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Background MRI with contrast material enhancement is the imaging modality of choice to evaluate sonographically indeterminate adnexal masses. The role of diffusion-weighted MRI, however, remains controversial. Purpose To evaluate the diagnostic performance of ultra-high-b-value diffusion kurtosis MRI in discriminating benign and malignant ovarian lesions. Materials and Methods This prospective cohort study evaluated consecutive women with sonographically indeterminate adnexal masses between November 2016 and December 2018. MRI at 3.0 T was performed, including diffusion-weighted MRI (b values of 0-2000 sec/mm2). Lesions were segmented on b of 1500 sec/mm2 by two readers in consensus and an additional independent reader by using full-lesion segmentations on a single transversal slice. Apparent diffusion coefficient (ADC) calculation and kurtosis fitting were performed. Differences in ADC, kurtosis-derived ADC (Dapp), and apparent kurtosis coefficient (Kapp) between malignant and benign lesions were assessed by using a logistic mixed model. Area under the receiver operating characteristic curve (AUC) for ADC, Dapp, and Kapp to discriminate malignant from benign lesions was calculated, as was specificity at a sensitivity level of 100%. Results from two independent reads were compared. Histopathologic analysis served as the reference standard. Results A total of 79 ovarian lesions in 58 women (mean age ± standard deviation, 48 years ± 14) were evaluated. Sixty-two (78%) lesions showed benign and 17 (22%) lesions showed malignant histologic findings. ADC and Dapp were lower and Kapp was higher in malignant lesions: median ADC, Dapp, and Kapp were 0.74 µm2/msec (range, 0.52-1.44 µm2/msec), 0.98 µm2/msec (range, 0.63-2.12 µm2/msec), and 1.01 (range, 0.69-1.30) for malignant lesions, and 1.13 µm2/msec (range, 0.35-2.63 µm2/msec), 1.45 µm2/msec (range, 0.44-3.34 µm2/msec), and 0.65 (range, 0.44-1.43) for benign lesions (P values of .01, .02, < .001, respectively). AUC for Kapp of 0.85 (95% confidence interval: 0.77, 0.94) was higher than was AUC from ADC of 0.78 (95% confidence interval: 0.67, 0.89; P = .047). Conclusion Diffusion-weighted MRI by using quantitative kurtosis variables is superior to apparent diffusion coefficient values in discriminating benign and malignant ovarian lesions and might be of future help in clinical practice, especially in patients with contraindication to contrast media application. © RSNA, 2020 Online supplemental material is available for this article.

OBJECTIVES Quantitative T1 relaxometry is the benchmark in imaging potential gadolinium deposition and known to be superior to semiquantitative signal intensity ratio analyses. However, T1 relaxometry studies are rare, commonly limited to a few target structures, and reported results are inconsistent.We systematically investigated quantitative T1 relaxation times (qT1) of a variety of brain nuclei after serial application of gadobutrol. MATERIALS AND METHODS Retrospectively, qT1 measurements were performed in a patient cohort with a mean number of 11 gadobutrol applications (n = 46) and compared with a control group with no prior gadolinium-based contrast agent administration (n = 48). The following target structures were evaluated: dentate nucleus, globus pallidus, thalamus, hippocampus, putamen, caudate, amygdala, and different white matter areas. Subsequently, multivariate regression analysis with adjustment for age, presence of brain metastases and previous cerebral radiotherapy was performed. RESULTS No assessed site revealed a significant correlation between qT1 and number of gadobutrol administrations in multivariate regression analysis. However, a significant negative correlation between qT1 and age was found for the globus pallidus as well as anterior and lateral thalamus (P < 0.05 each). CONCLUSIONS No T1 relaxation time shortening due to gadobutrol injection was found in any of the assessed brain structures after serial administration of 11 doses of gadobutrol.

Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic support for human interpretation requires further evaluation. Purpose To compare the performance of clinical assessment to a deep learning system optimized for segmentation trained with T2-weighted and diffusion MRI in the task of detection and segmentation of lesions suspicious for sPC. Materials and Methods In this retrospective study, T2-weighted and diffusion prostate MRI sequences from consecutive men examined with a single 3.0-T MRI system between 2015 and 2016 were manually segmented. Ground truth was provided by combined targeted and extended systematic MRI-transrectal US fusion biopsy, with sPC defined as International Society of Urological Pathology Gleason grade group greater than or equal to 2. By using split-sample validation, U-Net was internally validated on the training set (80% of the data) through cross validation and subsequently externally validated on the test set (20% of the data). U-Net-derived sPC probability maps were calibrated by matching sextant-based cross-validation performance to clinical performance of Prostate Imaging Reporting and Data System (PI-RADS). Performance of PI-RADS and U-Net were compared by using sensitivities, specificities, predictive values, and Dice coefficient. Results A total of 312 men (median age, 64 years; interquartile range [IQR], 58-71 years) were evaluated. The training set consisted of 250 men (median age, 64 years; IQR, 58-71 years) and the test set of 62 men (median age, 64 years; IQR, 60-69 years). In the test set, PI-RADS cutoffs greater than or equal to 3 versus cutoffs greater than or equal to 4 on a per-patient basis had sensitivity of 96% (25 of 26) versus 88% (23 of 26) at specificity of 22% (eight of 36) versus 50% (18 of 36). U-Net at probability thresholds of greater than or equal to 0.22 versus greater than or equal to 0.33 had sensitivity of 96% (25 of 26) versus 92% (24 of 26) (both P > .99) with specificity of 31% (11 of 36) versus 47% (17 of 36) (both P > .99), not statistically different from PI-RADS. Dice coefficients were 0.89 for prostate and 0.35 for MRI lesion segmentation. In the test set, coincidence of PI-RADS greater than or equal to 4 with U-Net lesions improved the positive predictive value from 48% (28 of 58) to 67% (24 of 36) for U-Net probability thresholds greater than or equal to 0.33 (P = .01), while the negative predictive value remained unchanged (83% [25 of 30] vs 83% [43 of 52]; P > .99). Conclusion U-Net trained with T2-weighted and diffusion MRI achieves similar performance to clinical Prostate Imaging Reporting and Data System assessment. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Padhani and Turkbey in this issue.

Diffusion-weighted (DW) MRI is a rapid technique that measures the mobility of water molecules within tissue, reflecting the cellular microenvironment. At DW MRI, breast cancers typically exhibit reduced diffusivity and appear hyperintense to surrounding tissues. On the basis of this characteristic, DW MRI may offer an unenhanced method to detect breast cancer without the costs and safety concerns associated with dynamic contrast material–enhanced MRI, the current reference standard in the setting of high-risk screening. This application of DW MRI has not been widely explored but is particularly timely given the growing health concerns related to the long-term use of gadolinium-based contrast material. Moreover, increasing breast density notification legislation across the United States is raising awareness of the limitations of mammography in women with dense breasts, emphasizing the need for additional cost-effective supplemental screening examinations. Preliminary studies suggest unenhanced MRI with DW MRI may provide higher sensitivity than screening mammography for the detection of breast malignancies. Larger prospective multicenter trials are needed to validate single-center findings and assess the performance of DW MRI for generalized breast cancer screening. Standardization of DW MRI acquisition and interpretation is essential to ensure reliable sensitivity and specificity, and an optimal approach for screening using readily available techniques is proposed here. © RSNA, 2019 Online supplemental material is available for this article.

