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Purpose: Ktrans$$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for Ktrans$$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging–Dynamic Contrast‐Enhanced (OSIPI‐DCE) challenge was designed to benchmark methods to better help the efforts to standardize Ktrans$$ {K}^{\mathrm{trans}} $$ measurement. Methods: A framework was created to evaluate Ktrans$$ {K}^{\mathrm{trans}} $$ values produced by DCE‐MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for Ktrans$$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' Ktrans$$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIPIgold$$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. Results: Across the 10 received submissions, the OSIPIgold$$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0–1 = lowest–highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in Ktrans$$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. Conclusions: This study reports results from the OSIPI‐DCE challenge and highlights the high inter‐software variability within Ktrans$$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real‐world clinical setting, many of these tools may perform differently with different benchmarking methodology. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Cardiac-induced liver motion can bias liver ADC measurements and compromise reproducibility. The purpose of this work was to enable motion-robust DWI on multiple MR scanners and assess reproducibility of the resulting liver ADC measurements., Methods: First moment-optimized diffusion imaging (MODI) was implemented on three MR scanners with various gradient performances and field strengths. MODI-DWI and conventional Stejskal-Tanner monopolar (MONO) DWI were acquired in eight (N = 8) healthy volunteers on each scanner, and DWI repetitions were combined using three different averaging methods. For each combination of scanner, acquisition, and averaging method, ADC measurements from each liver segment were collected. Systematic differences in ADC values between scanners and methods were assessed with linear mixed effects modeling, and reproducibility was quantified via reproducibility coefficients., Results: MODI reduced left-right liver lobe ADC bias from 0.43 × 10 -3  mm 2 /s (MONO) to 0.19 × 10 -3  mm 2 /s (MODI) when simple (unweighted) repetition averaging was used. The bias was reduced from 0.23 × 10 -3  mm 2 /s to 0.06 × 10 -3  mm 2 /s using weighted averaging, and 0.14 × 10 -3  mm 2 /s to 0.01 × 10 -3  mm 2 /s using squared weighted averaging. There was no significant difference in ADC measurements between field strengths or scanner gradient performance. MODI improved reproducibility coefficients compared to MONO: 0.84 × 10 -3  mm 2 /s vs. 0.63 × 10 -3  mm 2 /s (MODI vs. MONO) for simple averaging, 0.66 × 10 -3  mm 2 /s vs. 0.50 × 10 -3  mm 2 /s for weighted averaging, and 0.61 × 10 -3  mm 2 /s vs. 0.47 × 10 -3  mm 2 /s for squared weighted averaging., Conclusion: The feasibility of motion-robust liver DWI using MODI was demonstrated on multiple MR scanners. MODI improved interlobar agreement and reproducibility of ADC measurements in a healthy cohort., (© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)