# An open-source software for microCT-based longitudinal tracking of musculoskeletal tissues

> **NIH NIH P30** · UNIVERSITY OF PENNSYLVANIA · 2022 · $243,750

## Abstract

Project Summary (Supplement Project)
 The micro computed tomography (µCT) Imaging Core (µCTIC) is an integral part of the Penn Center for
Musculoskeletal Disorders (PCMD). Since its inception in 2012, the PCMD µCTIC has grown into a thriving
resource for the University of Pennsylvania and the region’s MSK research community, serving a vibrant and
growing base of 73 active PCMD faculty members and more than 170 trainees from their laboratories to
acquire over 55,000 µCT scans, resulting in over 400 terabytes of data. An important recent advance in µCT
technology is in vivo imaging of small animals, which enables evaluation of changes in a living animal non-
invasively and repeatedly over time. Another exciting advancement is high-resolution peripheral quantitative
CT (HR-pQCT), which can assess three-dimensional (3D) bone microarchitecture, geometry, and bone mineral
density in the distal peripheral skeleton of clinical patients. Currently, the µCTIC operates 3 in vivo µCT
scanners and an HR-pQCT scanner for longitudinal imaging of small rodents and clinical research subjects,
respectively. Consequently, individual datasets have grown in size and complexity, along with a growing
demand for specialized image analysis for longitudinal image data registration, post-processing, and
visualization from our users. To address these needs, the µCTIC has developed a customized software
platform called Computed Tomography Processing & Registration - Open Sourced (CTPros) for automated
data management, customized image processing, longitudinal image registration and analysis, and two-
dimensional (2D) and 3D visualization. This open-source Python software package with a Graphic User
Interface (GUI) is compatible with Mac, Linux, and Windows operating systems. Compared to other available
commercial and open-source software, CTPros is the only one that is specifically designed and have been
validated for quantitative analysis of musculoskeletal tissues based on longitudinal µCT images. Despite the
powerful functions of the CTPros software for academic research, the current version of CTPros is still lacking
software documentation and a logging system and only supports limited data formats. Through the support of
this supplement, we aim to ensure the rigor of CTPros-derived measurements, refine the software
documentation and logging system to improve user feedback, and package CTPros into standalone and
executable packages with containerized runtime to improve intersystem compatibility. Moreover, by releasing
beta versions to obtain user feedback on documentation, features, and usability, we aim to incorporate these
feedbacks into a formal release of CTPros to the general research community.

## Key facts

- **NIH application ID:** 10609255
- **Project number:** 3P30AR069619-07S1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** LOUIS J SOSLOWSKY
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $243,750
- **Award type:** 3
- **Project period:** 2016-07-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10609255

## Citation

> US National Institutes of Health, RePORTER application 10609255, An open-source software for microCT-based longitudinal tracking of musculoskeletal tissues (3P30AR069619-07S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10609255. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*