standard (70% of cases for training, 30% for validation). The analysis was performed five times each on (a) unmodified data and on data that were (b) resampled to the same matrix size, and (c) corrected for acquisition protocol differences using ComBat harmonization. RESULTS: Using unmodified data, the MLP-ANN classification yielded an overall median area under the receiver operating characteristic curve (AUC) of 0.78 (0.72-0.84). Using original data from center A and resampled data from center B, an overall median AUC of 0.88 (0.82-0.99) was yielded, while using ComBat harmonized data, an overall median AUC of 0.89 (0.79-0.92) was revealed. CONCLUSION: Radiomic features extracted from HRCT differentiate between cholesteatoma and MEI. When using multi-centric data obtained with differences in CT acquisition parameters, data resampling and ComBat post-reconstruction harmonization clearly improve radiomics-based lesion classification. KEY POINTS: • Unenhanced high-resolution CT coupled with radiomics analysis may be useful for the differentiation between cholesteatoma and middle ear inflammation. • Pooling of data extracted from inhomogeneous CT datasets does not appear meaningful without further post-processing. • When using multi-centric CT data obtained with differences in acquisition parameters, post-reconstruction harmonization and data resampling clearly improve radiomics-based soft-tissue differentiation.

Can Follow-up be Avoided for Probably Benign US Masses with No Enhancement on MRI?

OBJECTIVES: To assess whether no enhancement on pre-treatment MRI can rule out malignancy of additional US mass(es) initially assessed as BI-RADS 3 or 4 in women with newly diagnosed breast cancer. METHODS: This retrospective study included consecutive women from 2010-2018 with newly diagnosed breast cancer; at least one additional breast mass (distinct from index cancer) assigned a BI-RADS 3 or 4 on US; and a bilateral contrast-enhanced breast MRI performed within 90 days of US. All malignant masses were pathologically proven; benign masses were pathologically proven or defined as showing at least 2 years of imaging stability. Incidence of malignant masses and NPV were calculated on a per-patient level using proportions and exact 95% CIs. RESULTS: In 230 patients with 309 additional masses, 140/309 (45%) masses did not enhance while 169/309 (55%) enhanced on MRI. Of the 140 masses seen in 105 women (mean age, 54 years; range 28-82) with no enhancement on MRI, all had adequate follow-up and 140/140 (100%) were benign, of which 89/140 (63.6%) were pathologically proven and 51/140 (36.4%) demonstrated at least 2 years of imaging stability. Pre-treatment MRI demonstrating no enhancement of US mass correlate(s) had an NPV of 100% (95% CI 96.7-100.0). CONCLUSIONS: All BI-RADS 3 and 4 US masses with a non-enhancing correlate on pre-treatment MRI were benign. The incorporation of MRI, when ordered by the referring physician, may decrease unnecessary follow-up imaging and/or biopsy if the initial US BI-RADS assessment and management recommendation were to be retrospectively updated. KEY POINTS: • Of 309 BI-RADS 3 or 4 US masses with a corresponding mass on MRI, 140/309 (45%) demonstrated no enhancement whereas 169/309 (55%) demonstrated enhancement • All masses classified as BI-RADS 3 or 4 on US without enhancement on MRI were benign • MRI can rule out malignancy in non-enhancing US masses with an NPV of 100.

Radiomic signatures with contrast-enhanced magnetic resonance imaging for the assessment of breast cancer receptor status and molecular subtypes: initial results.