The outbreak of coronavirus disease 2019 (COVID-19) with the origin of the spread assumed to be located in Wuhan, China, began in December 2019, and is continuing until now. With the COVID-19 pandemic showing a progressive spread throughout the countries of the world, there is emerging interest for the potential long-term consequences of suffering from a COVID-19 pneumonia. Imaging plays a central role in the diagnosis and management of COVID-19 pneumonia, with chest X-ray examinations and computed tomography (CT) being undoubtedly the modalities most widely used, allowing for a fast and sensitive detection of infiltration patterns associated with COVID-19 pneumonia. For a better understanding of underlying pathomechanisms of pulmonary damage, longitudinal imaging series are warranted, for which CT is of limited usability due to repeated exposure of X-rays. Recent advances in MRI suggested that high-performance low-field MRI might represent a valuable method for pulmonary imaging without the need of radiation exposure. However, so far, low-field MRI has not been applied to study pulmonary damage after COVID-19 pneumonia. We present a case report of a patient who suffered from COVID-19 pneumonia using 0.55 T MRI for follow-up examinations three months after initial infection. Low-field MRI enables a precise visualization of persistent pulmonary changes including ground-glass opacities, which are consistent with CT performed on the same day. Low-field MRI seems to be feasible in the detection of pulmonary involvement in patients with COVID-19 pneumonia and may have the potential for repetitive lung examinations in monitoring the reconvalescence after pulmonary infections.

Background Diffusion weighted magnetic resonance imaging (DWI) is known to differentiate between malignant and benign lesions via the apparent diffusion coefficient (ADC). Here, the value of diffusion kurtosis imaging (DKI) for differentiation and further characterization of benign and malignant breast lesions and their subtypes in a clinically feasible protocol is investigated. Material and methods This study included 85 patients (with 68 malignant and 73 benign lesions) who underwent 3 T breast DWI using three b values (50, 750, 1500 s/mm2), with a total measurement time Results ADC, DK and K showed significant differences between malignant and benign lesions (p Conclusion DKI parameters and conventional ADC can differentiate between malignant and benign lesions. Differentiation performance was best for ADC. Different tumor grades were significantly different in ADC and DK, which may have an impact on therapy planning and monitoring. In our study, K did not add value to the diagnostic performance of DWI in a clinical setting.

Purpose: The application of amide proton transfer (APT) CEST MRI for diagnosis of breast cancer is of emerging interest. However, APT imaging in the human breast is affected by the ubiquitous fat signal preventing a straightforward application of existing acquisition protocols. Although the spectral region of the APT signal does not coincide with fat resonances, the fat signal leads to an incorrect normalization of the Z‐spectrum, and therefore to distorted APT effects. In this study, we propose a novel normalization for APT‐CEST MRI that corrects for fat signal–induced artifacts in the postprocessing without the need for application of fat saturation schemes or water–fat separation approaches. Methods The novel normalization uses the residual signal at the spectral position of the direct water saturation to estimate the fat contribution. A comprehensive theoretical description of the normalization for an arbitrary phase relation of the water and fat signal is provided. Functionality and applicability of the proposed normalization was demonstrated by in vitro and in vivo experiments. Results In vitro, an underestimation of the conventional APT contrast of approximately −1.2% per 1% fat fraction was observed. The novel normalization yielded an APT contrast independent of the fat contribution, which was also independent of the water‐fat phase relation. This allowed APT imaging in patients with mamma carcinoma corrected for fat signal contribution, field inhomogeneities, spillover dilution, and water relaxation effects. Conclusion The proposed normalization increases the specificity of APT imaging in tissues with varying fat content and represents a time‐efficient and specific absorption rate–efficient alternative to fat saturation and water–fat separation approaches.

Medical research in the field of oncologic imaging diagnostics using magnetic resonance imaging increasingly includes diffusion-weighted imaging (DWI) sequences. The DWI sequences allow insights into different microstructural diffusion properties of water molecules in tissues depending on the sequence modification used and enable visual and quantitative analysis of the acquired imaging data. In DWI, the application of intravenous gadolinium-containing contrast agents is unnecessary and only the mobility of naturally occurring water molecules in tissues is quantified. These characteristics predispose DWI as a potential candidate for emerging as an independent diagnostic tool in selected cases and specific points in question. Current clinical diagnostic studies and the ongoing technical developments, including the increasing influence of artificial intelligence in radiology, support the growing importance of DWI. Especially with respect to selective approaches for early detection of malignancies, DWI could make an essential contribution as an eligible diagnostic tool; however, prior to discussing a broader clinical implementation, challenges regarding reliable data quality, standardization and quality assurance must be overcome.

Objectives Motivated by the similar appearance of malignant breast lesions in high b-value diffusion-weighted imaging (DWI) and positron emission tomography, the purpose of this work was to evaluate the applicability of a threshold isocontouring approach commonly used in positron emission tomography to analyze DWI data acquired from female human breasts with minimal interobserver variability. Methods Twenty-three female participants (59.4 ± 10.0 years) with 23 lesions initially classified as suggestive of cancers in x-ray mammography screening were subsequently imaged on a 1.5-T magnetic resonance imaging scanner. Diffusion-weighted imaging was performed prior to biopsy with b values of 0, 100, 750, and 1500 s/mm. Isocontouring with different threshold levels was performed on the highest b-value image to determine the voxels used for subsequent evaluation of diffusion metrics. The coefficient of variation was computed by specifying 4 different regions of interest drawn around the lesion. Additionally, a receiver operating statistical analysis was performed. Results Using a relative threshold level greater than or equal to 0.85 almost completely suppresses the intra-individual and inter-individual variability. Among 4 studied diffusion metrics, the diffusion coefficients from the intravoxel incoherent motion model returned the highest area under curve value of 0.9. The optimal cut-off diffusivity was found to be 0.85 μm/ms with a sensitivity of 87.5% and specificity of 90.9%. Conclusion Threshold isocontouring on high b-value maps is a viable approach to reliably evaluate DWI data of suspicious focal lesions in magnetic resonance mammography.

Purpose We aimed to investigate whether quantitative diffusivity variables of healthy ovaries vary during the menstrual cycle and to evaluate alterations in women using oral contraceptives (OC). Methods This prospective study (S-339/2016) included 30 healthy female volunteers, with (n = 15) and without (n = 15) intake of OC between 07/2017 and 09/2019. Participants underwent 3T diffusion-weighted MRI (b-values 0–2000 s/mm2) three times during a menstrual cycle (T1 = day 1–5; T2 = day 7–12; T3 = day 19–24). Both ovaries were manually three-dimensionally segmented on b = 1500 s/mm2; apparent diffusion coefficient (ADC) calculation and kurtosis fitting (Dapp, Kapp) were performed. Differences in ADC, Dapp and Kapp between time points and groups were compared using repeated measures ANOVA and t-test after Shapiro-Wilk and Brown-Forsythe test for normality and equal variance. Results In women with a natural menstrual cycle, ADC and kurtosis variables showed significant changes in ovaries with the dominant follicle between T1 vs T2 and T1 vs T3, whilst no differences were observed between T2 vs T3: ADC ± SD for T1 1.524 ± 0.160, T2 1.737 ± 0.160, and T3 1.747 ± 0.241 μm2/ms (p = 0.01 T2 vs T1; p = 1.0 T2 vs T3, p = 0.003 T3 vs T1); Dapp ± SD for T1 2.018 ± 0.140, T2 2.272 ± 0.189, and T3 2.230 ± 0.256 μm2/ms (p = 0.003 T2 vs T1, p = 1.0 T2 vs T3, p = 0.02 T3 vs T1); Kapp ± SD for T1 0.614 ± 0.0339, T2 0.546 ± 0.0637, and T3 0.529 ± 0.0567 (p Conclusion Physiological cycle-dependent changes in quantitative diffusivity variables of ovaries should be considered especially when interpreting radiomics analyses in reproductive women.

Recent studies showed the potential of diffusion kurtosis imaging (DKI) as a tool for improved classification of suspicious breast lesions. However, in diffusion-weighted imaging of the female breast, sufficient fat suppression is one of the main factors determining the success. In this study, the data of 198 patients examined in two study centres was analysed using standard diffusion and kurtosis evaluation methods and three DKI fitting approaches accounting phenomenologically for fat-related signal contamination of the lesions. Receiver operating characteristic curve analysis showed the highest area under the curve (AUC) for the method including fat correction terms (AUC = 0.85, p p = 0.036) using a fat correction term for the first centre, while no significant difference with no adverse effects was observed for the second centre (AUC 0.89 vs. 0.90, p = 0.95). Contamination of the signal in breast lesions with unsuppressed fat causing a reduction of diagnostic performance of diffusion kurtosis imaging may potentially be counteracted by proposed adapted evaluation methods.

