C. Molodowitch
Brigham and Women's Hospital
7 Papers
59 Citations
C. Molodowitch is an academic researcher from Brigham and Women's Hospital. The author has contributed to research in topics: Radiation therapy & Quality assurance. The author has an hindex of 3, co-authored 5 publications. Previous affiliations of C. Molodowitch include Rush University Medical Center.
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Papers
Low Incidence of Chest Wall Pain with a Risk-Adapted Lung Stereotactic Body Radiation Therapy Approach Using Three or Five Fractions Based on Chest Wall Dosimetry
Thibaud P. Coroller,Raymond H. Mak,John H. Lewis,Elizabeth H. Baldini,Aileen B. Chen,Aileen B. Chen,Yolonda L. Colson,Fred Hacker,Gretchen Hermann,David Kozono,E. Mannarino,C. Molodowitch,Jon O. Wee,David J. Sher,Joseph H. Killoran +14 more
TL;DR: Optimization of treatment plans to reduce CW dose and a risk-adapted fractionation strategy of three or five fractions based on the CW V30 resulted in a low incidence of CW toxicity.
Independent brachytherapy plan verification software: improving efficacy and efficiency.
Antonio L. Damato,Phillip M. Devlin,Mandar S. Bhagwat,Ivan Buzurovic,Scott Friesen,Jorgen L. Hansen,Larissa J. Lee,C. Molodowitch,Paul L. Nguyen,Desmond A. O'Farrell,Akila N. Viswanathan,Christopher L. Williams,Joseph H. Killoran,Robert A. Cormack +13 more
TL;DR: SAV significantly reduced the number of undetected errors in HDR treatment plans compared to MV, and reduced the time required for plan verification.
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TU-E-BRB-02: A Decision Support Tool for SBRT Planning Using a Searchable DVH Database.
John H. Lewis,John H. Lewis,Raymond H. Mak,Raymond H. Mak,C. Molodowitch,C. Molodowitch,E. Mannarino,E. Mannarino,Elizabeth H. Baldini,Elizabeth H. Baldini,A.B. Chen,A.B. Chen,David Kozono,David Kozono,David J. Sher,David J. Sher,Fred Hacker,Fred Hacker,Joseph H. Killoran,Joseph H. Killoran +19 more
TL;DR: A searchable DVH database was constructed to provide planners, physicists, and physicians with a straightforward means of comparing plans against historic distributions of DVHs.
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Implementation of an Automated Radiation Oncology Prescription Checking System, Revealing a Baseline Prescription Error Rate of at Least 0.2%
Itai Pashtan,Tara Kosak,C. Molodowitch,Cindy Hancox,Joseph H. Killoran,M. Czerminska,Jeremy S. Bredfeldt,Daniel W. Cail,K Meghan,Roy B. Tishler,Raymond H. Mak +10 more
TL;DR: In this paper , an automated prescription checking system was designed and implemented to detect the potential for erroneous prescription entry in radiation oncology clinics, which is based on a review of 14,487 prescriptions written in 2019-2020.