A community-endorsed open-source lexicon for contrast agent-based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI).

This manuscript describes the ISMRM OSIPI (Open Science Initiative for Perfusion Imaging) lexicon for dynamic contrast-enhanced and dynamic susceptibility-contrast MRI. The lexicon was developed by Taskforce 4.2 of OSIPI to provide standardized definitions of commonly used quantities, models, and analysis processes with the aim of reducing reporting variability. The taskforce was established in February 2020 and consists of medical physicists, engineers, clinicians, data and computer scientists, and DICOM (Digital Imaging and Communications in Medicine) standard experts. Members of the taskforce collaborated via a slack channel and quarterly virtual meetings. Members participated by defining lexicon items and reporting formats that were reviewed by at least two other members of the taskforce. Version 1.0.0 of the lexicon was subject to open review from the wider perfusion imaging community between January and March 2022, and endorsed by the Perfusion Study Group of the ISMRM in the summer of 2022. The initial scope of the lexicon was set by the taskforce and defined such that it contained a basic set of quantities, processes, and models to enable users to report an end-to-end analysis pipeline including kinetic model fitting. We also provide guidance on how to easily incorporate lexicon items and definitions into free-text descriptions (e.g., in manuscripts and other documentation) and introduce an XML-based pipeline encoding format to encode analyses using lexicon definitions in standardized and extensible machine-readable code. The lexicon is designed to be open-source and extendable, enabling ongoing expansion of its content. We hope that widespread adoption of lexicon terminology and reporting formats described herein will increase reproducibility within the field.

MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging - design, implementation and application on the example of DCE-MRI.

BACKGROUND: Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI)/computed tomography (CT), apparent diffusion coefficient calculations and intravoxel incoherent motion modeling in diffusion-weighted MRI and Z-spectra analysis in chemical exchange saturation transfer MRI. Most available software tools are limited to a special purpose and do not allow for own developments and extensions. Furthermore, they are mostly designed as stand-alone solutions using external frameworks and thus cannot be easily incorporated natively in the analysis workflow. RESULTS: We present a framework for medical image fitting tasks that is included in the Medical Imaging Interaction Toolkit MITK, following a rigorous open-source, well-integrated and operating system independent policy. Software engineering-wise, the local models, the fitting infrastructure and the results representation are abstracted and thus can be easily adapted to any model fitting task on image data, independent of image modality or model. Several ready-to-use libraries for model fitting and use-cases, including fit evaluation and visualization, were implemented. Their embedding into MITK allows for easy data loading, pre- and post-processing and thus a natural inclusion of model fitting into an overarching workflow. As an example, we present a comprehensive set of plug-ins for the analysis of DCE MRI data, which we validated on existing and novel digital phantoms, yielding competitive deviations between fit and ground truth. CONCLUSIONS: Providing a very flexible environment, our software mainly addresses developers of medical imaging software that includes model fitting algorithms and tools. Additionally, the framework is of high interest to users in the domain of perfusion MRI, as it offers feature-rich, freely available, validated tools to perform pharmacokinetic analysis on DCE MRI data, with both interactive and automatized batch processing workflows.

IDH-wildtype glioblastomas and grade III/IV IDH-mutant gliomas show elevated tracer uptake in fibroblast activation protein-specific PET/CT.

PURPOSE: Targeting fibroblast activation protein (FAP) is a new diagnostic approach allowing the visualization of tumor stroma. Here, we applied FAP-specific PET imaging to gliomas. We analyzed the target affinity and specificity of two FAP ligands (FAPI-02 and FAPI-04) in vitro, and the pharmacokinetics and biodistribution in mice in vivo. Clinically, we used 68Ga-labeled FAPI-02/04 for PET imaging in 18 glioma patients (five IDH-mutant gliomas, 13 IDH-wildtype glioblastomas). METHODS: For binding studies with 177Lu-radiolabeled FAPI-02/04, we used the glioblastoma cell line U87MG, FAP-transfected fibrosarcoma cells, and CD26-transfected human embryonic kidney cells. For pharmacokinetic and biodistribution studies, U87MG-xenografted mice were injected with 68Ga-labeled compounds followed by small-animal PET imaging and 177Lu-labeled FAPI-02/04, respectively. Clinical PET/CT scans were performed 30 min post intravenous administration of 68Ga-FAPI-02/04. PET and MRI scans were co-registrated. Immunohistochemistry was done on 14 gliomas using a FAP-specific antibody. RESULTS: FAPI-02 and FAPI-04 showed high binding specificity to FAP. FAPI-04 demonstrated higher tumor accumulation and delayed elimination compared with FAPI-02 in preclinical studies. IDH-wildtype glioblastomas and grade III/IV, but not grade II, IDH-mutant gliomas showed elevated tracer uptake. In glioblastomas, we observed spots with increased uptake in projection on contrast-enhancing areas. Immunohistochemistry showed FAP-positive cells with mainly elongated cell bodies and perivascular FAP-positive cells in glioblastomas and an anaplastic IDH-mutant astrocytoma. CONCLUSIONS: Using FAP-specific PET imaging, increased tracer uptake in IDH-wildtype glioblastomas and high-grade IDH-mutant astrocytomas, but not in diffuse astrocytomas, may allow non-invasive distinction between low-grade IDH-mutant and high-grade gliomas. Therefore, FAP-specific imaging in gliomas may be useful for follow-up studies although further clinical evaluation is required.

Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T.

BACKGROUND: Patients with newly diagnosed inoperable glioma receive chemoradiotherapy (CRT). Standard Response Assessment in Neuro-Oncology (RANO) takes a minimum of 4 weeks after the end of treatment. PURPOSE/HYPOTHESIS: To investigate whether chemical exchange saturation transfer (CEST) MRI enables earlier assessment of response to CRT in glioma patients. STUDY TYPE: Longitudinal prospective study. POPULATION: Twelve brain tumor patients who underwent definitive CRT were included in this study. Three longitudinal CEST MRI measurements were performed for each patient at 7T: first before, second immediately after completion of CRT, and a third measurement as a 6-week follow-up. 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 all patients. ASSESSMENT: The mean relaxation-compensated relayed nuclear-Overhauser-effect CEST signal (rNOE) and the mean downfield-rNOE-suppressed amide proton transfer (dns-APT) CEST signal were investigated. Additionally, choline-to-N-acetyl-aspartate ratios (Cho/NAA) were evaluated using single-voxel 1 H-MRS in six of these patients. Performance of obtained contrasts was analyzed in assessing treatment response as classified according to the updated RANO criteria. STATISTICAL TEST: Unpaired Student's t-test. RESULTS: The rNOE signal significantly separated stable and progressive disease directly after the end of therapy (post-treatment normalized to pre-treatment mean ± SD: rNOEresponder = 1.090 ± 0.110, rNOEnon-responder = 0.808 ± 0.155, P = 0.015). In contrast, no significant difference was observed between either group when assessing the normalized dns-APT (dns-APTresponder = 0.953 ± 0.384, dns-APTnon-responder = 0.972 ± 0.477, P = 0.95). In the smaller MRS subcohort, normalized Cho/NAA decreased in therapy responders (Cho/NAAresponder = 0.632 ± 0.007, Cho/NAAnon-responder = 0.946 ± 0.124, P = 0.070). DATA CONCLUSION: rNOE mediated CEST imaging at 7T allowed for discrimination of responders and non-responders immediately after the end of CRT, additionally supported by 1 H-MRS data. This is at least 4 weeks earlier than the standard clinical evaluation according to RANO. Therefore, CEST MRI may enable early response assessment in glioma patients. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019;50:1268-1277.

Simultaneous whole-body 18F-PSMA-1007-PET/MRI with integrated high-resolution multiparametric imaging of the prostatic fossa for comprehensive oncological staging of patients with prostate cancer: a pilot study.

