Andrea Morotti1,2, Javier M Romero3,4,5, Michael J Jessel4, Andrew M Hernandez6, Anastasia Vashkevich4, Kristin Schwab4, Joseph D Burns7, Qaisar A Shah8, Thomas A Bergman9, M Fareed K Suri10, Mustapha Ezzeddine11, Jawad F Kirmani12, Sachin Agarwal13, Angela Hays Shapshak14, Steven R Messe15, Chitra Venkatasubramanian16, Katherine Palmieri17, Christopher Lewandowski18, Tiffany R Chang19, Ira Chang20, David Z Rose21, Wade Smith22, Chung Y Hsu23, Chun-Lin Liu23, Li-Ming Lien24, Chen-Yu Hsiao24, Toru Iwama25, Mohammad Rauf Afzal26, Christy Cassarly27, Steven M Greenberg4, Renee' Hebert Martin27, Adnan I Qureshi26, Jonathan Rosand3,4, John M Boone6, Joshua N Goldstein3,4,28. 1. Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA. a.morotti@ymail.com. 2. J. P. Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, 175 Cambridge Street, Suite 300, Boston, MA, 02114, USA. a.morotti@ymail.com. 3. Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA. 4. J. P. Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, 175 Cambridge Street, Suite 300, Boston, MA, 02114, USA. 5. Neuroradiology Service, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. 6. Department of Radiology, University of California Davis, Sacramento, CA, USA. 7. Department of Neurology, Lahey Hospital and Medical Center, Burlington, MA, USA. 8. Abington Memorial Hospital, Abington, PA, USA. 9. Hennepin County Medical Center, Minneapolis, MN, USA. 10. St. Cloud Hospital, St. Cloud, MN, USA. 11. University of Minnesota, Minneapolis, MN, USA. 12. Stroke & Neurovascular Center, JFK Medical Center, Edison, NJ, USA. 13. Columbia University Medical Center, New York, NY, USA. 14. University of Alabama at Birmingham, Birmingham, AL, USA. 15. University of Pennsylvania, Philadelphia, PA, USA. 16. Stanford University, Stanford, CA, USA. 17. The University of Kansas Health System, Kansas City, KS, USA. 18. Henry Ford Hospital, Detroit, MI, USA. 19. University of Texas Medical School, Houston, TX, USA. 20. Colorado Neurological Institute, Swedish Medical Center, Englewood, CO, USA. 21. Tampa General Hospital, University of South Florida College of Medicine, Tampa, FL, USA. 22. UCSF Medical Center, San Francisco, CA, USA. 23. China Medical University Hospital, Taichung, Taiwan. 24. Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan. 25. Gifu University Hospital, Gifu, Japan. 26. Zeenat Qureshi Stroke Research Center, University of Minnesota, Minneapolis, MN, USA. 27. Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA. 28. Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Abstract
PURPOSE: The CT angiography (CTA) spot sign is a strong predictor of hematoma expansion in intracerebral hemorrhage (ICH). However, CTA parameters vary widely across centers and may negatively impact spot sign accuracy in predicting ICH expansion. We developed a CT iodine calibration phantom that was scanned at different institutions in a large multicenter ICH clinical trial to determine the effect of image standardization on spot sign detection and performance. METHODS: A custom phantom containing known concentrations of iodine was designed and scanned using the stroke CT protocol at each institution. Custom software was developed to read the CT volume datasets and calculate the Hounsfield unit as a function of iodine concentration for each phantom scan. CTA images obtained within 8 h from symptom onset were analyzed by two trained readers comparing the calibrated vs. uncalibrated density cutoffs for spot sign identification. ICH expansion was defined as hematoma volume growth >33%. RESULTS: A total of 90 subjects qualified for the study, of whom 17/83 (20.5%) experienced ICH expansion. The number of spot sign positive scans was higher in the calibrated analysis (67.8 vs 38.9% p < 0.001). All spot signs identified in the non-calibrated analysis remained positive after calibration. Calibrated CTA images had higher sensitivity for ICH expansion (76 vs 52%) but inferior specificity (35 vs 63%) compared with uncalibrated images. CONCLUSION: Normalization of CTA images using phantom data is a feasible strategy to obtain consistent image quantification for spot sign analysis across different sites and may improve sensitivity for identification of ICH expansion.
PURPOSE: The CT angiography (CTA) spot sign is a strong predictor of hematoma expansion in intracerebral hemorrhage (ICH). However, CTA parameters vary widely across centers and may negatively impact spot sign accuracy in predicting ICH expansion. We developed a CT iodine calibration phantom that was scanned at different institutions in a large multicenter ICH clinical trial to determine the effect of image standardization on spot sign detection and performance. METHODS: A custom phantom containing known concentrations of iodine was designed and scanned using the stroke CT protocol at each institution. Custom software was developed to read the CT volume datasets and calculate the Hounsfield unit as a function of iodine concentration for each phantom scan. CTA images obtained within 8 h from symptom onset were analyzed by two trained readers comparing the calibrated vs. uncalibrated density cutoffs for spot sign identification. ICH expansion was defined as hematoma volume growth >33%. RESULTS: A total of 90 subjects qualified for the study, of whom 17/83 (20.5%) experienced ICH expansion. The number of spot sign positive scans was higher in the calibrated analysis (67.8 vs 38.9% p < 0.001). All spot signs identified in the non-calibrated analysis remained positive after calibration. Calibrated CTA images had higher sensitivity for ICH expansion (76 vs 52%) but inferior specificity (35 vs 63%) compared with uncalibrated images. CONCLUSION: Normalization of CTA images using phantom data is a feasible strategy to obtain consistent image quantification for spot sign analysis across different sites and may improve sensitivity for identification of ICH expansion.
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Authors: Viesha A Ciura; H Bart Brouwers; Raffaella Pizzolato; Claudia J Ortiz; Jonathan Rosand; Joshua N Goldstein; Steven M Greenberg; Stuart R Pomerantz; R Gilberto Gonzalez; Javier M Romero Journal: Stroke Date: 2014-10-09 Impact factor: 7.914
Authors: Dar Dowlatshahi; H Bart Brouwers; Andrew M Demchuk; Michael D Hill; Richard I Aviv; Lee-Anne Ufholz; Michael Reaume; Max Wintermark; J Claude Hemphill; Yasuo Murai; Yongjun Wang; Xingquan Zhao; Yilong Wang; Na Li; Takatoshi Sorimachi; Mitsunori Matsumae; Thorsten Steiner; Timolaos Rizos; Steven M Greenberg; Javier M Romero; Jonathan Rosand; Joshua N Goldstein; Mukul Sharma Journal: Stroke Date: 2016-02-04 Impact factor: 7.914