Morphometric analysis using automated image analysis of CD34-positive vessels in salivary gland acinic cell carcinoma

Luukkaa, Heikki; Laitakari, Jaakko; Vahlberg, Tero; Klemi, Pekka; Grénman, Reidar

doi:10.1080/00016480601053099

Cited by 14 publications

(12 citation statements)

References 18 publications

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“…Finally, the analysis of the relationship between the vascular markers shows that vessel size is a robust pathological marker with respect to different definitions, and that the prognostic ability of these markers is independent of vascular density. There is relevant work on similar markers in other cancers [29]–[31], [42], [47]–[54], but—to the best of our knowledge—no prognostic studies in breast cancer. There is, however, some literature on the association between vascular density measurements and DTC in breast cancer [11]–[14].…”

Section: Discussionmentioning

confidence: 99%

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The Clinical Impact of Mean Vessel Size and Solidity in Breast Carcinoma Patients

et al. 2013

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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.

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Section: Discussionmentioning

confidence: 99%

“…High MVPμ values (large vessels) and low MVSμ values (high complexity shapes) contribute to poor prognosis; as well as high MVA Σ values (high vascular area) [29], but MVD is inconsequential [29].…”

Section: Methodsmentioning

confidence: 99%

The Clinical Impact of Mean Vessel Size and Solidity in Breast Carcinoma Patients

et al. 2013

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“…Tumour relapse occurred in about 15% of patients within the first 5 years 25 . Apart from clinical parameters, prognostic impact could be demonstrated for the Ki‐67 index 24 and an irregularity and a larger size of concomitant blood vessels 23 …”

Section: Introductionmentioning

confidence: 99%

“…22 Due to the infrequency and low aggressiveness of ACC, in the last 20 years only a few clinicopathological studies with long-term follow-up have been published in the English literature. 1,18,[23][24][25][26] The largest study comprised 35 patients, with a median follow-up period of 5 years (range 3.4-210 months). 25 The 5-year overall survival (OS) was 100% for low-grade carcinomas and 69% for high-grade carcinomas (P = 0.01).…”

Section: Introductionmentioning

confidence: 99%

The many faces of acinic cell carcinomas of the salivary glands: a study of 40 cases relating histological and immunohistological subtypes to clinical parameters and prognosis

et al. 2012

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“…A few semi-automatic methods were developed particularly to avoid variability due to human error and evaluated in comparison to manual counting methods for breast cancer [11], squamous cell carcinoma of the head and neck [12], urinary bladder carcinoma [13], and acinic cell carcinoma [14]. Belien et al [11] used fixed-thresholding -one of the simplest methods in image segmentation and object features in grey-scaled images of breast cancer to count microvessels in hot spots.…”

Section: Introductionmentioning

confidence: 99%

Automatic identification of angiogenesis in double stained images of liver tissue

et al. 2009

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BackgroundTo grow beyond certain size and reach oxygen and other essential nutrients, solid tumors trigger angiogenesis (neovascularization) by secreting various growth factors. Based on this fact, several researches proposed that density of newly formed vessels correlate with tumor malignancy. Vessel density is known as a true prognostic indicator for several types of cancer. However, automated quantification of angiogenesis is still in its primitive stage, and deserves more intelligent methods by taking advantages accruing from novel computer algorithms.ResultsThe newly introduced characteristics of subimages performed well in identification of region-of-angiogenesis. The proposed technique was tested on 522 samples collected from two high-resolution tissues. Having 0.90 overall f-measure, the results obtained with Support Vector Machines show significant agreement between automated framework and manual assessment of microvessels.ConclusionThis study introduces a new framework to identify angiogenesis to measure microvessel density (MVD) in digitalized images of liver cancer tissues. The objective is to recognize all subimages having new vessel formations. In addition to region based characteristics, a set of morphological features are proposed to differentiate positive and negative incidences.

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Morphometric analysis using automated image analysis of CD34-positive vessels in salivary gland acinic cell carcinoma

Cited by 14 publications

References 18 publications

The Clinical Impact of Mean Vessel Size and Solidity in Breast Carcinoma Patients

The Clinical Impact of Mean Vessel Size and Solidity in Breast Carcinoma Patients

The many faces of acinic cell carcinomas of the salivary glands: a study of 40 cases relating histological and immunohistological subtypes to clinical parameters and prognosis

Automatic identification of angiogenesis in double stained images of liver tissue

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