INTRODUCTION: The aim of the present study was to explore the clinical feasibility and reproducibility of a comprehensive whole-body 18F-PSMA-1007-PET/MRI protocol for imaging prostate cancer (PC) patients. METHODS: Eight patients with high-risk biopsy-proven PC underwent a whole-body PET/MRI (3 h p.i.) including a multi-parametric prostate MRI after 18F-PSMA-1007-PET/CT (1 h p.i.) which served as reference. Seven patients presented with non-treated PC, whereas one patient presented with biochemical recurrence. SUVmean-quantification was performed using a 3D-isocontour volume-of-interest. Imaging data was consulted for TNM-staging and compared with histopathology. PC was confirmed in 4/7 patients additionally by histopathology after surgery. PET-artifacts, co-registration of pelvic PET/MRI and MRI-data were assessed (PI-RADS 2.0). RESULTS: The examinations were well accepted by patients and comprised 1 h. SUVmean-values between PET/CT (1 h p.i.) and PET/MRI (3 h p.i.) were significantly correlated (p < 0.0001, respectively) and similar to literature of 18F-PSMA-1007-PET/CT 1 h vs 3 h p.i. The dominant intraprostatic lesion could be detected in all seven patients in both PET and MRI. T2c, T3a, T3b and T4 features were detected complimentarily by PET and MRI in five patients. PET/MRI demonstrated moderate photopenic PET-artifacts surrounding liver and kidneys representing high-contrast areas, no PET-artifacts were observed for PET/CT. Simultaneous PET-readout during prostate MRI achieved optimal co-registration results. CONCLUSIONS: The presented 18F-PSMA-1007-PET/MRI protocol combines efficient whole-body assessment with high-resolution co-registered PET/MRI of the prostatic fossa for comprehensive oncological staging of patients with PC.

In vivo assessment of cold stimulation effects on the fat fraction of brown adipose tissue using DIXON MRI.

PURPOSE: To evaluate the volume and changes of human brown adipose tissue (BAT) in vivo following exposure to cold using magnetic resonance imaging (MRI). MATERIALS AND METHODS: The clavicular region of 10 healthy volunteers was examined with a 3T MRI system. One volunteer participated twice. A cooling vest that was circulated with temperature-controlled water was used to expose each volunteer to a cold environment. Three different water temperature phases were employed: baseline (23°C, 20 min), cooling (12°C, 90 min), and a final warming phase (37°C, 30 min). Temperatures of the water in the circuit, of the body, and at the back skin of the volunteers were monitored with fiberoptic temperature probes. Applying the 2-point DIXON pulse sequence every 5 minutes, fat fraction (FF) maps were determined and evaluated over time to distinguish between brown and white adipose tissue. RESULTS: Temperature measurements showed a decrease of 3.8 ± 1.0°C of the back skin temperature, while the body temperature stayed constant at 37.2 ± 0.9°C. Focusing on the two interscapular BAT depots, a mean FF decrease of -2.9 ± 2.0%/h (P < 0.001) was detected during cold stimulation in a mean absolute volume of 1.31 ± 1.43 ml. Also, a correlation of FF decrease to back skin temperature decrease was observed in all volunteers (correlation coefficients: |r| = [0.51; 0.99]). CONCLUSION: We found that FF decreases in BAT begin immediately with mild cooling of the body and continue during long-time cooling. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:369-380.

Prognostic value of combined visualization of MR diffusion and perfusion maps in glioblastoma.

We analyzed whether the combined visualization of decreased apparent diffusion coefficient (ADC) values and increased cerebral blood volume (CBV) in perfusion imaging can identify prognosis-related growth patterns in patients with newly diagnosed glioblastoma. Sixty-five consecutive patients were examined with diffusion and dynamic susceptibility-weighted contrast-enhanced perfusion weighted MRI. ADC and CBV maps were co-registered on the T1-w image and a region of interest (ROI) was manually delineated encompassing the enhancing lesion. Within this ROI pixels with ADC values the 70th percentile (CBVmax) and the intersection of pixels with ADCmin and CBVmax were automatically calculated and visualized. Initially, all tumors with a mean intersection greater than the upper quartile of the normally distributed mean intersection of all patients were subsumed to the first growth pattern termed big intersection (BI). Subsequently, the remaining tumors' growth patterns were categorized depending on the qualitative representation of ADCmin, CBVmax and their intersection. Log-rank test exposed a significantly longer overall survival of BI (n = 16) compared to non-BI group (n = 49) (p = 0.0057). Thirty-one, four and 14 patients of the non-BI group were classified as predominant ADC-, CBV- and mixed growth group, respectively. In a multivariate Cox regression model, the BI-, CBV- and mixed groups had significantly lower adjusted hazard ratios (p-value, α(Bonferroni) < 0.006) when compared to the reference group ADC: 0.29 (0.0027), 0.11 (0.038) and 0.33 (0.0059). Our study provides evidence that the combination of diffusion and perfusion imaging allows visualization of different glioblastoma growth patterns that are associated with prognosis. A possible biological hypothesis for this finding could be the interpretation of the ADCmin fraction as the invasion-front of tumor cells while the CBVmax fraction might represent the vascular rich tumor border that is "trailing behind" the invasion-front in the ADC group.