Oncologic imaging focused on the detection of breast cancer is of increasing importance, with over 1.7 million new cases detected each year worldwide. MRI of the breast has been described to be one of the most sensitive imaging modalities in breast cancer detection; however, clinical use is limited due to high costs. In the past, the objective and clinical routine of oncologic imaging was to provide one extended imaging protocol covering all potential needs and clinical implications regardless of the specific clinical indication or question. Future protocols might be more focused according to a "keep it short and simple" approach, with a reduction of patient magnet time and a limited number of images to review. Rather than replacing conventional full-diagnostic breast MRI protocols, these approaches aim at introducing a new thinking in oncologic imaging using a diversification of available imaging approaches targeted to the dedicated clinical needs of the individual patient. Here we review current approaches on using abbreviated protocols that aim to increase the clinical availability and use of breast MRI for improved early detection of breast cancer. Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:647-658.

Background Chemical exchange saturation transfer (CEST) is a novel MRI technique applied to brain tumor patients. Purpose To investigate the anatomic location dependence of CEST MRI obtained at 7T and histopathological/molecular parameters in WHO IV° glioma patients. Study type Analytic prospective study. Population Twenty-one patients with newly diagnosed WHO IV° gliomas were studied prior to surgery; 11 healthy volunteers were investigated. Field strength/sequence Conventional MRI (contrast-enhanced, T2 w and diffusion-weighted imaging) at 3T and T2 w and CEST MRI at 7T was performed for patients and both patients and volunteers. Assessment Mean CEST signal intensities (nuclear-Overhauser-enhancement [NOE], amide-proton-transfer [APT], downfield NOE-suppressed APT [dns-APT]), ADC values, and histopathological/molecular parameters were evaluated with regard to hemisphere location and contact with the subventricular zone. CEST signal intensities of cerebral tissue of healthy volunteers were evaluated with regard to hemisphere discrimination. Statistical tests Spearman correlation, Mann-Whitney U-test, Wilcoxon signed-rank-test, Fisher's exact test, and area under the receiver operating curve. Results Maximum APT and dns-APT signal intensities were significantly different in right vs. left hemisphere gliomas (P = 0.037 and P = 0.007), but not in right vs. left hemisphere cerebral tissue of healthy subjects (P = 0.062-0.859). Mean ADC values were significantly decreased in right vs. left hemisphere gliomas (P = 0.044). Mean NOE signal intensity did not differ significantly between gliomas of either hemisphere (P = 0.820), but in case of subventricular zone contact (P = 0.047). A significant correlation was observed between APT and dns-APT and ADC signal intensities (rs = -0.627, P = 0.004 and rs = -0.534, P = 0.019), but not between NOE and ADC (rs = -0.341, P = 0.154). Histopathological/molecular parameters were not significantly different concerning the tumor location (P = 0.104-1.000, P = 0.286-0.696). Data conclusion APT, dns-APT, and ADC were inversely correlated and depended on the gliomas' hemisphere location. NOE showed significant dependence on subventricular zone contact. Location dependency of APT- and NOE-mediated CEST effects should be considered in clinical investigations of CEST MRI. Level of evidence 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:777-785.

Background Fibrosis is a delayed side effect of radiation therapy (RT). Connective tissue growth factor (CTGF) promotes the development of fibrosis in multiple settings, including pulmonary radiation injury. Methods To better understand the cellular interactions involved in RT-induced lung injury and the role of CTGF in these responses, microarray expression profiling was performed on lungs of irradiated and non-irradiated mice, including mice treated with the anti-CTGF antibody pamrevlumab (FG-3019). Between group comparisons (Welch’s t-tests) and principal components analyses were performed in Genespring. Results At the mRNA level, the ability of pamrevlumab to prolong survival and ameliorate RT-induced radiologic, histologic and functional lung deficits was correlated with the reversal of a clear enrichment in mast cell, macrophage, dendritic cell and mesenchymal gene signatures. Cytokine, growth factor and matrix remodeling genes that are likely to contribute to RT pneumonitis and fibrosis were elevated by RT and attenuated by pamrevlumab, and likely contribute to the cross-talk between enriched cell-types in injured lung. Conclusions CTGF inhibition had a normalizing effect on select cell-types, including immune cells not typically regarded as being regulated by CTGF. These results suggest that interactions between RT-recruited cell-types are critical to maintaining the injured state; that CTGF plays a key role in this process; and that pamrevlumab can ameliorate RT-induced lung injury in mice and may provide therapeutic benefit in other immune and fibrotic disorders. Electronic supplementary material The online version of this article (10.1186/s12931-018-0720-4) contains supplementary material, which is available to authorized users.

Purpose To explore the value and reproducibility of a novel magnetic resonance based attenuation correction (MRAC) using a CAIPIRINHA-accelerated T1-weighted Dixon 3D-VIBE sequence for whole-body PET/MRI compared to the clinical standard. Methods The PET raw data of 19 patients from clinical routine were reconstructed with standard MRAC (MRAC std ) and the novel MRAC (MRAC caipi ), a prototype CAIPIRINHA accelerated Dixon 3D-VIBE sequence, both acquired in 19 s/bed position. Volume of interests (VOIs) for liver, lung and all voxels of the total image stack were created to calculate standardized uptake values (SUV mean ) followed by inter-method agreement (Passing-Bablok regression, Bland-Altman analysis). A voxel-wise SUV comparison per patient was performed for intra-individual correlation between MRAC std and MRAC caipi . Difference images (MRAC std -MRAC caipi ) of attenuation maps and SUV images were calculated. The image quality of in/opposed-phase water and fat images obtained from MRAC caipi was assessed by two readers on a 5-point Likert-scale including intra-class coefficients for inter-reader agreement. Results SUV mean correlations of VOIs demonstrated high linearity (0.95 8 pixels). Outliers could be explained by different physiological conditions between the scans such as different segmentation of air-containing tissue, lungs, kidneys, metal implants, diaphragm edge or small air bubbles in the gastrointestinal tracts that moved between MRAC acquisitions. Nasal sinuses and the trachea were better segmented in MRAC caipi . High-resolution T1w Dixon 3D VIBE images were acquired in all cases and could be used for PET/MRI fusion. MRAC caipi images were of high diagnostic quality (4.2 ± 0.8) with 0.92-0.96 intra-class correlation. Conclusions The novel prototype MRAC caipi extends the value for attenuation correction by providing a high spatial resolution DIXON-based dataset suited for diagnostic assessment towards time-efficient whole-body PET/MRI.

