Search

Purpose: Radiotherapy is used for the treatment of lung cancer, but at the same time induces acute pneumonitis and subsequent pulmonary fibrosis, where TGF-β signaling is considered to play an important role.Experimental Design: We irradiated thoraces of C57BL/6 mice (single dose, 20 Gy) and administered them a novel small-molecule TGF-β receptor I serine/threonine kinase inhibitor (LY2109761) orally for 4 weeks before, during, or after radiation. Noninvasive lung imaging including volume computed tomography (VCT) and MRI was conducted 6, 16, and 20 weeks after irradiation and was correlated to histologic findings. Expression profiling analysis and protein analysis was conducted in human primary fibroblasts.Results: Radiation alone induced acute pulmonary inflammation and lung fibrosis after 16 weeks associated with reduced life span. VCT, MRI, and histology showed that LY2109761 markedly reduced inflammation and pulmonary fibrosis resulting in prolonged survival. Mechanistically, we found that LY2109761 reduced p-SMAD2 and p-SMAD1 expression, and transcriptomics revealed that LY2109761 suppressed expression of genes involved in canonical and noncanonical TGF-β signaling and downstream signaling of bone morphogenetic proteins (BMP). LY2109761 also suppressed radiation-induced inflammatory [e.g., interleukin (IL)-6, IL-7R, IL-8] and proangiogenic genes (e.g., ID1) indicating that LY2109761 achieves its antifibrotic effect by suppressing radiation-induced proinflammatory, proangiogenic, and profibrotic signals.Conclusion: Small-molecule inhibitors of the TGF-β receptor I kinase may offer a promising approach to treat or attenuate radiation-induced lung toxicity or other diseases associated with fibrosis. Clin Cancer Res; 18(13); 3616–27. ©2012 AACR.

PDF file, 95KB.

PDF file, 37KB, Regulated GO-terms and Genes.

PDF file, 42KB.

Kira Knauer,1,2 Oliver Chaudry,2,3 Michael Uder,1 Matthias Kohl,4 Wolfgang Kemmler,1,2 Sebastian Bickelhaupt,1 Klaus Engelke2,3 1Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg and University Hospital Erlangen, Erlangen, 91054, Germany; 2Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, 91052, Germany; 3Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Erlangen, 91054, Germany; 4Faculty Medical and Life Sciences, University of Furtwangen, Villingen-Schwenningen, 78054, GermanyCorrespondence: Kira Knauer, Institute of Radiology, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Maximiliansplatz 3, Erlangen, 91054, Germany, Tel +49 9131/85-36065, Email Kira.knauer@fau.dePurpose: To evaluate the effect of a high-intensity resistance training (HIT-RT) on visceral adipose tissue (VAT) and abdominal aortic calcifications (AAC).Patients and Methods: We conducted a post hoc analysis of the Franconian Osteopenia and Sarcopenia Trial (FrOST). 43 community-dwelling men with osteosarcopenia aged 72 years and older were randomly allocated to a supervised high-intensity resistance training (HIT-RT) twice weekly for 18 months (EG; n=21) and a non-training control group (CG; n=22). Non-contrast enhanced 2-point Dixon MRI scans covering mid L2 to mid L3 were acquired to measure VAT volume inside the abdominal cavity. Volume of AAC and hard plaques in renal arteries, truncus celiacus and superior mesenteric artery was measured by computed tomography (CT) scans covering mid T12 to mid L3. Intention-to-treat analysis with imputation for missing data was used to determine longitudinal changes in VAT and AAC volume. Correlations were used to determine associations between VAT and AAC.Results: Significant reduction of VAT volume in the EG (− 7.7%; p< 0.001) combined with no change in the CG (− 1.3%; p=0.46) resulted in a significant 6.4% between group effect (p=0.022). We observed a significant increase of AAC volume in EG (+10.3%; p< 0.001) and CG (12.0%; p< 0.001). AAC differences between groups were not significant (p=0.57). In vascular outlets increases in volume of the hard plaques were observed in both groups, however, not all of them were significant. There was no significant correlation between changes in VAT and AAC volumes.Conclusion: The study confirmed a positive impact of HIT-RT on the metabolic and cardiovascular risk profile with respect to reduction of VAT volume. No positive exercise effect on AAC was observed. However, there was a further progression of AAC volume independent of group affiliation. Whether different exercise regimen may show a positive effect on AAC remains subject to further studies.Keywords: HIT-RT, VAT, AAC, osteopenia, sarcopenia