Time-dependent parameter of perfusion imaging as independent predictor of clinical outcome in symptomatic carotid artery stenosis.

BACKGROUND: Carotid artery stenosis is a frequent cause of ischemic stroke. While any degree of stenosis can cause embolic stroke, a higher degree of stenosis can also cause hemodynamic infarction. The hemodynamic effect of a stenosis can be assessed via perfusion weighted MRI (PWI). Our aim was to investigate the ability of PWI-derived parameters such as TTP (time-to-peak) and T(max) (time to the peak of the residue curve) to predict outcome in patients with unilateral acute symptomatic internal carotid artery (sICA) stenosis. METHODS: Patients with unilateral acute sICA stenosis (≥50% according to NASCET), without intracranial stenosis or occlusion, who underwent PWI, were included. Clinical characteristics, volume of restricted diffusion, volume of prolonged TTP and T(max) were retrospectively analyzed and correlated with outcome represented by the modified Rankin Scale (mRS) score at discharge. TTP and T(max) volumes were dichotomized using a ROC curve analysis. Multivariate analysis was performed to determine which PWI-parameter was an independent predictor of outcome. RESULTS: Thirty-two patients were included. Degree of stenosis, volume of visually assessed TTP and volume of TTP ≥2 s did not distinguish patients with favorable (mRS 0-2) and unfavorable (mRS 3-6) outcome. In contrast, patients with unfavorable outcome had higher volumes of TTP ≥4 s (9.12 vs. 0.87 ml; p = 0.043), TTP ≥6 s (6.70 vs. 0.20 ml; p = 0.017), T(max) ≥4 s (25.27 vs. 0.00 ml; p = 0.043), T(max) ≥6 s (9.21 vs. 0.00 ml; p = 0.017), T(max) ≥8 s (6.86 vs. 0.00 ml; p = 0.011) and T(max) ≥10s (5.94 vs. 0.00 ml; p = 0.025) in univariate analysis. Multivariate logistic regression showed that NIHSS score on admission (Odds Ratio (OR) 0.466, confidence interval (CI) [0.224;0.971], p = 0.041), T(max) ≥8 s (OR 0.025, CI [0.001;0.898] p = 0.043) and TTP ≥6 s (OR 0.025, CI [0.001;0.898] p = 0.043) were independent predictors of clinical outcome. CONCLUSION: As they stood out in multivariate regression and are objective and reproducible parameters, PWI-derived volumes of T(max) ≥8 s and TTP ≥6 s might be superior to degree of stenosis and visually assessed TTP maps in predicting short term patient outcome. Future studies should assess if perfusion weighted imaging might guide the selection of patients for recanalization procedures.

Infiltrative patterns of glioblastoma: Identification of tumor progress using apparent diffusion coefficient histograms.

PURPOSE: To investigate whether apparent diffusion coefficient (ADC) histogram analysis can differentiate between patients presenting T2-progress and patients presenting stable T2-signal in glioblastoma. MATERIALS AND METHODS: Fourteen patients presenting an isolated T2-progress and a matched control group exhibiting stable disease were included. Relative ADC value distribution within tumoral and peritumoral FLAIR hyperintensities were evaluated using ADC-histogram analysis. Severity and frequency of ADC shift between baseline, T2-progress, and subsequent T1-progress were analyzed using the Wilcoxon test. RESULTS: The shift of ADC histograms either to higher or to lower values in case of T2-progress was significantly more severe than in the control group (P value 0.05). Furthermore, a significant shift toward lower ADC values (P value 0.02) was detected when comparing ADC histograms of patients with T2-progress and subsequent T1-progress. CONCLUSION: The basis for the observed ADC shift in isolated T2-progress may be time dependent: Initially, formation of peritumoral edema may cause an increase of ADC values that is followed by tumor cells infiltrating the surrounding tissue, causing a subsequent decrease of ADC values. The shift toward lower ADC values in case of subsequent T1-progress confirms this hypothesis and provides further evidence for T2-progress being an intermediate step between stable disease (SD) and T1-progress.

Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics.

