Automatic Anatomy Recognition (AAR)

by Quantitative Radiology Solutions  · Based in United States → — We enable body-wide analysis of medical images to personalize cancer treatment decisions.
Nuclear Medicine Oncology Radiology
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Custom or subscription-based
Regulatory Status Disclosed

Overview

Quantitative Radiology Solutions (QRS) offers advanced body-wide quantification of medical images for applications in radiology, radiation oncology, and surgery. Its flagship product, Automatic Anatomy Recognition (AAR), is a unique software designed to support the localization and delineation of all major organs in multiple body regions using MRI, CT, and PET/CT images.

AAR dramatically reduces the time required for radiation oncologists and dosimetrists to delineate organs for treatment planning, from several hours to less than 5 minutes. This AI-powered solution improves the accuracy and consistency of Organs at Risk (OAR) contouring, which is crucial for personalizing cancer treatment decisions and minimizing exposure of healthy organs during radiation therapy.

Deployed on a cloud-based platform, AAR is a software-only medical device that operates independently of specific treatment planning systems. It is agnostic to the disease process being treated (e.g., head & neck, thoracic cancers) and various radiation treatment delivery methods or modalities.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automatic localization and delineation of major organs
  • Operates on MRI, CT, and PET/CT images
  • Reduces contouring time from hours to less than 5 minutes for radiation therapy planning
  • Supports body-wide quantification of medical images
  • Improves accuracy and consistency of Organs at Risk (OAR) contouring
  • Cloud-based platform deployment
  • Works independently of specific treatment planning systems
  • Agnostic to disease process (e.g., head & neck, thoracic cancers)
  • Agnostic to radiation treatment delivery method (photons, protons) and modality (3D-CRT, IMRT)
  • Agnostic to intent of radiation treatment (definitive, neoadjuvant, adjuvant, palliative)

Use Cases

  • Radiation therapy planning
  • Contouring of Organs at Risk (OARs)
  • Personalizing cancer treatment decisions
  • Body-wide disease quantification
  • Body composition assessment
  • Reducing side effects for cancer patients undergoing radiation therapy

What Physicians Need to Know

Key Capabilities
Automatically processes CT studies to generate contours for organs-at-risk (OARs) in radiation treatment planning. It significantly reduces the time for recognizing, delineating, and identifying anatomical objects and diseased tissue on MRI, CT, and PET/CT images, from hours to minutes (e.g., less than 5 minutes for radiation therapy planning). The system supports body-wide localization and delineation of major organs in regions like the head & neck and thorax, and is designed to be modality-independent. AAR employs fuzzy anatomy models built from patient populations and uses hierarchical image analysis to recognize and delineate anatomical differences. It is agnostic to the method, modality, and intent of radiation treatment delivery, as well as the specific disease process being treated.
Clinical Utility
AAR improves the accuracy and consistency of OAR contouring, which is crucial for precise radiation therapy. By dramatically reducing the time required for treatment planning, it allows highly skilled professionals to dedicate more time to patient care. This automation addresses the traditionally time-consuming and error-prone nature of manual contouring. The ability to efficiently re-contour during treatment to account for anatomical changes can lead to improved patient outcomes and fewer side effects.
Compliance Status
Quantitative Radiology Solutions' AAR technology received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for use in radiation treatment planning in April/November 2021, classifying it as a Class II medical device. The software underwent Verification and Validation Testing in accordance with the IEC 62304 standard.
User Experience
The system automatically processes CT studies to produce contours without human intervention, significantly streamlining the workflow by reducing contouring time from hours to minutes. Users should note that contour modifications are not performed within AAR and require a separate system.
Implementation Complexity
Being a cloud-based platform, AAR may offer a less complex deployment compared to on-premise solutions. Its design for independent operation from specific TPS can simplify integration efforts. However, ensuring DICOM 3.0 compliance is a prerequisite. General integration of AI into radiology workflows can be complex, necessitating strategic planning.
Evidence Base
Clinical evaluations at four radiation treatment centers have demonstrated that AAR improves the accuracy and consistency of OAR contouring and reduces treatment planning time. The technology originated from innovations at the University of Pennsylvania's Medical Image Processing Group and has received STTR grants from the National Cancer Institute and National Science Foundation. Studies on the AAR-RT framework show recognition accuracy within 2 voxels and delineation boundary distance within ~1 voxel on 'good' cases, comparable to inter-dosimetrist variability. Research papers detail the AAR methodology, including multiobject generalization of OASM and object recognition strategies, applied across various body regions and imaging protocols.
Physician Tip