BACKGROUND: To evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular subtypes. METHODS: One hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, n = 49; luminal B, n = 8; HER2-enriched, n = 11; triple negative, n = 23), while the validation dataset comprised 52 patients from a second institution (luminal A, n = 17; luminal B, n = 17; triple negative, n = 18). Radiomic analysis of manually segmented tumors included calculation of features derived from the first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient (GRA), autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry (GEO). Fisher, probability of error and average correlation (POE + ACC), and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise radiomic-based separation of receptor status and molecular subtypes. Histopathology served as the standard of reference. RESULTS: In the training dataset, radiomic signatures yielded the following accuracies > 80%: luminal B vs. luminal A, 84.2% (mainly based on COM features); luminal B vs. triple negative, 83.9% (mainly based on GEO features); luminal B vs. all others, 89% (mainly based on COM features); and HER2-enriched vs. all others, 81.3% (mainly based on COM features). Radiomic signatures were successfully validated in the separate validation dataset for luminal A vs. luminal B (79.4%) and luminal B vs. triple negative (77.1%). CONCLUSIONS: In this preliminary study, radiomic signatures with CE-MRI enable the assessment of breast cancer receptor status and molecular subtypes with high diagnostic accuracy. These results need to be confirmed in future larger studies.

Limited role of DWI with apparent diffusion coefficient mapping in breast lesions presenting as non-mass enhancement on dynamic contrast-enhanced MRI.

BACKGROUND: Available data proving the value of DWI for breast cancer diagnosis is mainly for enhancing masses; DWI may be less sensitive and specific in non-mass enhancement (NME) lesions. The objective of this study was to assess the diagnostic accuracy of DWI using different ROI measurement approaches and ADC metrics in breast lesions presenting as NME lesions on dynamic contrast-enhanced (DCE) MRI. METHODS: In this retrospective study, 95 patients who underwent multiparametric MRI with DCE and DWI from September 2007 to July 2013 and who were diagnosed with a suspicious NME (BI-RADS 4/5) were included. Twenty-nine patients were excluded for lesion non-visibility on DWI (n = 24: 12 benign and 12 malignant) and poor DWI quality (n = 5: 1 benign and 4 malignant). Two readers independently assessed DWI and DCE-MRI findings in two separate randomized readings using different ADC metrics and ROI approaches. NME lesions were classified as either benign (> 1.3 × 10-3 mm2/s) or malignant (≤ 1.3 × 10-3 mm2/s). Histopathology was the standard of reference. ROC curves were plotted, and AUCs were determined. Concordance correlation coefficient (CCC) was measured. RESULTS: There were 39 malignant (59%) and 27 benign (41%) lesions in 66 (65 women, 1 man) patients (mean age, 51.8 years). The mean ADC value of the darkest part of the tumor (Dptu) achieved the highest diagnostic accuracy, with AUCs of up to 0.71. Inter-reader agreement was highest with Dptu ADC max (CCC 0.42) and lowest with the point tumor (Ptu) ADC min (CCC = - 0.01). Intra-reader agreement was highest with Wtu ADC mean (CCC = 0.44 for reader 1, 0.41 for reader 2), but this was not associated with the highest diagnostic accuracy. CONCLUSIONS: Diagnostic accuracy of DWI with ADC mapping is limited in NME lesions. Thirty-one percent of lesions presenting as NME on DCE-MRI could not be evaluated with DWI, and therefore, DCE-MRI remains indispensable. Best results were achieved using Dptu 2D ROI measurement and ADC mean.

Mammographic screening in male patients at high risk for breast cancer: is it worth it?

PURPOSE: To investigate the utility of mammography for breast cancer screening in a population of males at increased risk for breast cancer. METHODS: In this HIPAA-compliant institutional review board-approved single-institution study, mammography records and clinical data of 827 male patients who underwent digital mammography from September 2011-July 2018 were analyzed via the electronic medical record. 664 of these men presented with masses, pain, or nipple discharge and were excluded from this study. The remaining 163 asymptomatic men with familial and/or personal history of breast cancer, or with a known germline mutation in BRCA, underwent screening mammography and were included in this analysis. RESULTS: 163 asymptomatic men (age: mean 63 years, range 24-87 years) underwent 806 screening mammograms. 125/163 (77%) had a personal history of breast cancer and 72/163 (44%) had a family history of breast cancer. 24/163 (15%) were known mutation carriers: 4/24 (17%) BRCA1 and 20/24 (83%) BRCA2. 792/806 (98%) of the screening mammograms were negative (BI-RADS 1 or 2); 10/806 (1.2%) were classified as BI-RADS 3, all of which were eventually downgraded to BI-RADS 2 on follow-up. 4/806 (0.4%) mammograms were abnormal (BI-RADS 4/5): all were malignant. The cancer detection rate in this cohort was 4.9 cancers/1000 examinations. CONCLUSIONS: In our cohort, screening mammography yielded a cancer detection rate of 4.9 cancers/1000 examinations which is like the detection rate of screening mammography in a population of women at average risk, indicating that screening mammography is of value in male patients at high risk for breast cancer.