OBJECTIVES: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation. MATERIALS AND METHODS: The consensus was achieved by a multi-stage process. Stage 1 comprised a definition screening, a retrospective analysis with semantic mapping of terms found in 22 workflow definitions, and the compilation of an initial baseline definition. Stages 2 and 3 consisted of a Delphi process with over 45 experts hailing from sites participating in the German Research Foundation (DFG) Priority Program 2177. Stage 2 aimed to achieve a broad consensus for a definition proposal, while stage 3 identified the importance of translational challenges. RESULTS: Workflow definitions from 22 publications (published 2012-2020) were analyzed. Sixty-nine definition terms were extracted, mapped, and semantic ambiguities (e.g., homonymous and synonymous terms) were identified and resolved. The consensus definition was developed via a Delphi process. The final definition comprising seven phases and 37 aspects reached a high overall consensus (> 89% of experts "agree" or "strongly agree"). Two aspects reached no strong consensus. In addition, the Delphi process identified and characterized from the participating experts' perspective the ten most important challenges in radiomics workflows. CONCLUSION: To overcome semantic inconsistencies between existing definitions and offer a well-defined, broad, referenceable terminology, a consensus workflow definition for radiomics-based setups and a terms mapping to existing literature was compiled. Moreover, the most relevant challenges towards clinical application were characterized. CRITICAL RELEVANCE STATEMENT: Lack of standardization represents one major obstacle to successful clinical translation of radiomics. Here, we report a consensus workflow definition on different aspects of radiomics studies and highlight important challenges to advance the clinical adoption of radiomics. KEY POINTS: Published radiomics workflow terminologies are inconsistent, hindering standardization and translation. A consensus radiomics workflow definition proposal with high agreement was developed. Publicly available result resources for further exploitation by the scientific community.

Addressing image misalignments in multi-parametric prostate MRI for enhanced computer-aided diagnosis of prostate cancer.

Prostate cancer (PCa) diagnosis on multi-parametric magnetic resonance images (MRI) requires radiologists with a high level of expertise. Misalignments between the MRI sequences can be caused by patient movement, elastic soft-tissue deformations, and imaging artifacts. They further increase the complexity of the task prompting radiologists to interpret the images. Recently, computer-aided diagnosis (CAD) tools have demonstrated potential for PCa diagnosis typically relying on complex co-registration of the input modalities. However, there is no consensus among research groups on whether CAD systems profit from using registration. Furthermore, alternative strategies to handle multi-modal misalignments have not been explored so far. Our study introduces and compares different strategies to cope with image misalignments and evaluates them regarding to their direct effect on diagnostic accuracy of PCa. In addition to established registration algorithms, we propose 'misalignment augmentation' as a concept to increase CAD robustness. As the results demonstrate, misalignment augmentations can not only compensate for a complete lack of registration, but if used in conjunction with registration, also improve the overall performance on an independent test set.

Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke.

Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate the underlying diagnostic processes. Here, we developed an artificial neural network (ANN) which allows automated detection of abnormal vessel findings without any a-priori restrictions and in <2 minutes. Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%). Benchmarking against two CE- and FDA-approved software solutions showed significantly higher performance for our ANN with improvements of 25-45% for sensitivity and 4-11% for NPV (p ≤ 0.003 each). We provide an imaging platform ( https://stroke.neuroAI-HD.org ) for online processing of medical imaging data with the developed ANN, including provisions for data crowdsourcing, which will allow continuous refinements and serve as a blueprint to build robust and generalizable AI algorithms.

Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk stratification, and response assessment. However, invasive bone marrow (BM) biopsies cannot be performed frequently and multifocally to assess the spatially heterogenous tumor tissue. Therefore, the goal of this study was to establish an automated framework to predict local BM biopsy results from magnetic resonance imaging (MRI). MATERIALS AND METHODS: This retrospective multicentric study used data from center 1 for algorithm training and internal testing, and data from center 2 to 8 for external testing. An nnU-Net was trained for automated segmentation of pelvic BM from T1-weighted whole-body MRI. Radiomics features were extracted from these segmentations, and random forest models were trained to predict PCI and the presence or absence of cytogenetic aberrations. Pearson correlation coefficient and the area under the receiver operating characteristic were used to evaluate the prediction performance for PCI and cytogenetic aberrations, respectively. RESULTS: A total of 672 MRIs from 512 patients (median age, 61 years; interquartile range, 53-67 years; 307 men) from 8 centers and 370 corresponding BM biopsies were included. The predicted PCI from the best model was significantly correlated ( P ≤ 0.01) to the actual PCI from biopsy in all internal and external test sets (internal test set: r = 0.71 [0.51, 0.83]; center 2, high-quality test set: r = 0.45 [0.12, 0.69]; center 2, other test set: r = 0.30 [0.07, 0.49]; multicenter test set: r = 0.57 [0.30, 0.76]). The areas under the receiver operating characteristic of the prediction models for the different cytogenetic aberrations ranged from 0.57 to 0.76 for the internal test set, but no model generalized well to all 3 external test sets. CONCLUSIONS: The automated image analysis framework established in this study allows for noninvasive prediction of a surrogate parameter for PCI, which is significantly correlated to the actual PCI from BM biopsy.