Purpose To assess radiomics as a tool to determine how well lesions found suspicious on breast cancer screening X-ray mammography can be categorized into malignant and benign with unenhanced magnetic resonance (MR) mammography with diffusion-weighted imaging and T2-weighted sequences. Materials and Methods From an asymptomatic screening cohort, 50 women with mammographically suspicious findings were examined with contrast-enhanced breast MRI (ceMRI) at 1.5T. Out of this protocol an unenhanced, abbreviated diffusion-weighted imaging protocol (ueMRI) including T2-weighted, (T2w), diffusion-weighted imaging (DWI), and DWI with background suppression (DWIBS) sequences and corresponding apparent diffusion coefficient (ADC) maps were extracted. From ueMRI-derived radiomic features, three Lasso-supervised machine-learning classifiers were constructed and compared with the clinical performance of a highly experienced radiologist: 1) univariate mean ADC model, 2) unconstrained radiomic model, 3) constrained radiomic model with mandatory inclusion of mean ADC. Results The unconstrained and constrained radiomic classifiers consisted of 11 parameters each and achieved differentiation of malignant from benign lesions with a .632 + bootstrap receiver operating characteristics (ROC) area under the curve (AUC) of 84.2%/85.1%, compared to 77.4% for mean ADC and 95.9%/95.9% for the experienced radiologist using ceMRI/ueMRI. Conclusion In this pilot study we identified two ueMRI radiomics classifiers that performed well in the differentiation of malignant from benign lesions and achieved higher performance than the mean ADC parameter alone. Classification was lower than the almost perfect performance of a highly experienced breast radiologist. The potential of radiomics to provide a training-independent diagnostic decision tool is indicated. A performance reaching the human expert would be highly desirable and based on our results is considered possible when the concept is extended in larger cohorts with further development and validation of the technique. Level of Evidence: 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:604–616

INTRODUCTION Diffusion-weighted imaging (DWI) is an important part of oncological magnetic resonance imaging (MRI) examinations, especially for tertiary cancer prevention in terms of early detection of recurrent disease. However, abdominal studies can be challenged by motion artifacts, poor signal-to-noise ratios, and visibility of retroperitoneal structures, which necessitates sequence optimization depending on the investigated region. This study aims at prospectively evaluating an adapted DWI sequence ex vivo and in vivo in oncologic patients undergoing abdominal MRI. METHODS This institutional review board-approved, prospective study included phantom measurements, volunteer examinations, and oncologic patient examinations of the abdomen. Fifty-seven MRI examinations in 54 patients (mean age, 58 years; range, 21-90 years) were included into the analysis. The MRI examination were performed at a 1.5 T MRI scanner (MAGNETOM Aera; Siemens Healthcare, Erlangen, Germany) and included both a standard EPI-DWI (s-DWI; b = 50, 900 s/mm) and an adapted DWI (opt-DWI; EPI-DWI with b = 0, 50, 900, 1500 s/mm, acquisition with higher spatial resolution and optimized processing for the abdomen including motion correction, adaptive image combination, and background suppression). For b = 900 s/mm, the ratio of signal intensity in the normal tissue and the standard deviation of the noise in the surrounding air was quantitatively calculated; image quality and tissue differentiation parameters were rated by 2 independent, blinded readers using a 5-point Likert scale. Statistics included Wilcoxon signed-rank test and kappa statistic (P < 0.05/0.0125 after Bonferroni correction). RESULTS The DWI phantom demonstrated an optimized contour sharpness and inlay differentiation for opt-DWI. The apparent ratio of normal tissue signal/standard deviation of background noise at b = 900 s/mm of the right/left hemiabdomen was significantly increased in opt-DWI (mean, 71.9 ± 23.5/86.0 ± 43.3) versus s-DWI (mean, 51.4 ± 15.4/63.4 ± 36.5; P < 0.001). Image quality parameters (contour sharpness and tissue differentiation of upper abdominal and retroperitoneal structures) were significantly increased in opt-DWI versus s-DWI (P < 0.001). Interreader reliability test showed good agreement (kappa = 0.768; P < 0.001). DISCUSSION This study prospectively evaluated the potential of adapted DWI for screening in tertiary prevention of oncologic patients. An optimized DWI protocol with advanced processing achieved improved image quality in quantitative and qualitative analyses. Oncological optimization of DWI should be performed before its application in cancer patients to improve both screening and follow-up examinations, to better unleash the diagnostic potential of DWI.

The purpose of this study was to investigate the association of relaxation-compensated chemical exchange saturation transfer (CEST) MRI with overall survival (OS) and progression-free survival (PFS) in newly diagnosed high-grade glioma (HGG) patients. Twenty-six patients with newly diagnosed high-grade glioma (WHO grades III–IV) were included in this prospective IRB-approved study. CEST MRI was performed on a 7.0-T whole-body scanner. Association of patient OS/PFS with relaxation-compensated CEST MRI (amide proton transfer (APT), relayed nuclear Overhauser effect (rNOE)/NOE, downfield-rNOE-suppressed APT (dns-APT)) and diffusion-weighted imaging (apparent diffusion coefficient) were assessed using the univariate Cox proportional hazards regression model. Hazard ratios (HRs) and corresponding 95% confidence intervals were calculated. Furthermore, OS/PFS association with clinical parameters (age, gender, O6-methylguanine-DNA methyltransferase (MGMT) promotor methylation status, and therapy: biopsy + radio-chemotherapy vs. debulking surgery + radio-chemotherapy) were tested accordingly. Relaxation-compensated APT MRI was significantly correlated with patient OS (HR = 3.15, p = 0.02) and PFS (HR = 1.83, p = 0.009). The strongest association with PFS was found for the dns-APT metric (HR = 2.61, p = 0.002). These results still stand for the relaxation-compensated APT contrasts in a homogenous subcohort of n = 22 glioblastoma patients with isocitrate dehydrogenase (IDH) wild-type status. Among the tested clinical parameters, patient age (HR = 1.1, p = 0.001) and therapy (HR = 3.68, p = 0.026) were significant for OS; age additionally for PFS (HR = 1.04, p = 0.048). Relaxation-compensated APT MRI signal intensity is associated with overall survival and progression-free survival in newly diagnosed, previously untreated glioma patients and may, therefore, help to customize treatment and response monitoring in the future. • Amide proton transfer (APT) MRI signal intensity is associated with overall survival and progression in glioma patients. • Relaxation compensation enhances the information value of APT MRI in tumors. • Chemical exchange saturation transfer (CEST) MRI may serve as a non-invasive biomarker to predict prognosis and customize treatment.

Introduction To evaluate the feasibility and accuracy of a semiautomatic, three-dimensional volume of interest (3D sphere) for measuring the apparent diffusion coefficient (ADC) in suspicious breast lesions compared to conventional single-slice two-dimensional regions of interest (2D ROIs). Method This institutional-review-board-approved study included 56 participants with Breast Imaging Reporting and Data System 4/5 lesion. All received diffusion-weighted imaging magnetic resonance imaging prior to biopsy ( b =0–1500 s/mm 2 ). ADC values were measured in the lesions with both methods. Reproducibility and accuracies were compared. Results Area under the curve was 0.93 [95% confidence interval (CI) 0.86–0.99] for the 3D sphere and 0.91 (95% CI 0.84–0.98) for the 2D ROIs without significantly differing reproducibility ( P =.45). Conclusion A semiautomatic 3D sphere could reliably estimate ADC values in suspicious breast lesions without significant difference compared to conventional 2D ROIs.

Purpose Chemical exchange sensitive spin-lock and related techniques allow to observe the uptake of administered D-glucose in vivo. The exchange-weighting increases with the magnetic field strength, but inhomogeneities in the radiofrequency (RF) field at ultrahigh field whole-body scanners lead to artifacts in conventional spin-lock experiments. Thus, our aim was the development of an adiabatically prepared T1ρ-based imaging sequence applicable to studies of glucose metabolism in tumor patients at ultrahigh field strengths. Methods An adiabatically prepared on-resonant spin-lock approach was realized at a 7 Tesla whole-body scanner and compared with conventional spin-lock. The insensitivity to RF field inhomogeneities as well as the chemical exchange sensitivity of the approach was investigated in simulations, model solutions and in the human brain. Results The suggested spin-lock approach was shown to be feasible for in vivo application at ultrahigh field whole-body scanners and showed substantially improved image quality compared with conventional spin-lock. The sensitivity of the presented method to glucose was verified in model solutions and a glucose contrast was observed in a glioblastoma patient after intravenous administration of glucose solution. Conclusion An adiabatically prepared spin-lock preparation was presented that enables a homogeneous and chemical exchange sensitive T1ρ-based imaging at ultra-high field whole-body scanners, e.g., for T1ρ-based dynamic glucose enhanced MRI. Magn Reson Med 78:215–225, 2017. © 2016 International Society for Magnetic Resonance in Medicine

Background Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique that was established in the clinical routine primarily for the detection of brain ischemia. In the past 15 years its clinical use has been extended to oncological radiology, as tumor and metastases can be depicted in DWI due to their hypercellular nature. Principles The basis of DWI is the Stejskal-Tanner experiment. The diffusion properties of tissue can be visualized after acquisition of at least two diffusion-weighted series using echo planar imaging and a specific sequence of gradient pulses. Clinical applications The use of DWI in prostate MRI was reported to be one of the first established applications that found its way into internationally recognized clinical guidelines of the European Society of Urological Radiology (ESUR) and the prostate imaging reporting and data system (PI-RADS) scale. Due to recently reported high specificity and negative predictive values of 94% and 92%, respectively, its regular use for breast MRI is expected in the near future. Furthermore, DWI can also reliably be used for whole-body imaging in patients with multiple myeloma or for measuring the extent of bone metastases. Outlook New techniques in DWI, such as intravoxel incoherent motion imaging, diffusion kurtosis imaging and histogram-based analyses represent promising approaches to achieve a more quantitative evaluation for tumor detection and therapy response.