A multiparametric [18F]FDG PET/MRI diagnostic model including imaging biomarkers of the tumor and contralateral healthy breast tissue aids breast cancer diagnosis.

PURPOSE: To develop a multiparametric [18F]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: In this prospective study and retrospective data analysis, 141 patients (mean 57 years) with an imaging abnormality detected on mammography and/or ultrasound (BI-RADS 4/5) underwent combined multiparametric [18F]FDG PET/MRI with PET/computed tomography and multiparametric MRI of the breast at 3 T. Images were evaluated and the following were recorded: for the tumor, BI-RADS descriptors on dynamic contrast-enhanced (DCE)-MRI, mean apparent diffusion co-efficient (ADCmean) on diffusion-weighted imaging (DWI), and maximum standard uptake value (SUVmax) on [18F]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: A multiparametric [18F]FDG PET/MRI diagnostic model incorporating both qualitative and quantitative parameters of the tumor and the healthy contralateral tissue aids breast cancer diagnosis.

Proton MR spectroscopy in the breast: Technical innovations and clinical applications.

Proton magnetic resonance spectroscopy (MRS) is a promising noninvasive diagnostic technique for investigation of breast cancer metabolism. Spectroscopic imaging data may be obtained following contrast-enhanced MRI by applying the point-resolved spectroscopy sequence (PRESS) or the stimulated echo acquisition mode (STEAM) sequence from the MR voxel encompassing the breast lesion. Total choline signal (tCho) measured in vivo using either a qualitative or quantitative approach has been used as a diagnostic test in the workup of malignant breast lesions. In addition to tCho metabolites, other relevant metabolites, including multiple lipids, can be detected and monitored. MRS has been heavily investigated as an adjunct to morphologic and dynamic MRI to improve diagnostic accuracy in breast cancer, obviating unnecessary benign biopsies. Besides its use in the staging of breast cancer, other promising applications have been recently investigated, including the assessment of treatment response and therapy monitoring. This review provides guidance on spectroscopic acquisition and quantification methods and highlights current and evolving clinical applications of proton MRS. Level of Evidence 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

Abbreviated MRI of the Breast: Does It Provide Value?

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. Level of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:e85-e100.

Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy.

BACKGROUND: The MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI protocol contain T2 -weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imaging (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, and T2 -weighted imaging are most strongly associated with a breast cancer diagnosis. PURPOSE/HYPOTHESIS: To develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating American College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2 -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: Two radiologists in consensus and another radiologist independently evaluated the mpMRI data. Characteristics for mass (n = 182) and nonmass (n = 28) lesions were recorded on DCE and T2 -weighted imaging according to BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2 -weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoff value of ≤1.25 × 10-3 mm2 /sec for differentiation between benign and malignant lesions. Histopathology was the standard of reference. STATISTICAL TESTS: χ2 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: In Model 1, ADCmean (P = 0.0031), mass margins with DCE (P = 0.0016), and delayed enhancement with DCE (P = 0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean (P = 0.0031), mass margins with DCE (P = 0.0012), initial enhancement (P = 0.0422), and delayed enhancement with DCE (P = 0.0065) to be significantly independently associated with breast cancer diagnosis. T2 -weighted imaging variables were not included in the final models. DATA CONCLUSION: mpMRI with DCE-MRI and DWI with ADC mapping enables accurate breast cancer diagnosis. A model using quantitative and qualitative descriptors from DCE-MRI and DWI identifies breast cancer with a high diagnostic accuracy. T2 -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.

Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping as a quantitative imaging biomarker for prediction of immunohistochemical receptor status, proliferation rate, and molecular subtypes of breast cancer.

BACKGROUND: Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping is one of the most useful additional MRI parameters to improve diagnostic accuracy and is now often used in a multiparameric imaging setting for breast tumor detection and characterization. PURPOSE: To evaluate whether different ADC metrics can also be used for prediction of receptor status, proliferation rate, and molecular subtype in invasive breast cancer. STUDY TYPE: Retrospective. SUBJECTS: In all, 107 patients with invasive breast cancer met the inclusion criteria (mean age 57 years, range 32-87) and underwent multiparametric breast MRI. FIELD STRENGTH/SEQUENCE: 3 T, readout-segmented echo planar imaging (rsEPI) with IR fat suppression, dynamic contrast-enhanced (DCE) T1 -weighted imaging, T2 -weighted turbo-spin echo (TSE) with fatsat. ASSESSMENT: Two readers independently drew a region of interest on ADC maps on the whole tumor (WTu), and on its darkest part (DpTu). Minimum, mean, and maximum ADC values of both WTu and DpTu were compared for receptor status, proliferation rate, and molecular subtypes. STATISTICAL TESTS: Wilcoxon rank sum, Mann-Whitney U-tests for associations between radiologic features and histopathology; histogram and q-q plots, Shapiro-Wilk's test to assess normality, concordance correlation coefficient for precision and accuracy; receiver operating characteristics curve analysis. RESULTS: Estrogen receptor (ER) and progesterone receptor (PR) status had significantly different ADC values for both readers. Maximum WTu (P = 0.0004 and 0.0005) and mean WTu (P = 0.0101 and 0.0136) were significantly lower for ER-positive tumors, while PR-positive tumors had significantly lower maximum WTu values (P = 0.0089 and 0.0047). Maximum WTu ADC was the only metric that was significantly different for molecular subtypes for both readers (P = 0.0100 and 0.0132) and enabled differentiation of luminal tumors from nonluminal (P = 0.0068 and 0.0069) with an area under the curve of 0.685 for both readers. DATA CONCLUSION: Maximum WTu ADC values may be used to differentiate luminal from other molecular subtypes of breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:836-846.

Quantitative in vivo proton MR spectroscopic assessment of lipid metabolism: Value for breast cancer diagnosis and prognosis.

BACKGROUND: Breast magnetic resonance spectroscopy (1 H-MRS) has been largely based on choline metabolites; however, other relevant metabolites can be detected and monitored. PURPOSE: To investigate whether lipid metabolite concentrations detected with 1 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: Dynamic contrast-enhanced MRI at 1.5 T: sagittal 3D spoiled gradient recalled sequence with fat saturation, flip angle = 10°, repetition time / echo time (TR/TE) = 7.4/4.2 msec, slice thickness = 3.0 mm, field of view (FOV) = 20 cm, and matrix size = 256 × 192. 1 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: There were 111 malignant and 57 benign lesions. Mean voxel size was 4.4 ± 4.6 cm3 . 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: Quantitative in vivo 1 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.

Gadolinium-enhanced imaging of pediatric thoracic lymphoma: is intravenous contrast really necessary?

OBJECTIVES: 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: MRI in young patients with thoracic lymphoma can safely be done without the use of contrast agent. KEY POINT: • Thoracic magnetic resonance imaging in young lymphoma patients can safely be done without gadolinium-based contrast agents.

Comparison of Radiation Dose and Image Quality of Contrast-Enhanced Dual-Source CT of the Chest: Single-Versus Dual-Energy and Second-Versus Third-Generation Technology.