Statistical breathing curve sampling to quantify interplay effects of moving lung tumors in a 4D Monte Carlo dose calculation framework.

PURPOSE: The interplay between respiratory tumor motion and dose application by intensity modulated radiotherapy (IMRT) techniques can potentially lead to undesirable and non-intuitive deviations from the planned dose distribution. We developed a 4D Monte Carlo (MC) dose recalculation framework featuring statistical breathing curve sampling, to precisely simulate the dose distribution for moving target volumes aiming at a comprehensive assessment of interplay effects. METHODS: We implemented a dose accumulation tool that enables dose recalculations of arbitrary breathing curves including the actual breathing curve of the patient. This MC dose recalculation framework is based on linac log-files, facilitating a high temporal resolution up to 0.1 s. By statistical analysis of 128 different breathing curves, interplay susceptibility of different treatment parameters was evaluated for an exemplary patient case. To facilitate prospective clinical application in the treatment planning stage, in which patient breathing curves or linac log-files are not available, we derived a log-file free version with breathing curves generated by a random walk approach. Interplay was quantified by standard deviations σ in D5%, D50% and D95%. RESULTS: Interplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy (σD95% up to 1.3 %) showing a decrease with higher fraction doses and an increase with higher MU rates. Interplay effects for conformal treatment techniques were negligible (σ<0.1%). The log-file free version and the random walk generated breathing curves yielded similar results (deviations in σ< 0.1 %) and can be used as substitutes for interplay assessment. CONCLUSION: It is feasible to combine statistically sampled breathing curves with MC dose calculations. The universality of the presented framework allows comprehensive assessment of interplay effects in retrospective and prospective clinically relevant scenarios.

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Marrow Characterization From Whole-Body MRI: A Multicentric Feasibility Study.

OBJECTIVES: Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole BM. Reading of such whole-body scans is time-consuming, and yet radiologists can transfer only a small fraction of the information of the imaging data set to the report. This limits the influence that imaging can have on clinical decision-making and in research toward precision oncology. The objective of this feasibility study was to implement a concept for automatic, comprehensive characterization of the BM from wb-MRI, by automatic BM segmentation and subsequent radiomics analysis of 30 different BM spaces (BMS). MATERIALS AND METHODS: This retrospective multicentric pilot study used a total of 106 wb-MRI from 102 patients with (smoldering) MM from 8 centers. Fifty wb-MRI from center 1 were used for training of segmentation algorithms (nnU-Nets) and radiomics algorithms. Fifty-six wb-MRI from 8 centers, acquired with a variety of different MRI scanners and protocols, were used for independent testing. Manual segmentations of 2700 BMS from 90 wb-MRI were performed for training and testing of the segmentation algorithms. For each BMS, 296 radiomics features were calculated individually. Dice score was used to assess similarity between automatic segmentations and manual reference segmentations. RESULTS: The "multilabel nnU-Net" segmentation algorithm, which performs segmentation of 30 BMS and labels them individually, reached mean dice scores of 0.88 ± 0.06/0.87 ± 0.06/0.83 ± 0.11 in independent test sets from center 1/center 2/center 3-8 (interrater variability between radiologists, 0.88 ± 0.01). The subset from the multicenter, multivendor test set (center 3-8) that was of high imaging quality was segmented with high precision (mean dice score, 0.87), comparable to the internal test data from center 1. The radiomic BM phenotype consisting of 8880 descriptive parameters per patient, which result from calculation of 296 radiomics features for each of the 30 BMS, was calculated for all patients. Exemplary cases demonstrated connections between typical BM patterns in MM and radiomic signatures of the respective BMS. In plausibility tests, predicted size and weight based on radiomics models of the radiomic BM phenotype significantly correlated with patients' actual size and weight ( P = 0.002 and P = 0.003, respectively). CONCLUSIONS: This pilot study demonstrates the feasibility of automatic, objective, comprehensive BM characterization from wb-MRI in multicentric data sets. This concept allows the extraction of high-dimensional phenotypes to capture the complexity of disseminated BM disorders from imaging. Further studies need to assess the clinical potential of this method for automatic staging, therapy response assessment, or prediction of biopsy results.