The objective of the current study was to assess sodium (

Background Long COVID occurs in lower frequency in children and adolescents than in adults. Morphologic and free-breathing phase-resolved functional low-field MRI may identify persistent pulmonary manifestations after SARS-CoV-2 infection. Purpose To characterize both morphologic and functional changes of lung parenchyma on low-field MRI in children and adolescents with post COVID-19 compared with healthy controls. Materials and Methods Between August and December 2021, a cross-sectional, prospective clinical trial using low-field MRI was performed in children and adolescents from a single academic medical center. The primary outcome was the frequency of morphologic changes on MRI. Secondary outcomes included MRI-derived functional proton ventilation and perfusion parameters. Clinical symptoms, the duration from positive RT-PCR test and serological parameters were compared with imaging results. Nonparametric tests for pairwise and corrected tests for groupwise comparisons were applied to assess differences in healthy controls, recovered participants and with long COVID. Results A total of 54 participants post COVID-19 infection (mean age, 11 years ±3 [SD], 56 males) and 9 healthy controls (mean age, 10 years ±3 [SD], 70 males) were included: 29 (54%) in the COVID-19 group had recovered from infection and 25 (46%) were classified as having long COVID on the day of enrollment. Morphologic abnormality was identified in one recovered participant. Both ventilated and perfused lung parenchyma (V/Q match) was reduced from 81±6.1% in healthy controls to 62±19% (

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.

The onset of rheumatic diseases such as rheumatoid arthritis is typically subclinical, which results in challenging early detection of the disease. However, characteristic changes in the anatomy can be detected using imaging techniques such as MRI or CT. Modern imaging techniques such as chemical exchange saturation transfer (CEST) MRI drive the hope to improve early detection even further through the imaging of metabolites in the body. To image small structures in the joints of patients, typically one of the first regions where changes due to the disease occur, a high resolution for the CEST MR imaging is necessary. Currently, however, CEST MR suffers from an inherently low resolution due to the underlying physical constraints of the acquisition. In this work we compared established up-sampling techniques to neural network-based super-resolution approaches. We could show, that neural networks are able to learn the mapping from low-resolution to high-resolution unsaturated CEST images considerably better than present methods. On the test set a PSNR of 32.29 dB (+10%), a NRMSE of 0.14 (+28%), and a SSIM of 0.85 (+15%) could be achieved using a ResNet neural network, improving the baseline considerably. This work paves the way for the prospective investigation of neural networks for super-resolution CEST MRI and, followingly, might lead to a earlier detection of the onset of rheumatic diseases.

Objectives To evaluate whether neural networks can distinguish between seropositive RA, seronegative RA, and PsA based on inflammatory patterns from hand MRIs and to test how psoriasis patients with subclinical inflammation fit into such patterns. Methods ResNet neural networks were utilized to compare seropositive RA vs PsA, seronegative RA vs PsA, and seropositive vs seronegative RA with respect to hand MRI data. Results from T1 coronal, T2 coronal, T1 coronal and axial fat-suppressed contrast-enhanced (CE), and T2 fat-suppressed axial sequences were used. The performance of such trained networks was analysed by the area under the receiver operating characteristics curve (AUROC) with and without presentation of demographic and clinical parameters. Additionally, the trained networks were applied to psoriasis patients without clinical arthritis. Results MRI scans from 649 patients (135 seronegative RA, 190 seropositive RA, 177 PsA, 147 psoriasis) were fed into ResNet neural networks. The AUROC was 75% for seropositive RA vs PsA, 74% for seronegative RA vs PsA, and 67% for seropositive vs seronegative RA. All MRI sequences were relevant for classification, however, when deleting contrast agent–based sequences the loss of performance was only marginal. The addition of demographic and clinical data to the networks did not provide significant improvements for classification. Psoriasis patients were mostly assigned to PsA by the neural networks, suggesting that a PsA-like MRI pattern may be present early in the course of psoriatic disease. Conclusion Neural networks can be successfully trained to distinguish MRI inflammation related to seropositive RA, seronegative RA, and PsA.

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.

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.

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.

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

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.

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.

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.

// 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.