AAR offers substantial time savings and improved consistency in OAR contouring for radiation therapy planning, allowing more focus on complex cases and patient interaction. While it automates contour generation, be prepared to utilize existing treatment planning systems for any necessary contour adjustments. Its FDA clearance provides a level of assurance regarding its safety and effectiveness for its intended use in adults for head & neck and thoracic regions.

AAR is a cloud-based, software-only solution designed for independent operation from your primary treatment planning system, requiring DICOM 3.0 compliance for seamless data exchange. Plan for a workflow where AAR generates initial contours, which are then imported into your existing TPS for review and potential modification, as AAR itself does not support editing.

Details

Category Oncology AI, Radiology & Imaging AI
Pricing Custom or subscription-based — Custom; subscription-based; pay-per-analysis; tiered
DeploymentCloud-based
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

Received 510(k) clearance from the U.S. Food and Drug Administration (FDA) on April 20, 2021 (K203610) for its Automatic Anatomy Recognition (AAR) technology for use in radiation treatment planning. It is a software-only medical device that automatically processes CT studies to produce contours for organs-at-risk.
Integrations
EHR Not specified
Specialties Nuclear Medicine, Oncology, Radiology

What the Web Says

Automatic Anatomy Recognition (AAR) from Quantitative Radiology Solutions (QRS) is generally viewed positively, particularly for its ability to automate and standardize anatomical labeling in medical imaging. Reviewers highlight its potential to improve efficiency and reduce manual errors in clinical workflows. While specific detailed reviews from all requested sources are not readily available, the overall sentiment leans towards appreciation for its technological advancement in radiology.

Overall: Positive

Strengths

  • Automates anatomical labeling, saving significant time for clinicians.
  • Enhances standardization and consistency in medical image analysis.
  • Reduces the potential for human error in identifying and labeling anatomical structures.
  • Improves workflow efficiency in radiology departments.
  • Supports quantitative analysis by providing accurate anatomical context.
  • Potentially aids in research and clinical trials by standardizing data.

Limitations

  • Limited detailed, independent reviews from physicians or major tech review sites (G2, Capterra) are publicly available.
  • Potential for a learning curve during initial integration into existing systems.
  • Dependence on the quality of input images for accurate recognition.
  • Specific pricing and cost-benefit analyses are not widely published.
  • May require customization to fit unique clinical protocols or preferences.
  • Lack of extensive user-generated content or discussions on platforms like Reddit.

Based on reviews from: Quantitative Radiology Solutions (QRS) website, Academic papers and research articles mentioning AAR technology, Industry news and technology publications in medical imaging, Healthcare IT forums (limited specific discussion on QRS AAR), Radiology professional organizations (general discussion on AI in radiology)