AIM The aim of this study was to evaluate the robustness of radiomics features of a MRI (magnetic resonance imaging) phantom in quantitative diffusion-weighted imaging (DWI) and depending on the image resolution. MATERIALS AND METHODS Scanning of an in-house developed DWI phantom was performed at a 1.5 T MRI scanner (Magnetom AERA, Siemens, Erlangen, Germany) using an echo planar imaging (EPI) DWI sequence (b=0,500,1,000 s/mm2) with low (3×3 mm2) and high (2×2 mm2) image resolutions. Scans were repeated after phantom repositioning to evaluate retest reliability. Radiomics features were extracted after semi-automatic segmentation and standardised pre-processing. Intra-/interobserver reproducibility and test–retest robustness were assessed using intraclass correlation coefficients (ICC). Differences were tested with non-parametric Wilcoxon's signed-rank and Friedman's test (p RESULTS Test–retest ICC was overall high with >0.90 for 39/46 radiomics features in all sequences/resolutions. Decreased test–retest ICCs were pronounced for conventional Min-value (overall ICC=0.817), and grey-level zone length matrix (GLZLM) features Short-Zone Emphasis (SZE) and Short-Zone Low Grey-level Emphasis (SZLGE) (for both overall ICC=0.927). Test–retest reproducibility was significantly different between b=500, 1,000 and apparent diffusion coefficient (ADC) (mean 0.975±0.050, 0.974±0.051 and 0.966±0.063), which remained significant after post-hoc analysis between b=1,000 and ADC (p = 0.022). ICCs were not significantly different between resolutions of 2×2 and 3×3 mm2 regarding b=500 (mean: 0.977±0.052 and 0.974±0.049, p = 0.612), b=1,000 (mean: 0.973±0.059 and 0.974±0.054, p = 0.516), and ADC (mean: 0.972±0.049 and 0.955±0.101, p = 0.851). Inter- and intra-observer reliability was consistently high for all sequences (overall mean 0.992±0.021 and 0.990±0.028). CONCLUSION Under ex-vivo conditions, DWI provided robust radiomics features with those from ADC being slightly less robust than from raw DWI (b=500, 1,000 s/mm2). No significant difference was detected for different resolutions. Although, ex-vivo reliability of DWI radiomics features was high, no implications can be made regarding in-vivo analyses.

Purpose To investigate whether fat-corrected and relaxation-compensated amide proton transfer (APT) and guanidyl CEST-MRI enables the detection of signal intensity differences between breast tumors and normal-appearing fibroglandular tissue in patients with newly-diagnosed breast cancer. Method Ten patients with newly-diagnosed breast cancer and seven healthy volunteers were included in this prospective IRB-approved study. CEST-MRI was performed on a 7 T-whole-body scanner followed by a multi-Lorentzian fit analysis. APT and guanidyl CEST signal intensities were quantified in the tumor and in healthy fibroglandular tissue after correction of B0/B1-field inhomogeneities, fat signal contribution, T1- and T2-relaxation; signal intensity differences of APT and guanidyl resonances were compared using Mann–Whitney-U-tests. Pearson correlations between tumor CEST signal intensities and the proliferation index Ki-67 were performed. Results APT CEST signal in tumor tissue (6.70 ± 1.38%Hz) was increased compared to normal-appearing fibroglandular tissue of patients (3.56 ± 0.54%Hz, p = 0.001) and healthy volunteers (3.70 ± 0.68%Hz, p = 0.001). Further, a moderate positive correlation was found between the APT signal and the proliferation index Ki-67 (R2 = 0.367, r = 0.606, p = 0.11). Guanidyl CEST signal was also increased in tumor tissue (5.24 ± 1.85%Hz) compared to patients’ (2.42 ± 0.45%Hz, p = 0.006) and volunteers’ (2.36 ± 0.54%Hz, p Conclusion Relaxation-compensated and fat-corrected CEST-MRI allowed a non-invasive differentiation of breast cancer and normal-appearing breast tissue. Thus, this approach represents a contrast agent-free method that may help to increase diagnostic accuracy in MR-mammography.

BACKGROUND The "glymphatic system" (GS), a brain-wide network of cerebrospinal fluid microcirculation, supplies a pathway through and out of the central nervous system (CNS); malfunction of the system is implicated in a variety of neurological disorders. In this exploratory study, we analyzed the potential of a new imaging approach that we coined delayed T2-weighted gadolinium-enhanced imaging to visualize the GS in vivo. METHODS Heavily T2-weighted fluid-attenuated inversion recovery (hT2w-FLAIR) magnetic resonance imaging was obtained before, and 3 hours and 24 hours after intravenous gadolinium-based contrast agent (GBCA) application in 33 neurologically healthy patients and 7 patients with an impaired blood-brain barrier (BBB) due to cerebral metastases. Signal intensity (SI) was determined in various cerebral fluid spaces, and white matter hyperintensities were quantified by applying the Fazekas scoring system. FINDINGS Delayed hT2w-FLAIR showed GBCA entry into the CNS via the choroid plexus and the ciliary body, with GBCA drainage along perineural sheaths of cranial nerves and along perivascular spaces of penetrating cortical arteries. In all patients and all sites, a significant SI increase was found for the 3 hours and 24 hours time points compared with baseline. Although no significant difference in SI was found between neurologically healthy patients and patients with an impaired BBB, a significant positive correlation between Fazekas scoring system and SI increase in the perivascular spaces 3 hours post injection was shown. INTERPRETATION Delayed T2-weighted gadolinium-enhanced imaging can visualize the GBCA pathway into and through the GS. Presence of GBCAs within the GS might be regarded as part of the natural excretion process and should not be mixed up with gadolinium deposition. Rather, the correlation found between deep white matter hyperintensities, an imaging sign of vascular dementia, and GS functioning demonstrated feasibility to exploit the pathway of GBCAs through the GS for diagnostic purposes.

Magnetic resonance imaging (MRI) of the breast represents one of the most sensitive imaging modalities in breast cancer detection. Diffusion-weighted imaging (DWI) is a sequence variation introduced as a complementary MRI technique that relies on mapping the diffusion process of water molecules thereby providing additional information about the underlying tissue. Since water diffusion is more restricted in most malignant tumors than in benign ones owing to the higher cellularity of the rapidly proliferating neoplasia, DWI has the potential to contribute to the identification and characterization of suspicious breast lesions. Thus, DWI might increase the diagnostic accuracy of breast MRI and its clinical value. Future applications including optimized DWI sequences, technical developments in MR devices, and the application of radiomics/artificial intelligence algorithms may expand the potential of DWI in breast imaging beyond its current supplementary role.

