TCU Senior Design 2025–26 · CenterTX

MPC Plus
Radiation Oncology
QA Platform

A full-stack Quality Assurance ecosystem designed for the modern medical physics department. Automating threshold monitoring and delivering deep analytics into geometry and beam consistency — ensuring patient safety through algorithmic precision.

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Viewing Data

Generating Graphs

Generating Reports

Dose Output Correction

Auto Data Ingestion

Personalized Accents

About the Project

Machine Performance Check Plus

Machine Performance Check Plus (MPC-Plus) is a full-stack Quality Assurance ecosystem designed for the modern medical physics department. Radiation oncology clinics rely on daily QA, but existing tools lack analytics, auditing, and workflow support, making data review inefficient and fragmented.

By leveraging a distributed architecture featuring a Python-driven data extraction engine, a PostgreSQL database, and a Next.js-powered frontend, we provide a centralized hub for multi-machine tracking. Our system automates threshold monitoring and provides deep-dive analytics into geometry and beam consistency, ensuring patient safety through algorithmic precision.

The team was evenly split, with three members focusing on backend development and three on frontend development, ensuring balanced expertise across the full application stack.

🐍 Python 🐘 PostgreSQL ▲ Next.js 🔗 REST API 🐳 Docker 🌐 Network Drive 📈 Data Analytics

What We Built

Key Features

MPC-Plus streamlines QA workflows, enhances decision-making, and ensures compliance through centralized data management, automation, and clear performance insights.

Data Visualization

Interactive charts and graphs for viewing MPC results across all machines. Spot trends and anomalies at a glance.

Graph Generation

Automated generation of beam profile and dose-output graphs. Export-ready visualizations for clinical review.

Report Generation

One-click PDF and structured reports that compile daily QA results, threshold exceedances, and performance summaries.

Dose Output Correction

Automated correction algorithms to calibrate dose output measurements, reducing manual physicist intervention.

Automatic Data Ingestion

Seamless ETL pipeline ingesting files from the network drive. Python-driven parsers extract and normalize raw linac data automatically.

Personalized Color Accents

Each user can choose their own accent color scheme, making the dashboard feel personal while maintaining clinical clarity.