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.

Evaluation of a Computer-Aided Diagnosis System for Automated Bone Age Assessment in Comparison to the Greulich-Pyle Atlas Method: A Multireader Study.

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: 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.

MRI evaluation of axillary and intramammary lymph nodes in the postoperative period.

Our study aimed to evaluate if breast-conserving surgery and adjuvant treatment could affect the morphological features of axillary and intramammary lymph nodes on magnetic resonance imaging (MRI) in patients with invasive breast cancer and clinically negative axilla. In this single-center study, we retrospectively evaluated 50 patients who had (a) breast-conserving surgery, (b) clinically negative axilla, (c) preoperative MRI within 3 months before surgery, and (d) postoperative MRI within 12 months after surgery. Axillary and intramammary lymph nodes on postoperative MRI were identified and then compared with preoperative MRI by two breast radiologists with regards to the following: enlargement, cortical thickening, presence of fatty hilum, irregularity, heterogeneity, matting, and axillary lymph node asymmetry. Three hundred and two axillary and eight intramammary lymph nodes were evaluated. Enlargement and cortical thickening were seen in 5/50 (10%) patients in three axillary and two intramammary lymph nodes. None of the lymph nodes on postoperative MRI demonstrated occurrence of lack of fatty hilum, irregularity, heterogeneity, matting or axillary lymph node asymmetry. No evidence of recurrence was observed on 2-year follow-up. Lymph node enlargement and cortical thickening may be observed in a few patients in the postoperative period. Nevertheless, in patients with clinically negative axilla, these changes in morphology are often related to treatment rather than malignancy and favor short-term follow-up as an alternative to lymph node biopsy.

Optimisation of window settings for traditional and noise-optimised virtual monoenergetic imaging in dual-energy computed tomography pulmonary angiography.

OBJECTIVES: To define optimal window settings for displaying virtual monoenergetic images (VMI) of dual-energy CT pulmonary angiography (DE-CTPA). METHODS: Forty-five patients who underwent clinically-indicated third-generation dual-source DE-CTPA were retrospectively evaluated. Standard linearly-blended (M_0.6), 70-keV traditional VMI (M70), and 40-keV noise-optimised VMI (M40+) reconstructions were analysed. For M70 and M40+ datasets, the subjectively best window setting (width and level, B-W/L) was independently determined by two observers and subsequently related with pulmonary artery attenuation to calculate separate optimised values (O-W/L) using linear regression. Subjective evaluation of image quality (IQ) between W/L settings were assessed by two additional readers. Repeated measures of variance were performed to compare W/L settings and IQ indices between M_0.6, M70, and M40+. RESULTS: B-W/L and O-W/L for M70 were 460/140 and 450/140, and were 1100/380 and 1070/380 for M40+, respectively, differing from standard DE-CTPA W/L settings (450/100). Highest subjective scores were observed for M40+ regarding vascular contrast, embolism demarcation, and overall IQ (all p<0.001). CONCLUSIONS: Application of O-W/L settings is beneficial to optimise subjective IQ of VMI reconstructions of DE-CTPA. A width slightly less than two times the pulmonary trunk attenuation and a level approximately of overall pulmonary vessel attenuation are recommended. KEY POINTS: • Application of standard window settings for VMI results in inferior image perception. • No significant differences between B-W/L and O-W/L for M70/M40+ were observed. • O-W/L for M70 were 450/140 and were 1070/380 for M40+. • Improved subjective IQ characteristics were observed for VMI displayed with O-W/L.

Noise-Optimized Virtual Monoenergetic Dual-Energy CT Improves Diagnostic Accuracy for the Detection of Active Arterial Bleeding of the Abdomen.