// Sebastian Regnery 1, 2 , Sebastian Adeberg 3 , Constantin Dreher 2 , Johanna Oberhollenzer 2 , Jan-Eric Meissner 4 , Steffen Goerke 4 , Johannes Windschuh 4 , Katerina Deike-Hofmann 2 , Sebastian Bickelhaupt 2 , Moritz Zaiss 5 , Alexander Radbruch 2 , Martin Bendszus 6 , Wolfgang Wick 7 , Andreas Unterberg 8 , Stefan Rieken 1 , Jurgen Debus 1 , Peter Bachert 4 , Mark Ladd 4, 9, 10 , Heinz-Peter Schlemmer 2 and Daniel Paech 2 1 Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany 2 German Cancer Research Center (DKFZ), Division of Radiology, Heidelberg, Germany 3 German Cancer Research Center (DKFZ), HIRO (Heidelberg Institute for Radiation Oncology), Heidelberg, Germany 4 German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Heidelberg, Germany 5 Max-Planck-Institute, Tubingen, Germany 6 Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany 7 Department of Neurology, University Hospital Heidelberg, Heidelberg, Germany 8 Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany 9 Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany 10 Faculty of Medicine, University of Heidelberg, Heidelberg, Germany Correspondence to: Daniel Paech, email: d.paech@dkfz.de Keywords: magnetic resonance imaging; amide-proton-transfer-imaging; nuclear overhauser imaging; glioblastoma; predictive biomarker Received: March 29, 2018 Accepted: May 24, 2018 Published: June 19, 2018 ABSTRACT Purpose: To prospectively investigate chemical exchange saturation transfer (CEST) MRI in glioblastoma patients as predictor of early tumor progression after first-line treatment. Experimental Design: Twenty previously untreated glioblastoma patients underwent CEST MRI employing a 7T whole-body scanner. Nuclear Overhauser effect (NOE) as well as amide proton transfer (APT) CEST signals were isolated using Lorentzian difference (LD) analysis and relaxation compensated by the apparent exchange-dependent relaxation rate (AREX) evaluation. Additionally, NOE-weighted asymmetric magnetic transfer ratio (MTRasym) and downfield-NOE-suppressed APT (dns-APT) were calculated. Patient response to consecutive treatment was determined according to the RANO criteria. Mean signal intensities of each contrast in the whole tumor area were compared between early-progressive and stable disease. Results: Pre-treatment tumor signal intensity differed significantly regarding responsiveness to first-line therapy in NOE-LD ( p = 0.0001), NOE-weighted MTRasym ( p = 0.0186) and dns-APT ( p = 0.0328) contrasts. Hence, significant prediction of early progression was possible employing NOE-LD (AUC = 0.98, p = 0.0005), NOE-weighted MTRasym (AUC = 0.83, p = 0.0166) and dns-APT (AUC = 0.80, p = 0.0318). The NOE-LD provided the highest sensitivity (91%) and specificity (100%). Conclusions: CEST derived contrasts, particularly NOE-weighted imaging and dns-APT, yielded significant predictors of early progression after fist-line therapy in glioblastoma. Therefore, CEST MRI might be considered as non-invasive tool for customization of treatment in the future.

Purpose To evaluate a radiomics model of Breast Imaging Reporting and Data System (BI-RADS) 4 and 5 breast lesions extracted from breast-tissue-optimized kurtosis magnetic resonance (MR) imaging for lesion characterization by using a sensitivity threshold similar to that of biopsy. Materials and Methods This institutional study included 222 women at two independent study sites (site 1: training set of 95 patients; mean age ± standard deviation, 58.6 years ± 6.6; 61 malignant and 34 benign lesions; site 2: independent test set of 127 patients; mean age, 58.2 years ± 6.8; 61 malignant and 66 benign lesions). All women presented with a finding suspicious for cancer at x-ray mammography (BI-RADS 4 or 5) and an indication for biopsy. Before biopsy, diffusion-weighted MR imaging (b values, 0-1500 sec/mm

Background Early identification of prognostic superior characteristics in glioma patients such as Isocitrate dehydrogenase(IDH)-mutation and O6-methylguanine-DNA-methyltransferase (MGMT) promotor methylation status is of great clinical importance. The study purpose was to investigate the non-invasive predictability of IDH-mutation status, MGMT promotor methylation, and differentiation of lower versus higher grade glioma (LGG vs. HGG) in newly-diagnosed patients employing relaxation-compensated multi-pool Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) at 7.0 Tesla (7T). Methods Thirty-one newly-diagnosed glioma patients were included in this prospective study. CEST MRI was performed at a 7T whole-body scanner. Nuclear Overhauser Effect (NOE) and isolated amide proton transfer (APT, downfield NOE-suppressed APT=dns-APT) CEST signals (mean value and 90th signal percentile) were quantitatively investigated in the whole tumor area with regard to predictability of IDH-mutation, MGMT promotor methylation status, and differentiation of LGG vs. HGG. Statistics were performed using receiver operating characteristic (ROC) and area under the curve (AUC) analysis. Results were compared to advanced MRI methods (apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) ROC/AUC analysis) obtained at 3T. Results dns-APT CEST contrasts yielded highest AUCs in IDH-mutation status prediction (dns-APTmean=91.84, p0.05). Conclusions Relaxation-compensated multi-pool CEST MRI, particularly dns-APT imaging, enabled prediction of IDH-mutation status and differentiation of LGG vs. HGG and should therefore be considered as non-invasive MR biomarker in the diagnostic workup.

Purpose To evaluate the ability to detect intracerebral regions of increased glucose concentration at T1ρ-weighted dynamic glucose-enhanced (DGE) magnetic resonance (MR) imaging at 7.0 T. Materials and Methods This prospective study was approved by the institutional review board. Nine patients with newly diagnosed glioblastoma and four healthy volunteers were included in this study from October 2015 to July 2016. Adiabatically prepared chemical exchange-sensitive spin-lock imaging was performed with a 7.0-T whole-body unit with a temporal resolution of approximately 7 seconds, yielding the time-resolved DGE contrast. T1ρ-weighted DGE MR imaging was performed with injection of 100 mL of 20% d-glucose via the cubital vein. Glucose enhancement, given by the relative signal intensity change at T1ρ-weighted MR imaging (DGEρ), was quantitatively investigated in brain gray matter versus white matter of healthy volunteers and in tumor tissue versus normal-appearing white matter of patients with glioblastoma. The median signal intensities of the assessed brain regions were compared by using the Wilcoxon rank-sum test. Results In healthy volunteers, the median signal intensity in basal ganglia gray matter (DGEρ = 4.59%) was significantly increased compared with that in white matter tissue (DGEρ = 0.65%) (P = .028). In patients, the median signal intensity in the glucose-enhanced tumor region as displayed on T1ρ-weighted DGE images (DGEρ = 2.02%) was significantly higher than that in contralateral normal-appearing white matter (DGEρ = 0.08%) (P.0001). Conclusion T1ρ-weighted DGE MR imaging in healthy volunteers and patients with newly diagnosed, untreated glioblastoma enabled visualization of brain glucose physiology and pathophysiologically increased glucose uptake and may have the potential to provide information about glucose metabolism in tumor tissue.

Purpose To determine the effect of at least five serial injections of the macrocyclic gadolinium-based contrast agent (GBCA) gadoterate meglumine on the signal intensity (SI) of the dentate nucleus (DN) of the pediatric brain on nonenhanced T1-weighted magnetic resonance (MR) images. Materials and Methods In this retrospective, institutional review board-approved study, 41 pediatric patients (age range, 3-17 years) who were imaged in at least five consecutive 1.5-T MR examinations with the exclusive use of gadoterate meglumine (plus a final additional nonenhanced MR imaging examination) were evaluated. SI ratio differences between the first and last MR examination were calculated for DN-to-pons and DN-to-middle cerebellar peduncle (MCP) ratios in a region-of-interest-based analysis, and one-sample t tests were used to examine if the SI ratio differences differed from 0. Bayes factors were calculated to quantify the strength of evidence for each test. Results Patients underwent a mean of 8.6 ± 3.9 GBCA administrations (mean accumulated dose, 32.07 mmol ± 17.62, with an average of 16.7 weeks ± 7.9 between every administration). Both ratio differences did not differ significantly from 0 (DN-to-pons ratio: -0.0012 ± 0.0101, P = .436; DN-to-MCP ratio: 0.0007 ± 0.0088, P = .604), and one-sided Bayes factors provided substantial evidence against an SI ratio increase (0.10 for DN-to-pons ratio; 0.27 for DN-to-MCP ratio). Conclusion No increase of the SI in the DN was found after a mean of 8.6 serial injections of the macrocyclic GBCA gadoterate meglumine in pediatric patients, confirming previous studies that did not find this effect after serial injections of macrocyclic GBCAs in adults.