End-to-end deep learning improves breast cancer classification on diffusion-weighted MR images (DWI) using a convolutional neural network (CNN) architecture. A limitation of CNN as opposed to previous model-based approaches is the dependence on specific DWI input channels used during training. However, in the context of large-scale application, methods agnostic towards heterogeneous inputs are desirable, due to the high deviation of scanning protocols between clinical sites. We propose model-based domain adaptation to overcome input dependencies and avoid re-training of networks at clinical sites by restoring training inputs from altered input channels given during deployment. We demonstrate the method’s significant increase in classification performance and superiority over implicit domain adaptation provided by training-schemes operating on model-parameters instead of raw DWI images.

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 signal under certain assumptions regarding noise and spatial homogeneity. This process is prone to fitting instability and partial information loss due to model simplicity.

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.

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.

Small bowel motility analyses using magnetic resonance imaging (MRI) could reduce current invasive techniques in animal studies and comply with the ‘three Rs’ rule for human animal experimentation. Thus we investigated the feasibility of in vivo small bowel motility analyses in mice using dynamic MRI acquisitions. All experimental procedures were approved by the institutional animal care committee. Six C57BL/6 mice underwent MRI without additional preparation after isoflurane anaesthetization in the prone position on a 4.7 T small animal imager equipped with a linear polarized hydrogen birdcage whole-body mouse coil. Motility was assessed using a true fast imaging in a steady precession sequence in the coronal orientation (acquisition time per slice 512 ms, in-plane resolution 234 × 234 µm, matrix size 128 × 128, slice thickness 1 mm) over 30 s corresponding to 60 acquisitions. Motility was manually assessed measuring the small bowel diameter change over time. The resulting motility curves were analysed for the following parameters: contraction frequency per minute (cpm), maximal contraction amplitude (maximum to minimum [mm]), luminal diameter (mm) and luminal occlusion rate. Small bowel motility quantification was found to be possible in all animals with a mean small bowel contraction frequency of 10.67 cpm (SD ± 3.84), a mean amplitude of the contractions of 1.33 mm (SD ± 0.43) and a mean luminal diameter of 1.37 mm (SD ± 0.42). The mean luminal occlusion rate was 1.044 (SD ± 0.45%/100). The mean duration needed for a single motility assessment was 185 s (SD ± 54.02). Thus our study demonstrated the feasibility of an easy and time-sparing functional assessment for in vivo small bowel motility analyses in mice. This could improve the development of small animal models of intestinal diseases and provide a method similar to clinical MR examinations that is in concordance with the ‘three Rs’ for humane animal experimentation.

Purpose: Radiotherapy is used for the treatment of lung cancer, but at the same time induces acute pneumonitis and subsequent pulmonary fibrosis, where TGF-β signaling is considered to play an important role. Experimental Design: We irradiated thoraces of C57BL/6 mice (single dose, 20 Gy) and administered them a novel small-molecule TGF-β receptor I serine/threonine kinase inhibitor (LY2109761) orally for 4 weeks before, during, or after radiation. Noninvasive lung imaging including volume computed tomography (VCT) and MRI was conducted 6, 16, and 20 weeks after irradiation and was correlated to histologic findings. Expression profiling analysis and protein analysis was conducted in human primary fibroblasts. Results: Radiation alone induced acute pulmonary inflammation and lung fibrosis after 16 weeks associated with reduced life span. VCT, MRI, and histology showed that LY2109761 markedly reduced inflammation and pulmonary fibrosis resulting in prolonged survival. Mechanistically, we found that LY2109761 reduced p-SMAD2 and p-SMAD1 expression, and transcriptomics revealed that LY2109761 suppressed expression of genes involved in canonical and noncanonical TGF-β signaling and downstream signaling of bone morphogenetic proteins (BMP). LY2109761 also suppressed radiation-induced inflammatory [e.g., interleukin (IL)-6, IL-7R, IL-8] and proangiogenic genes (e.g., ID1) indicating that LY2109761 achieves its antifibrotic effect by suppressing radiation-induced proinflammatory, proangiogenic, and profibrotic signals. Conclusion: Small-molecule inhibitors of the TGF-β receptor I kinase may offer a promising approach to treat or attenuate radiation-induced lung toxicity or other diseases associated with fibrosis. Clin Cancer Res; 18(13); 3616–27. ©2012 AACR.

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 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.