Imaging Artifacts of Nonadhesive Liquid Embolic Agents in Conventional and Cone-beam CT in a Novel in Vitro AVM Model.

BACKGROUND: A major drawback of liquid embolic agents (LEAs) is the generation of imaging artifacts (IA), which may represent a crucial obstacle for the detection of periprocedural hemorrhage or subsequent radiosurgery of cerebral arteriovenous malformations (AVMs). This study aimed to compare the IAs of Onyx, Squid and PHIL in a novel three-dimensional in vitro AVM model in conventional computed tomography (CT) and cone-beam CT (CBCT). METHODS: Tubes with different diameters were configured in a container resembling an AVM with an artificial nidus at its center. Subsequently, the AVM models were filled with Onyx 18, Squid 18, PHIL 25% or saline and inserted into an imaging phantom (n = 10/LEA). Afterwards CT and CBCT scans were acquired. The degree of IAs was graded quantitatively (Hounsfield units in a defined region of interest) and qualitatively (feasibility of defining the nidus)-Onyx vs. Squid vs. PHIL vs. saline, respectively. RESULTS: Quantitative density evaluation demonstrated more artifacts for Onyx compared to Squid and PHIL, e.g. 48.15 ± 14.32 HU for Onyx vs. 7.56 ± 1.34 HU for PHIL in CT (p < 0.001) and 41.88 ± 7.22 density units (DU) for Squid vs. 35.22 ± 5.84 DU for PHIL in CBCT (p = 0.044). Qualitative analysis showed less artifacts for PHIL compared to Onyx and Squid in both imaging modalities while there was no difference between Onyx and Squid regarding the definition of the nidus (p > 0.999). CONCLUSION: In this novel three-dimensional in vitro AVM model, IAs were higher for the EVOH/tantalum-based LEAs Onyx and Squid compared to iodine-based PHIL. Onyx induced the highest degree of IAs with only minor differences to Squid.

Biologically consistent dose accumulation using daily patient imaging.

BACKGROUND: This work addresses a basic inconsistency in the way dose is accumulated in radiotherapy when predicting the biological effect based on the linear quadratic model (LQM). To overcome this inconsistency, we introduce and evaluate the concept of the total biological dose, bEQDd. METHODS: Daily computed tomography imaging of nine patients treated for prostate carcinoma with intensity-modulated radiotherapy was used to compute the delivered deformed dose on the basis of deformable image registration (DIR). We compared conventional dose accumulation (DA) with the newly introduced bEQDd, a new method of accumulating biological dose that considers each fraction dose and tissue radiobiology. We investigated the impact of the applied fractionation scheme (conventional/hypofractionated), uncertainties induced by the DIR and by the assigned α/ß-value. RESULTS: bEQDd was systematically higher than the conventionally accumulated dose with difference hot spots of 3.3-4.9 Gy detected in six out of nine patients in regions of high dose gradient in the bladder and rectum. For hypofractionation, differences are up to 8.4 Gy. The difference amplitude was found to be in a similar range to worst-case uncertainties induced by DIR and was higher than that induced by α/ß. CONCLUSION: Using bEQDd for dose accumulation overcomes a potential systematic inaccuracy in biological effect prediction based on accumulated dose. Highest impact is found for serial-type late responding organs at risk in dose gradient regions and for hypofractionation. Although hot spot differences are in the order of several Gray, in dose-volume parameters there is little difference compared with using conventional or biological DA. However, when local dose information is used, e.g. dose surface maps, difference hot spots can potentially change outcomes of dose-response modelling and adaptive treatment strategies.

Dataset of voxelwise correlated signal values of ADC, rCBV and FAP-specific PET of 13 Glioblastoma patients.

