Brigitte Degasperi

Dr. Brigitte Degasperi


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 June 2024 in Veterinary Sciences
Verified
Journal Article
Open access
PDF file
IGImaine Glahn
Imaine Glahn
AHAndreas Haghofer
Andreas Haghofer
TDTaryn Donovan
Taryn Donovan
BDBrigitte Degasperi
Brigitte Degasperi
ABAlexander Bartel
Alexander Bartel
CBChristof Albert Bertram
Christof Albert Bertram
The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists’ NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists’ estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required.

14 January 2022 in Veterinary Record Case Reports
Verified
Journal Article
Open access
PDF file
CLChristian Lohinger
Christian Lohinger
MGMichaela Gumpenberger
Michaela Gumpenberger
UKUrsula Susanne Kolm
Ursula Susanne Kolm
BDBrigitte Degasperi
Brigitte Degasperi
Peritoneopericardial diaphragmatic hernia (PPDH) is a congenital defect allowing communication between the peritoneal cavity and the pericardial sac, through which abdominal organs may herniate into the pericardial space. The condition can be asymptomatic or symptomatic, and if symptomatic, accompanied mostly with non‐specific gastrointestinal or respiratory clinical signs. A 2‐year‐old, male, neutered mixed breed dog was referred due to fever, lethargy and decreased food intake over the last 2 weeks. Abdominal ultrasound was performed and a transposition of abdominal organs into the thoracic cavity was suspected. Further diagnostic imaging confirmed PPDH with herniation of the gall bladder and spleen into the pericardial sac. The dog underwent surgery for hernia repair. Severe pneumopericardium subsequently complicated by pericardial effusion developed postoperatively. Both complications resolved without intervention. The dog never showed signs of haemodynamic instability or cardiac tamponade.