Aim To investigate an abbreviated, contrast-agent free diffusion-weighted (DW) breast magnetic resonance imaging (MRI) protocol that provides a single image for the radiologist to read in order to non-invasively examine Breast Imaging-Reporting and Data System (BI-RADS) 4 lesions detected using breast cancer screening X-ray mammography. Materials and methods This retrospective evaluation within a institutional review board-approved, prospective study included 115 women (mean 57 years, range 50–69 years) with BI-RADS 4 findings on X-ray mammography and indication for biopsy over a period of 15 months. Full diagnostic breast MRI (FDP) was performed prior to biopsy (1.5 T). Maximum intensity breast diffusion (MIBD) images were generated from DW images (b = 1,500 mm/s2, 3 mm section thickness) of the breast. MIBD and T2-weighted (T2W) images were read by two radiologists and compared to the diagnostic accuracy of an expert reading of the FDP with histopathology as the reference standard. The acquisition time of MIBD and T2W MRI was about 7 minutes. Results MIBD MRI provided a diagnostic accuracy of 87.93% (95% confidence interval [CI]: 80.58–93.24%) for R1 and 89.66% (95% CI: 82.63–94.54%) for R2. Expert reading of the FDP revealed a similar accuracy of 86.2% (95% CI: 78.67–91.43%). The positive predictive value (PPV) could be increased from 36.2% (95% CI: 28.02–45.28; X-ray mammography alone) to a mean PPV of 80.89% (R1 79.17%, R2 82.16%) using MIBD MRI. Mean reading time was 30 seconds (25%/75 percentile 24.5–41.25). Conclusions MIBD MRI might be of supplemental value if added to the work-up of BI-RADS 4 X-ray mammography screening findings. MIBD MRI might help reduce the false-positive rate prior to biopsy for reference lesions at only limited expense of measurement and reading time.

Purpose To correlate histopathologic findings from biopsy specimens with their corresponding location within enhancing areas, non-enhancing areas and necrotic areas on contrast enhanced T1-weighted MRI scans (cT1). Materials and Methods In 37 patients with newly diagnosed glioblastoma who underwent stereotactic biopsy, we obtained a correlation of 561 1mm3 biopsy specimens with their corresponding position on the intraoperative cT1 image at 1.5 Tesla. Biopsy points were categorized as enhancing (CE), non-enhancing (NE) or necrotic (NEC) on cT1 and tissue samples were categorized as “viable tumor cells”, “blood” or “necrotic tissue (with or without cellular component)”. Cell counting was done semi-automatically. Results NE had the highest content of tissue categorized as viable tumor cells (89% vs. 60% in CE and 30% NEC, respectively). Besides, the average cell density for NE (3764 ± 2893 cells/mm2) was comparable to CE (3506 ± 3116 cells/mm2), while NEC had a lower cell density with 2713 ± 3239 cells/mm2. If necrotic parts and bleeds were excluded, cell density in biopsies categorized as “viable tumor tissue” decreased from the center of the tumor (NEC, 5804 ± 3480 cells/mm2) to CE (4495 ± 3209 cells/mm2) and NE (4130 ± 2817 cells/mm2). Discussion The appearance of a glioblastoma on a cT1 image (circular enhancement, central necrosis, peritumoral edema) does not correspond to its diffuse histopathological composition. Cell density is elevated in both CE and NE parts. Hence, our study suggests that NE contains considerable amounts of infiltrative tumor with a high cellularity which might be considered in resection planning.

Mammography screening for early detection of breast lesions currently suffers from high amounts of false positive findings, which result in unnecessary invasive biopsies. Diffusion-weighted MR images (DWI) can help to reduce many of these false-positive findings prior to biopsy. Current approaches estimate tissue properties by means of quantitative parameters taken from generative, biophysical models fit to the q-space encoded signal under certain assumptions regarding noise and spatial homogeneity. This process is prone to fitting instability and partial information loss due to model simplicity. We reveal unexplored potentials of the signal by integrating all data processing components into a convolutional neural network (CNN) architecture that is designed to propagate clinical target information down to the raw input images. This approach enables simultaneous and target-specific optimization of image normalization, signal exploitation, global representation learning and classification. Using a multicentric data set of 222 patients, we demonstrate that our approach significantly improves clinical decision making with respect to the current state of the art.

The aim of this study was to evaluate the accuracy and applicability of solitarily reading fused image series of T2-weighted and high-b-value diffusion-weighted sequences for lesion characterization as compared to sequential or combined image analysis of these unenhanced sequences and to contrast- enhanced breast MRI. This IRB-approved study included 50 female participants with suspicious breast lesions detected in screening X-ray mammograms, all of which provided written informed consent. Prior to biopsy, all women underwent MRI including diffusion-weighted imaging (DWIBS, b = 1500s/mm2). Images were analyzed as follows: prospective image fusion of DWIBS and T2-weighted images (FU), side-by-side analysis of DWIBS and T2-weighted series (CO), combination of the first two methods (CO+FU), and full contrast-enhanced diagnostic protocol (FDP). Diagnostic indices, confidence, and image quality of the protocols were compared by two blinded readers. Reading the CO+FU (accuracy 0.92; NPV 96.1 %; PPV 87.6 %) and the CO series (0.90; 96.1 %; 83.7 %) provided a diagnostic performance similar to the FDP (0.95; 96.1 %; 91.3 %; p > 0.05). FU reading alone significantly reduced the diagnostic accuracy (0.82; 93.3 %; 73.4 %; p = 0.023). MR evaluation of suspicious BI-RADS 4 and 5 lesions detected on mammography by using a non-contrast-enhanced T2-weighted and DWIBS sequence protocol is most accurate if MR images were read using the CO+FU protocol. • Unenhanced breast MRI with additional DWIBS/T2w-image fusion allows reliable lesion characterization. • Abbreviated reading of fused DWIBS/T2w-images alone decreases diagnostic confidence and accuracy. • Reading fused DWIBS/T2w-images as the sole diagnostic method should be avoided.

Background: Radiotherapy is a mainstay for the treatment of lung cancer that can induce pneumonitis or pulmonary fibrosis. The matricellular protein connective tissue growth factor (CTGF) is a central mediator of tissue remodeling. Methods: A radiation-induced mouse model of pulmonary fibrosis was used to determine if transient administration of a human antibody to CTGF (FG-3019) started at different times before or after 20 Gy thoracic irradiation reduced acute and chronic radiation toxicity. Mice (25 mice/group; 10 mice/group in a confirmation study) were examined by computed tomography, histology, gene expression changes, and for survival. In vitro experiments were performed to directly study the interaction of CTGF blockade and radiation. All statistical tests were two-sided. Results: Administration of FG-3019 prevented (∼50%–80%) or reversed (∼50%) lung remodeling, improved lung function, improved mouse health, and rescued mice from lethal irradiation (P < .01). Importantly, when antibody treatment was initiated at 16 weeks after thoracic irradiation, FG-3019 reversed established lung remodeling and restored lung function. CTGF blockade abrogated M2 polarized macrophage influx, normalized radiation-induced gene expression changes, and reduced myofibroblast abundance and Osteopontin expression. Conclusion: These results indicate that blocking CTGF attenuates radiation-induced pulmonary remodeling and can reverse the process after initiation. CTGF has a central role in radiation-induced fibrogenesis, and FG-3019 may benefit patients with radiation-induced pulmonary fibrosis or patients with other forms or origin of chronic fibrotic diseases.

