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Breast Cancer Detection: The Development and Pilot Study of a "Tactile Landscape" as a Standardized Testing Tool
Daisy E Veitch1, Melissa Bochner, Johan F M Molenbroek
1From the Faculty of Industrial Design Engineering (D.E.V.), Delft University of Technology (TU Delft), Delft, the Netherlands; Breast Endocrine and Surgical Oncology Unit (M.B.), Royal Adelaide Hospital, Adelaide, SA, Australia; Faculty of Industrial Design Engineering (J.F.M.M., R.H.M.G.), Delft University of Technology (TU Delft), Delft, the Netherlands; and College of Medicine and Public Health (H.O.), Flinders University, Adelaide, SA, Australia.
A new tactile landscape (TL) test effectively assesses breast lump palpation skills. Experts accurately identified simulated lesions, while students showed significant room for improvement, highlighting the test's potential for training.
Area of Science:
- Medical Education
- Diagnostic Skills Assessment
- Surgical Simulation
Background:
- Competent breast lump palpation skills are crucial, particularly in resource-limited settings.
- Current assessment methods for these skills require enhancement.
Purpose of the Study:
- To design and develop a novel test for evaluating palpation skills in identifying and discriminating simulated breast lesions.
- To assess the efficacy of this test by comparing expert and student performance.
Main Methods:
- A "tactile landscape" (TL) model was created with simulated common breast lesions (cancers, cysts) at varying depths to mimic adiposity.
- Realistic anatomical features (ribs, muscle) and nodularity were incorporated.
- A testing protocol was used to evaluate 5 experts and 20 medical students on lesion identification and discrimination.
Main Results:
- The TL model demonstrated realistic breast softness (53%) and nodularity (60%).
- Experts achieved 100% accuracy in identifying lesions and non-lesions within the TL.
- Students performed poorly, with a mean score of 65%, indicating a significant skill gap compared to experts.
Conclusions:
- The developed tactile landscape test effectively differentiates between expert and student palpation abilities.
- This assessment tool has the potential to improve breast lump detection training and evaluation.
- Implementing this test could address a critical need for improved clinical breast examination skills assessment.
