1. Diagnosing Lung Cancer with Computer-Aided Detection:
Role-Playing in the Advanced Placement Biology Classroom
William J. Furiosi II
University of Central Florida
Purpose
Lesson Description
Computer Vision Relationship
Introduction
Day 1: Setting the stage, students receive direct instruction in the following topics:
General respiratory anatomy.
Lung cancer significance, epidemiology, and diagnosis.
Benefits and disadvantages of computed tomography (CT).
Impact of computer vision on lung nodule detection.
Connect computer vision with Advanced Placement Biology instruction using computer-aided detection algorithms to improve lung cancer diagnosis.
The bridge between biology and computer vision is reinforced based on the following applications within the lesson:
Use of Python to develop programs that meet research needs.
Use of computer algorithms to detect lung nodules at sizes smaller than manually detected by radiologists.
Region-growing as a means of segmenting nodules and the lungs from other structures in the body.
Alternative applications of computer vision are also mentioned during instruction, including:
Region-growing in Photoshop and image manipulation.
Facial recognition for surveillance cameras.
Population counting at large events.
Optimizing search engine results based on image characteristics.
Overview
Increasing technological advances have led to a significant interdisciplinary approach in the fields of biology and medicine.
This lesson aims to:
Connect medicine to computer vision applications
Introduce programming principles in a public school setting
Expose high school students to genuine medical scenarios
Elaborate on cell cycling pathways in relation to cancer
Improve information synthesis, through use of multiple charts, images, and graphs.
Figure 3: Comparison of cancer deaths by type of cancer. Lung cancer far surpasses any other type with over a quarter of all cancer-related deaths. [1]
Figure 2: Comparison of all deaths by cause. Cancer is the second leading cause of death and accounts for nearly a quarter of all deaths.[3]
Practice
Day 2: Students spend time segmenting nodules via a PowerPoint tutorial and known reference.
Acknowledgements
Education Standards
The initial segmentation will likely select a larger area than desired. Use the (maximum total volume) slider to reduce your selection to only the lung cavity. Keep in mind the limitation of region growing is that it may select too much or too little of the desired area.
AP Curriculum Standards
3.A.2: In eukaryotes, heritable information is passed to the next generation via processes that include the cell cycle and mitosis or meiosis plus fertilization.
Next Generation Sunshine State Standards
SC.912.L.16.8: Explain the relationship between mutation, cell cycle, and uncontrolled cell growth potentially resulting in cancer.
Many thanks go to the following individuals:
Salman Khokhar and Aliasghar Mortazi, UCF Ph. D. students, for their programming instruction and troubleshooting.
Dr. Ulas Bagci for his direction with segmentation of lung nodules and technical expertise.
Dr. Niels Lobo for his administration of the program, troubleshooting, and advice as co-principal investigator.
Dr. Mubarak Shah for his oversight as principle investigator.
Funding for this project was provided through the National Science Foundation, grant #
Figure 4: Sample slide from the student tutorial showing how to segment the lung and approximate lung volume.
Figure 5: Sample lung cancer data showing a nodule with a maximum diameter of 48 mm with the nodule (yellow) and lungs (salmon) segmented. Data from The Cancer Imaging Archive.[2, 4]
Role-Playing
Day 3: Students role-play a medical exam involving symptoms typical of lung cancer. Students are divided into one of two roles: Patient or Medical Resident.
Patients and medical residents will role-play an examination, consultation with an attending physician, and diagnosis and treatment.
References
[1]American Cancer Society. (2014). Cancer Facts & Figures Atlanta, GA: American Cancer Society, Inc.
[2]Clark K., Vendt B., Smith K., Freymann J., Kirby J., Koppel P., … Prior F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and operating a public information repository. Journal of Digital Imaging, 26(6),
[3]National Center for Health Statistics. (2016). Health, United States, 2015: With special feature on racial and ethnic health disparities. Washington, DC: U.S. Government Printing Office.
[4]Smith K., Clark K., Bennett W., Nolan T., Kirby J., Wolfsberger M., … Freymann J.  Data from NSCLC-Radiomics-Genomics. doi: /K9/TCIA.2015.L4FRET6Z
Staging
T: T3
N: N0
M: M0
TNM Stage: Stage IIA
Treatment Recommendations
Surgery, likely pneumonectomy.
Chemotherapy to limit further spread.
Figure 6: Sample cancerous nodule segmented and staged according to World Health Guidelines. The medical team would present these findings to the patient during the treatment stage. Data from The Cancer Imaging Archive.[2, 4]
Figure 1: The above diagram shows the stages in the animal cell cycle. The cell cycle is the most relevant application of this biology-computer vision lesson. Checkpoint regulation failures, especially in the p53 regulatory pathways, can lead to unregulated cell growth and cancer. When lung cells are exposed to toxins, like those in tobacco smoke, or radiation, they can become cancerous.
Tables 1 & 2: Patient history and nodule characterization references for use by the medical team during the examination and diagnosis stages.