Last updated: 2026-07-18

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Press & Coverage

PACT Philadelphia
Quantitative Radiology Solutions Receives 510(k) Clearance for AAR
Quantitative Radiology Solutions (QRS) received 510(k) clearance from the FDA for its Automatic Anatomy Recognition (AAR) technology for use in radiation treatment planning. AAR is a software-only medical device that automatically processes CT studies to produce contours for organs-at-risk.
2021-11
Penn Center for Innovation
Quantitative Radiology Solutions receives 510(k) FDA clearance
Quantitative Radiology Solutions (QRS) announced on April 21, 2021, that it received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its Automatic Anatomy Recognition (AAR) technology for radiation treatment planning. AAR is a software-only medical device designed to improve the accuracy and consistency of OAR contouring and reduce treatment planning time.
2021-04
Innolitics
Automatic Anatomy Recognition (AAR) (K203610) u2014 FDA 510(k)
This FDA 510(k) premarket notification details the clearance of Automatic Anatomy Recognition (AAR) as a software-only medical device. It is intended for use by technicians and trained physicians to derive contours of anatomical structures from CT studies for radiation treatment planning, specifically in the head & neck and thoracic regions.
2021-04
Ben Franklin Technology Partners
QRS is Expanding its Automatic Anatomy Recognition Software to Help Physicians Personalize Treatment Planning and Response Assessment for Cancer Patients.
Quantitative Radiology Solutions (QRS) received a second STTR grant from the National Cancer Institute (NCI) to expand its Automatic Anatomy Recognition (AAR) software. This grant will enable AAR to be used for automated PET/CT interpretation, disease burden estimation, and standardized reporting.
2020-08
Penn Center for Innovation
Spinout Stories: Quantitative Radiology Solutions
Quantitative Radiology Solutions (QRS) was founded to commercialize innovations in Automatic Anatomy Recognition (AAR) from the University of Pennsylvania. AAR is a software that recognizes and analyzes anatomical objects and diseased tissue in medical images to improve radiation therapy planning.
2020-05
PMC
Automatic Anatomy Recognition using Neural Network Learning of Object Relationships via Virtual Landmarks
This paper introduces a new one-shot Automatic Anatomy Recognition (AAR) method that utilizes virtual landmarks and neural networks to learn complex object relationships. The method aims to improve object recognition in AAR, particularly for head and neck cancer patients undergoing radiation therapy.
2018-03
DOI
Automatic anatomy recognition in whole-body PET/CT images
This paper demonstrates the adaptation of Automatic Anatomy Recognition (AAR) methodology to whole-body PET/CT images, aiming to improve object localization accuracy for quantifying disease burden. The study compares various strategies for recognizing objects in PET/CT images against diagnostic CT images.
2016-01
SPIE Digital Library
Automatic anatomy recognition on CT images with pathology
This paper investigates strategies for adapting the Automatic Anatomy Recognition (AAR) system to diagnostic CT images of patients with various pathologies. The goal is to move towards automated body-wide disease quantification by improving object recognition in abnormal images.
2016-03

Videos

Product demos, reviews, and walkthroughs for Automatic Anatomy Recognition (AAR).

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Frequently Asked Questions

AAR solutions are designed to integrate seamlessly into existing clinical workflows, often embedded within Electronic Health Records (EHRs) to automatically process medical images and display results. Its primary applications include efficient and accurate anatomical segmentation for diagnostic purposes, surgical planning, and radiation therapy planning, where it helps contour organs at risk.
AAR solutions, as with any healthcare AI handling Protected Health Information (PHI), must adhere to stringent regulations like HIPAA. This involves implementing robust security measures such as data encryption, strict access controls for authorized personnel, and comprehensive protocols for managing potential security breaches. Vendors typically establish formal agreements to ensure data handling complies with privacy policies and applicable laws.
AAR consistently outperforms manual segmentation in terms of efficiency, significantly reducing the time-consuming and tedious nature of traditional methods. In terms of accuracy, automatic segmentation techniques have demonstrated over 90% accuracy when compared to manual segmentation, which is considered the gold standard. However, some discrepancies can still occur, highlighting the ongoing development in the field.
Implementing AAR solutions typically involves various cost considerations, including initial licensing fees, integration expenses with existing imaging and EHR systems, and ongoing maintenance and support costs. Pricing models can vary, potentially including subscription-based services or per-use fees, depending on the vendor and the scale of deployment. Specific costs will depend on the complexity of the solution and the size of the healthcare institution.
Current limitations of AAR technology include potential variations in accuracy due to factors like image quality, artifacts, and the inherent heterogeneity of patient populations and complex pathologies. Inaccurate segmentation can lead to misinterpretations or misguided clinical procedures. Therefore, careful consideration is needed when applying AAR to diverse patient demographics or unusual anatomical presentations.
The accuracy and reliability of AAR for clinical use are validated through rigorous comparisons with manual segmentation, often considered the gold standard, utilizing metrics like Dice coefficient and true/false positive volume fractions. Evidence supporting its performance comes from systematic reviews and studies demonstrating high delineation and recognition accuracy in various anatomical regions. As a medical device, AAR solutions also undergo regulatory review (e.g., FDA clearance) requiring demonstration of safety and effectiveness, and clinical validation assesses its utility in specific clinical contexts.

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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