This dataset is based on multimodal MRI and FAP-specific PET/CT Imaging applied to 13 patients with histologically proven glioblastomas. Imaging Data was processed using Medical Imaging Interaction Toolkit (MITK) software. MRI images (contrast enhanced T1w, T2w/FLAIR, ADC, rCBV) were co-registrated with FAP-specific PET images. T2w/FLAIR hyperintensities and contrast enhancing lesions were segmented manually. Necrotic areas were segmented manually and subtracted from T2w/FLAIR hyperintensities and contrast enhancing lesions. Voxelwise ADC/rCBV and PET signal intensities in projection on T2w/FLAIR hyperintensities and contrast enhancing lesions were extracted using the pixel dumper function of the MITK software and stored as excel-files. The data presented in this article has been analysed and described in the article FAP-specific "PET signaling shows a moderately positive correlation with relative CBV and no correlation with ADC in 13 IDH wildtype Glioblastomas" published in the European Journal of Radiology.

FAP-specific PET signaling shows a moderately positive correlation with relative CBV and no correlation with ADC in 13 IDH wildtype glioblastomas.

OBJECTIVES: Targeting Fibroblast Activation Protein (FAP) is a new approach for glioblastoma imaging. In a recent pilot study glioblastomas showed elevated tracer uptake with high intratumoral heterogeneity in projection on the corresponding T2w/FLAIR and contrast enhanced MRI lesions. In this study, we correlated FAP-specific signaling with apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) signals in MRI to further characterize the significance of FAP uptake. METHODS: Clinical PET/CT scans of 13 glioblastoma patients were performed post i. v. administration of 68Ga-labelled-FAP-specific tracer molecules. PET- and corresponding MRI-scans were co-registrated. 3d volumetric segmentations were performed of T2w/FLAIR lesions and contrast enhancing lesions within co-registrated MRI slides. Signal intensity values of FAP-specific PET signaling, ADC and rCBV were analyzed for their pixel wise correlation in each patient. Pooled estimates of the correlation coefficients were calculated by using the Fisher z-transformation. RESULTS: FAP-specific PET signals showed a moderately positive correlation with rCBV values which is more pronounced within the T2w/FLAIR lesion (pooled correlation 0,229) than in the contrast enhancing tumor region (pooled correlation 0.09). FAP-specific PET signals showed no correlation with ADC values. CONCLUSIONS: The moderately positive correlation of FAP-specific signals with rCBV values in MRI indicates that FAP-signaling is not independent from perfusion, but also does not only reflect intratumoral perfusion differences. The missing correlation of FAP-specific signals with ADC indicates that FAP-specific imaging does not reflect cell density, but the spot-like expression of FAP in glioblastomas. The clinical value of FAP-specific imaging needs further investigation.

Impact of Single Dose Photons and Carbon Ions on Perfusion and Vascular Permeability: A Dynamic Contrast-Enhanced MRI Pilot Study in the Anaplastic Rat Prostate Tumor R3327-AT1.

We collected initial quantitative information on the effects of high-dose carbon (12C) ions compared to photons on vascular damage in anaplastic rat prostate tumors, with the goal of elucidating differences in response to high-LET radiation, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Syngeneic R3327-AT1 rat prostate tumors received a single dose of either 16 or 37 Gy 12C ions or 37 or 85 Gy 6 MV photons (iso-absorbed and iso-effective doses, respectively). The animals underwent DCE-MRI prior to, and on days 3, 7, 14 and 21 postirradiation. The extended Tofts model was used for pharmacokinetic analysis. At day 21, tumors were dissected and histologically examined. The results of this work showed the following: 1. 12C ions led to stronger vascular changes compared to photons, independent of dose; 2. Tumor growth was comparable for all radiation doses and modalities until day 21; 3. Nonirradiated, rapidly growing control tumors showed a decrease in all pharmacokinetic parameters (area under the curve, Ktrans, ve, vp) over time; 4. 12C-ion-irradiated tumors showed an earlier increase in area under the curve and Ktrans than photon-irradiated tumors; 5. 12C-ion irradiation resulted in more homogeneous parameter maps and histology compared to photons; and 6. 12C-ion irradiation led to an increased microvascular density and decreased proliferation activity in a largely dose-independent manner compared to photons. Postirradiation changes related to 12C ions and photons were detected using DCE-MRI, and correlated with histological parameters in an anaplastic experimental prostate tumor. In summary, this pilot study demonstrated that exposure to 12C ions increased the perfusion and/or permeability faster and led to larger changes in DCE-MRI parameters resulting in increased vessel density and presumably less hypoxia at the end of the observation period when compared to photons. Within this study no differences were found between curative and sub-curative doses in either modality.