Education
Supports ENT trainees, pathology residents, medical students, surgeons, clinicians, and cytotechnologists learning how head and neck tumors present in African settings.
Research Infrastructure by Kebeza
African Head & Neck Tumor Image Registry
A clinical-image-first African registry of head and neck tumor presentations, linking actual clinical images with radiology, cytology, histology, and future precision oncology data where available.
The registry starts with what is available today: visible clinical presentation images of head and neck masses and lesions. It is designed to preserve valuable African clinical data while building toward education, research, digital pathology, and AI-ready cancer datasets.
Why it matters
Clinical presentation is often where the African cancer pathway begins.
Many global image datasets focus on histology or radiology alone. This registry begins with the visible clinical presentation: the neck mass, oral lesion, facial swelling, salivary gland mass, thyroid swelling, skin lesion, or other head and neck tumor presentation.
Research readiness
Creates structured clinical-image data for future studies on presentation, diagnostic pathways, clinicopathologic correlation, referral delay, and outcomes.
AI readiness
Builds responsibly governed African image datasets for future validation of decision-support, digital pathology, and precision oncology tools.
Accepted case types
No clinical image, no case for this registry.
Cytology-only, histology-only, and cytology-plus-histology-only cases belong in the broader African Pathology Image Registry. This focused registry is anchored by the clinical presentation image.
Accepted into this registry
Cases with a clinical presentation image, with optional radiology, cytology, histology, gross specimen images, and best available diagnosis.
Clinical image only
Clinical + radiology
Clinical + cytology
Clinical + histology
Clinical + radiology + cytology
Clinical + radiology + histology
Full multimodal case
Not accepted here
Cases without clinical presentation images are redirected to the broader African Pathology Image Registry.
Cytology only
Histology only
Pathology images only
Scientific credibility
Evidence levels keep incomplete data useful but honest.
The registry is designed so valuable retrospective clinical images are not lost simply because age, sex, radiology, cytology, or histology is missing. Each case is clearly labelled by evidence level.
Future roadmap
From clinical images to African precision oncology infrastructure.
The first phase starts pragmatically with clinical presentation images and available linked diagnostic material. Over time, where ethical approval, patient consent, funding, FFPE block access, and institutional partnerships allow, Kebeza aims to expand the registry into a richer African oncology intelligence platform.
Future layers may include FFPE block-derived sequencing, tumor molecular profiles, histology-genomics correlation, treatment received, treatment response, recurrence, follow-up, outcomes, survival, referral pathway data, and AI-ready structured datasets.
FFPE sequencing
Molecular profiles
Treatment response
Recurrence
Follow-up outcomes
AI-ready datasets
Precision oncology research
Governance
Built for ethical, de-identified, controlled use.
Public teaching cases should be de-identified and approved before publication. Restricted datasets should remain under controlled access, with review for visible identifiers, embedded radiology labels, hospital numbers, names, dates of birth, facial identification, duplicate cases, and uncertain diagnosis labels.
Contributor review
Images and metadata are reviewed before inclusion in public-facing teaching or research views.
Access control
Cases can be separated into public teaching, restricted research, and private partner datasets.
African ownership
The registry is positioned as African-owned cancer data infrastructure built from real diagnostic pathways.
Partner with Kebeza
Kebeza is seeking collaborators in ENT surgery, pathology, radiology, oncology, medical education, AI, data governance, and African cancer research implementation.