Citations 2
The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI–Dynamic Contrast‐Enhanced challenge
Shalom, Eve , Kim, Harrison , Heijden, Rianne A. van der , Ahmed, Zaki , Patel, Reyna, DiCarlo, Julie C. , Yankeelov, Thomas E. , Stokes, Ashley M. , Grech‐Sollars, Matthew , Sahoo, Prativa , Verma, Sanjay Kumar , Rathore, Divya, Kazerouni, Anum S. , LoCastro, Eve , Paudyal, Ramesh , Wolansky, Ivan A. , Shukla‐Dave, Amita , Schouten, Pepijn, Gurney‐Champion, Oliver J. , Macíček, Ondřej , Vitouš, Jiří , Das, Ayesha , Mikheev, Artem , Rusinek, Henry , Cristinacce, Penny L. Hubbard , Little, Ross A. , Cheung, Susan , O’Connor, James P.B. , Moloney, Brendan, Bobholz, Samuel , Duenweg, Savannah , Laue, Hendrik , Sung, Kyunghyun , Nabavizadeh, Ali , Rad, Hamidreza Saligheh , Hu, Leland , Kazerooni, Anahita Fathi , Shalom, Eve S , van der Heijden, Rianne A , Hormuth, David A , DiCarlo, Julie C , Yankeelov, Thomas E , Dortch, Richard D , Grech-Sollars, Matthew , Kazerouni, Anum S , Partridge, Savannah C , LoCastro, Eve , Wolansky, Ivan A , Jiřík, Radovan , Macíček, Ondřej , Bartoš, Michal , Vitouš, Jiří , Das, Ayesha Bharadwaj , Kim, S Gene , Rusinek, Henry , Berks, Michael , Hubbard Cristinacce, Penny L , O'Connor, James P B , Parker, Geoff J M , LaViolette, Peter S , Bobholz, Samuel , Duenweg, Savannah , Virostko, John , Sung, Kyunghyun , Saligheh Rad, Hamidreza , Sourbron, Steven , Bell, Laura C , Fathi Kazerooni, Anahita , Paudyal, Ramesh , Shukla-Dave, Amita , Sisco, Nicholas J. , Inglese, Marianna , Toschi, Nicola , Singh, Anup K. , Schouten, Pepijn, Bokacheva, Louisa , Bell, Laura C.
Magnetic Resonance in Medicine | December 20, 2023 | Volume: 91 | Issue: 5 | Pages: 1803-1821
AbstractPurpose 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 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 measurement.MethodsA framework was created to evaluate values produced by DCE‐MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' values, the applied software, and a standard operating procedure. These were evaluated using the proposed score defined with accuracy, repeatability, and reproducibility components.ResultsAcross the 10 received submissions, the 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 analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility.ConclusionsThis study reports results from the OSIPI‐DCE challenge and highlights the high inter‐software variability within 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.
Accuracy and processing time of kidney volume measurement methods in rodents polycystic kidney disease models: superiority of semiautomated kidney segmentation
Doss, Mary Claire, Mullen, Sean, Roye, Ronald, Zhou, Juling, Chumley, Phillip , Mrug, Elias, Qian, Feng , Harris, Peter C. , Yoder, Bradley K. , Kim, Harrison , Mrug, Michal , Wallace, Darren P , Qian, Feng , Kim, Harrison , Mrug, Michal , Harris, Peter C , Yoder, Bradley K , Wallace, Darren P.
American Journal of Physiology-Renal Physiology | February 16, 2023 | Volume: 324 | Issue: 4 | Pages: F423-F430
Total kidney volume (TKV) is a valuable readout in preclinical studies for autosomal dominant and autosomal recessive polycystic kidney diseases (ADPKD and ARPKD). Since conventional TKV assessment by manual contouring of kidney areas in all images is time-consuming, we developed a template-based semiautomatic image segmentation method (SAM) and validated it in three commonly used ADPKD and ARPKD models. SAM-based TKV measurements were fast, highly reproducible, and accurate across mouse and rat ARPKD and ADPKD models.