PURPOSE: To prospectively determine if magnetic resonance (MR) angiography can depict intracranial vascular morphologic changes during treatment of brain metastases from breast cancer and if serial quantitative vessel tortuosity measurements can be used to predict tumor treatment response sooner than traditional methods. MATERIALS AND METHODS: Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. Twenty-two women aged 31-61 years underwent brain MR angiography prior to and 2 months after initiation of lapatinib therapy for brain metastases from breast cancer. Vessels were extracted from MR angiograms with a computer program. Changes in vessel number, radius, and tortuosity were calculated mathematically, normalized with values obtained in 34 healthy control subjects (19 women, 15 men; age range, 19-72 years), and compared with subsequent assessments of tumor volume and clinical course. RESULTS: All patients exhibited abnormal vessel tortuosity at baseline. Nineteen (86%) patients did not exhibit improvement in vessel tortuosity at 2-month follow-up, and all patients demonstrated tumor growth at 4-month follow-up. Vessel tortuosity measurements enabled us to correctly predict treatment failure 1-2 months earlier than did traditional methods. Three (14%) patients had quantitative improvement in vessel tortuosity at 2-month follow-up, with drop out of small abnormal vessels and straightening of large vessels. Each of the two patients for whom further follow-up data were available responded to treatment for more than 6 months. CONCLUSION: Study results established the feasibility of using MR angiography to quantify vessel shape changes during therapy. Although further research is required, results suggest that changes in vessel tortuosity might enable early prediction of tumor treatment response. (c) RSNA, 2007.
PURPOSE: To prospectively determine if magnetic resonance (MR) angiography can depict intracranial vascular morphologic changes during treatment of brain metastases from breast cancer and if serial quantitative vessel tortuosity measurements can be used to predict tumor treatment response sooner than traditional methods. MATERIALS AND METHODS: Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. Twenty-two women aged 31-61 years underwent brain MR angiography prior to and 2 months after initiation of lapatinib therapy for brain metastases from breast cancer. Vessels were extracted from MR angiograms with a computer program. Changes in vessel number, radius, and tortuosity were calculated mathematically, normalized with values obtained in 34 healthy control subjects (19 women, 15 men; age range, 19-72 years), and compared with subsequent assessments of tumor volume and clinical course. RESULTS: All patients exhibited abnormal vessel tortuosity at baseline. Nineteen (86%) patients did not exhibit improvement in vessel tortuosity at 2-month follow-up, and all patients demonstrated tumor growth at 4-month follow-up. Vessel tortuosity measurements enabled us to correctly predict treatment failure 1-2 months earlier than did traditional methods. Three (14%) patients had quantitative improvement in vessel tortuosity at 2-month follow-up, with drop out of small abnormal vessels and straightening of large vessels. Each of the two patients for whom further follow-up data were available responded to treatment for more than 6 months. CONCLUSION: Study results established the feasibility of using MR angiography to quantify vessel shape changes during therapy. Although further research is required, results suggest that changes in vessel tortuosity might enable early prediction of tumor treatment response. (c) RSNA, 2007.
Authors: P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther Journal: J Natl Cancer Inst Date: 2000-02-02 Impact factor: 13.506
Authors: Elizabeth Bullitt; Nancy U Lin; Matthew G Ewend; Donglin Zeng; Eric P Winer; Lisa A Carey; J Keith Smith Journal: Med Image Comput Comput Assist Interv Date: 2006
Authors: Christopher G Willett; Yves Boucher; Emmanuelle di Tomaso; Dan G Duda; Lance L Munn; Ricky T Tong; Daniel C Chung; Dushyant V Sahani; Sanjeeva P Kalva; Sergey V Kozin; Mari Mino; Kenneth S Cohen; David T Scadden; Alan C Hartford; Alan J Fischman; Jeffrey W Clark; David P Ryan; Andrew X Zhu; Lawrence S Blaszkowsky; Helen X Chen; Paul C Shellito; Gregory Y Lauwers; Rakesh K Jain Journal: Nat Med Date: 2004-01-25 Impact factor: 53.440
Authors: M O Leach; K M Brindle; J L Evelhoch; J R Griffiths; M R Horsman; A Jackson; G C Jayson; I R Judson; M V Knopp; R J Maxwell; D McIntyre; A R Padhani; P Price; R Rathbone; G J Rustin; P S Tofts; G M Tozer; W Vennart; J C Waterton; S R Williams; P Workman Journal: Br J Cancer Date: 2005-05-09 Impact factor: 7.640
Authors: H Wildiers; G Guetens; G De Boeck; E Verbeken; B Landuyt; W Landuyt; E A de Bruijn; A T van Oosterom Journal: Br J Cancer Date: 2003-06-16 Impact factor: 7.640
Authors: Ewelina Kluza; Jean-Paul J E Kleijnen; Milou H Martens; Dorit Rennspiess; Monique Maas; Cécile R L P N Jeukens; Robert G Riedl; Axel zur Hausen; Geerard L Beets; Regina G H Beets-Tan Journal: Eur Radiol Date: 2015-08-30 Impact factor: 5.315
Authors: Eugene Kim; Spyros Stamatelos; Jana Cebulla; Zaver M Bhujwalla; Aleksander S Popel; Arvind P Pathak Journal: Ann Biomed Eng Date: 2012-05-08 Impact factor: 3.934
Authors: Shom Goel; Dan G Duda; Lei Xu; Lance L Munn; Yves Boucher; Dai Fukumura; Rakesh K Jain Journal: Physiol Rev Date: 2011-07 Impact factor: 37.312
Authors: Rachel A Freedman; Elizabeth Bullitt; Lixian Sun; Rebecca Gelman; Gordon Harris; Jennifer A Ligibel; Ian E Krop; Ann H Partridge; Emily Eisenberg; Eric P Winer; Nancy U Lin Journal: Clin Breast Cancer Date: 2011-06-22 Impact factor: 3.225
Authors: Nancy U Lin; Laleh Amiri-Kordestani; Diane Palmieri; David J Liewehr; Patricia S Steeg Journal: Clin Cancer Res Date: 2013-12-01 Impact factor: 12.531
Authors: Elizabeth Bullitt; Matthew Ewend; James Vredenburgh; Allan Friedman; Weili Lin; Kathy Wilber; Donglin Zeng; Stephen R Aylward; David Reardon Journal: Neuroimage Date: 2008-12-06 Impact factor: 6.556