PURPOSE: To evaluate diagnostic accuracy of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique for detection of active arterial abdominal bleeding on dual-energy (DE) CT angiography compared with standard image reconstruction. MATERIALS AND METHODS: DE CT angiography data sets of 71 patients (46 men; age 63.6 y ± 13.3) with suspected arterial bleeding of the abdomen or pelvis were reconstructed with standard linearly blended (F_0.5), VMI+, and traditional virtual monoenergetic imaging (VMI) algorithms in 10-keV increments from 40 to 100 keV. Attenuation measurements were performed in the descending aorta, area of hemorrhage, and feeding artery to calculate contrast-to-noise ratios (CNRs) in patients with active arterial bleeding. Based on quantitative image quality results, the best series for each reconstruction technique were chosen to analyze the diagnostic performance of 3 blinded radiologists. RESULTS: DE CT angiography showed acute arterial bleeding in 36 patients. Mean CNR was superior in 40-keV VMI+ compared with VMI series (all P < .001), which showed highest CNRs in 70-keV VMI and F_0.5 (21.6 ± 7.9, 12.9 ± 4.7, and 10.4 ± 3.6) images. Area under the curve analysis for detection of arterial bleeding showed significantly superior (P < .001) results for 40-keV VMI+ (0.963) compared with 70-keV VMI (0.775) and F_0.5 (0.817) series. CONCLUSIONS: Diagnostic accuracy in patients with active arterial bleeding of the abdomen can be significantly improved using VMI+ reconstructions at 40 keV compared with standard linearly blended and traditional VMI series in DE CT angiography.

Detecting Intracranial Hemorrhage Using Automatic Tube Current Modulation With Advanced Modeled Iterative Reconstruction in Unenhanced Head Single- and Dual-Energy Dual-Source CT.

OBJECTIVE: The purpose of our study was to determine diagnostic accuracy, image quality, and radiation dose of low-dose single- and dual-energy unenhanced third-generation dual-source head CT for detection of intracranial hemorrhage (ICH). MATERIALS AND METHODS: A total of 123 patients with suspected ICH were examined using a dual-source 192-MDCT scanner. Standard-dose 120-kVp single-energy CT (SECT; n = 36) and 80-kVp and 150-kVp dual-energy CT (DECT; n = 30) images were compared with low-dose SECT (n = 32) and DECT (n = 25) images obtained using automated tube current modulation (ATCM). Advanced modeled iterative reconstruction (ADMIRE) was used for all protocols. Detection of ICH was performed by three readers who were blinded to the image acquisition parameters of each image series. Image quality was assessed both quantitatively and qualitatively. Interobserver agreement was calculated using the Fleiss kappa. Radiation dose was measured as dose-length product (DLP). RESULTS: Detection of ICH was excellent (sensitivity, 94.9-100%; specificity, 94.7-100%) in all protocols (p = 1.00) with perfect interobserver agreement (0.83-0.96). Qualitative ratings showed significantly better ratings for both standard-dose protocols regarding gray matter-to-white matter contrast (p ≤ 0.014), whereas highest gray matter-to-white matter contrast-to-noise ratio was observed with low-dose DECT images (p ≥ 0.057). The lowest posterior fossa artifact index was measured for standard-dose DECT, which showed significantly lower values compared with low-dose protocols (p ≤ 0.034). Delineation of ventricular margins and sharpness of subarachnoidal spaces were rated excellent in all protocols (p ≥ 0.096). Low-dose techniques lowered radiation dose by 26% for SECT images (DLP, 575.0 ± 72.3 mGy · cm vs 771.5 ± 146.8 mGy · cm; p < 0.001) and by 24% in DECT images (DLP, 587.0 ± 103.2 mGy · cm vs 770.6 ± 90.2 mGy · cm; p < 0.001). No significant difference was observed between the low-dose protocols (p = 1.00). CONCLUSION: Low-dose unenhanced head SECT and DECT using ATCM and ADMIRE provide excellent diagnostic accuracy for detection of ICH with good quantitative and qualitative image quality in third-generation dual-source CT while allowing significant radiation dose reduction.