To evaluate the ability of a diagnostic abbreviated magnetic resonance (MR) imaging protocol consisting of maximum intensity projections (MIPs) from diffusion-weighted imaging with background suppression (DWIBS) and unenhanced morphologic sequences to help predict the likelihood of malignancy on suspicious screening x-ray mammograms, as compared with an abbreviated contrast material-enhanced MR imaging protocol and a full diagnostic breast MR imaging protocol.This prospective institutional review board-approved study included 50 women (mean age, 57.1 years; range, 50-69 years), who gave informed consent and who had suspicious screening mammograms and an indication for biopsy, from September 2014 to January 2015. Before biopsy, full diagnostic contrast-enhanced MR imaging was performed that included DWIBS (b = 1500 sec/mm(2)). Two abbreviated protocols (APs) based on MIPs were evaluated regarding the potential to exclude malignancy: DWIBS (AP1) and subtraction images from the first postcontrast and the unenhanced series (AP2). Diagnostic indexes of both methods were examined by using the McNemar test and were compared with those of the full diagnostic protocol and histopathologic findings.Twenty-four of 50 participants had a breast carcinoma. With AP1 (DWIBS), the sensitivity was 0.92 (95% confidence interval [CI]: 0.73, 0.98), the specificity was 0.94 (95% CI: 0.77, 0.99), the negative predictive value (NPV) was 0.92 (95% CI: 0.75, 0.99), and the positive predictive value (PPV) was 0.93 (95% CI: 0.75, 0.99). The mean reading time was 29.7 seconds (range, 4.9-110.0 seconds) and was less than 3 seconds (range, 1.2-7.6 seconds) in the absence of suspicious findings on the DWIBS MIPs. With the AP2 protocol, the sensitivity was 0.85 (95% CI: 0.78, 0.95), the specificity was 0.90 (95% CI: 0.72, 0.97), the NPV was 0.87 (95% CI: 0.69, 0.95), the PPV was 0.89 (95% CI: 0.69, 0.97), and the mean reading time was 29.6 seconds (range, 6.0-100.0 seconds).Unenhanced diagnostic MR imaging (DWIBS mammography), with an NPV of 0.92 and an acquisition time of less than 7 minutes, could help exclude malignancy in women with suspicious x-ray screening mammograms. The method has the potential to reduce unnecessary invasive procedures and emotional distress for breast cancer screening participants if it is used as a complement after the regular screening clarification procedure.

To use the “apparent diffusion coefficient” (Dapp) as a quantitative imaging parameter, well-suited test fluids are essential. In this study, the previously proposed aqueous solutions of polyvinylpyrrolidone (PVP) were examined and temperature calibrations were obtained. For example, at a temperature of 20°C, Dapp ranged from 1.594 (95% CI: 1.593, 1.595) μm2/ms to 0.3326 (95% CI: 0. 3304, 0.3348) μm2/ms for PVP-concentrations ranging from 10% (w/w) to 50% (w/w) using K30 polymer lengths. The temperature dependence of Dapp was found to be so strong that a negligence seems not advisable. The temperature dependence is descriptively modelled by an exponential function exp(c2 (T − 20°C)) and the determined c2 values are reported, which can be used for temperature calibration. For example, we find the value 0.02952 K-1 for 30% (w/w) PVP-concentration and K30 polymer length. In general, aqueous PVP solutions were found to be suitable to produce easily applicable and reliable Dapp-phantoms.

Objective To evaluate a fractional order calculus (FROC) model in diffusion weighted imaging to differentiate between malignant and benign breast lesions in breast cancer screening work-up using recently introduced parameters (βFROC, DFROC and μFROC). Materials and methods This retrospective analysis within a prospective IRB-approved study included 51 participants (mean 58.4 years) after written informed consent. All patients had suspicious screening mammograms and indication for biopsy. Prior to biopsy, full diagnostic contrast-enhanced MRI examination was acquired including diffusion-weighted-imaging (DWI, b = 0,100,750,1500 s/mm2). Conventional apparent diffusion coefficient Dapp and FROC parameters (βFROC, DFROC and μFROC) as suggested further indicators of diffusivity components were measured in benign and malignant lesions. Receiver operating characteristics (ROC) were calculated to evaluate the diagnostic performance of the parameters. Results 29/51 patients histopathologically revealed malignant lesions. The analysis revealed an AUC for Dapp of 0.89 (95% CI 0.80–0.98). For FROC derived parameters, AUC was 0.75 (0.60–0.89) for DFROC, 0.59 (0.43–0.75) for βFROC and 0.59 (0.42–0.77) for μFROC. Comparison of the AUC curves revealed a significantly higher AUC of Dapp compared to the FROC parameters DFROC (p = 0.009), βFROC (p = 0.003) and μFROC (p = 0.001). Conclusion In contrast to recent description in brain tumors, the apparent diffusion coefficient Dapp showed a significantly higher AUC than the recently proposed FROC parameters βFROC, DFROC and μFROC for differentiating between malignant and benign breast lesions. This might be related to the intrinsic high heterogeneity within breast tissue or to the lower maximal b-value used in our study.

Background: Radiotherapy (RT) is a mainstay for the treatment of lung cancer, but the effective dose is often limited by the development of radiation-induced pneumonitis and pulmonary fibrosis. Transforming growth factor β (TGFβ) and platelet-derived growth factor (PDGF) play crucial roles in the development of these diseases, but the effects of dual growth factor inhibition on pulmonary fibrosis development remain unclear. Methods: C57BL/6 mice were treated with 20 Gy to the thorax to induce pulmonary fibrosis. PDGF receptor inhibitors SU9518 and SU14816 (imatinib) and TGFβ receptor inhibitor galunisertib were applied individually or in combinations after RT. Lung density and septal fibrosis were measured by high-resolution CT and MRI. Lung histology and gene expression analyses were performed and Osteopontin levels were studied. Results: Treatment with SU9518, SU14816 or galunisertib individually attenuated radiation-induced pulmonary inflammation and fibrosis and decreased radiological and histological signs of lung damage. Combining PDGF and TGFβ inhibitors showed to be feasible and safe in a mouse model, and dual inhibition significantly attenuated radiation-induced lung damage and extended mouse survival compared to blockage of either pathway alone. Gene expression analysis of irradiated lung tissue showed upregulation of PDGF and TGFβ-dependent signaling components by thoracic irradiation, and upregulation patterns show crosstalk between downstream mediators of the PDGF and TGFβ pathways. Conclusion: Combined small-molecule inhibition of PDGF and TGFβ signaling is a safe and effective treatment for radiation-induced pulmonary inflammation and fibrosis in mice and may offer a novel approach for treatment of fibrotic lung diseases in humans. Translational statement: RT is an effective treatment modality for cancer with limitations due to acute and chronic toxicities, where TGFβ and PDGF play a key role. Here, we show that a combined inhibition of TGFβ and PDGF signaling is more effective in attenuating radiation-induced lung damage compared to blocking either pathway alone. We used the TGFβ-receptor I inhibitor galunisertib, an effective anticancer compound in preclinical models and the PDGFR inhibitors imatinib and SU9518, a sunitinib analog. Our signaling data suggest that the reduction of TGFβ and PDGF signaling and the attenuation of SPP1 (Osteopontin) expression may be responsible for the observed benefits. With the clinical availability of similar compounds currently in phase-I/II trials as cancer therapeutics or already approved for certain cancers or idiopathic lung fibrosis (IPF), our study suggests that the combined application of small molecule inhibitors of TGFβ and PDGF signaling may offer a promising approach to treat radiation-associated toxicity in RT of lung cancer.