title: The clinical impact of mean vessel size and solidity in breast carcinoma patients.
abstract: Angiogenesis quantification, through vessel counting or area estimation in the most vascular part of the tumour, has been found to be of prognostic value across a range of carcinomas, breast cancer included. We have applied computer image analysis to quantify vascular properties pertaining to size, shape and spatial distributions in photographed fields of CD34 stained sections. Aided by a pilot (98 cases), seven parameters were selected and validated on a separate set from 293 breast cancer patients. Two new prognostic markers were identified through continuous cox regression with endpoints breast cancer specific survival and distant disease free survival: The average size of the vessels as measured by their perimeter (p = 0.003 and 0.004, respectively), and the average complexity of the vessel shapes measured by their solidity (p = 0.004 and 0.004). The Hazard ratios for the corresponding median-dichotomized markers were 2.28 (p = 0.005) and 1.89 (p = 0.016) for the mean perimeter and 1.80 (p = 0.041) and 1.55 (p = 0.095) for the shape complexity. The markers were associated with poor histologic type, high grade, necrosis, HR negativity, inflammation, and p53 expression (vessel size only). Both markers were found to strongly influence the prognostic properties of vascular invasion (VI) and disseminated tumour cells in the bone marrow. The latter being prognostic only in cases with large vessels (p = 0.004 and 0.043) or low complexity (p = 0.018 and 0.024), but not in the small or complex vessel groups (p>0.47). VI was significant in all groups, but showed greater hazard ratios for small and low complexity vessels (6.54-11.2) versus large and high complexity vessels (2.64-3.06). We find that not only the overall amount of produced vasculature in angiogenic hot-spots is of prognostic significance, but also the morphological appearance of the generated vessels, i.e. the size and shape of vessels in the studied hot spots.
authors.affiliation: Department of Physics, University of Oslo, Oslo, Norway.
authors.forename: Lars Tore Gyland
authors.initials: LT
authors.lastname: Mikalsen
authors.forename: Hari Prasad
authors.initials: HP
authors.lastname: Dhakal
authors.forename: Øyvind S
authors.initials: ØS
authors.lastname: Bruland
authors.forename: Bjørn
authors.initials: B
authors.lastname: Naume
authors.forename: Elin
authors.initials: E
authors.lastname: Borgen
authors.forename: Jahn M
authors.initials: JM
authors.lastname: Nesland
authors.forename: Dag Rune
authors.initials: DR
authors.lastname: Olsen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000235:genetics*; D001808:Blood Vessels / Q000378:metabolism / Q000473:pathology*; D001943:Breast Neoplasms / Q000098:blood supply* / Q000175:diagnosis / Q000401:mortality / Q000473:pathology; D002277:Carcinoma / Q000098:blood supply* / Q000175:diagnosis / Q000401:mortality / Q000473:pathology; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008853:Microscopy / Q000295:instrumentation / Q000379:methods; D008875:Middle Aged; D060787:Neoplasm Grading; D009389:Neovascularization, Pathologic; D011379:Prognosis; D016016:Proportional Hazards Models; D016159:Tumor Suppressor Protein p53 / Q000235:genetics*
chemical_list: D014408:Biomarkers, Tumor; D016159:Tumor Suppressor Protein p53