Quantitative Total Extensible Imaging (QTxI)
Overview
Quantitative Total Extensible Imaging (QTxI) is a software tool developed by AIQ Solutions to aid trained medical professionals in the evaluation and information management of digital medical images. Cleared by the FDA, QTxI is designed for use by radiologists, oncologists, nuclear medicine physicians, medical imaging technologists, dosimetrists, and physicists. The software operates on DICOM CT and PET modalities, supporting ACR/NEMA DICOM 3.0 standards. Its core functionalities include receiving, storing, retrieving, displaying, and processing digital medical images. QTxI enables the identification and contouring of Regions of Interest (ROIs), facilitating quantitative and statistical analysis of full or partial-body scans through registration to template space. The tool provides 3D interactive rendering of images with highlighted ROIs and, at the time of its FDA clearance, included the Quantitative Total Bone Imaging (QTBI) module for identifying and measuring hot-spots on PET scans. AIQ Solutions has since evolved its technology, with TRAQinform IQ being a modification of QTxI, also FDA-cleared, focusing on quantifying changes in regions of interest over time to optimize late-stage cancer care.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Evaluation and information management of digital medical images (DICOM CT and PET)
- Display, registration, and fusion of medical images from multiple modalities
- Identification and contouring of Regions of Interest (ROIs)
- Quantitative and statistical analysis of full or partial-body scans
- 3D interactive rendering of images with highlighted ROIs
- Automated quantification of ROIs and changes in ROIs (via QTBI module)
- Cloud-based HIPAA-compliant data pipelines
- Automated report generation
- Lesion-level longitudinal quantitative imaging
- Radiomics and lesion heterogeneity metrics
- Integration into existing clinical workflows
Use Cases
- Optimizing late-stage cancer care
- Monitoring treatment response in metastatic cancer (e.g., lung, lymphoma, prostate, bladder, head and neck, neuroendocrine system, melanoma)
- Aiding oncologists/clinicians in adjusting therapies and optimizing clinical outcomes
- Personalized medicine through analysis of individual patient treatment response
- Quantitative assessment of early treatment response
- Evaluating lesion response heterogeneity for prognostication
What Physicians Need to Know
When utilizing QTxI, focus on integrating its quantitative outputs with your clinical judgment and other patient data. Pay close attention to alerts generated by changes in ROIs, but also be mindful of potential alert fatigue; customize alert settings if possible to prioritize critical information. Leverage QTxI's objective measurements to refine differential diagnoses and monitor treatment response more precisely, especially in oncology. Ensure the tool is well-integrated into your existing EHR to streamline workflow and avoid data silos. Regularly review the audit trail for insights into decision-making processes and for quality assurance.
Optimal performance of QTxI relies heavily on seamless integration with existing hospital information systems, particularly PACS (Picture Archiving and Communication Systems) for image acquisition and EHRs for patient context and documentation. Bidirectional data exchange is key to ensure QTxI can pull relevant patient history and write back quantitative analysis results and any generated alerts directly into the patient's record. Integration should support standardized imaging formats like DICOM 3.0. Future integrations could explore AI-driven differential diagnosis platforms, where QTxI's quantitative data could serve as a valuable input.
Details
| Category | Oncology AI, Radiology & Imaging AI |
| Pricing | Contact for pricing — Not publicly available; contact vendor for custom pricing. |
| Deployment | Cloud-based |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated QTxI received FDA 510(k) clearance (K173444) on July 23, 2018, as a Class II medical device. It is intended to aid in the evaluation and information management of digital medical images by trained medical professionals. AIQ Solutions' subsequent technology, TRAQinform IQ, also has FDA clearance (K233998). |
| Integrations | |
| EHR | Not specified |
| Specialties | Nuclear Medicine, Oncology, Radiology |
What the Web Says
Quantitative Total Extensible Imaging (QTxI) by AIQ Solutions is an FDA-cleared software designed to help clinicians, particularly oncologists, assess cancer treatment response by analyzing imaging data over time. It provides novel information about the quantification of change in regions of interest (ROIs) and aids in optimizing therapy plans. The software integrates with serial radiographic images like PET and CT, offers cloud-based image upload, and generates comprehensive reports.
Overall: MixedStrengths
- FDA-cleared for clinical use, ensuring regulatory compliance and reliability.
- Aids oncologists and clinicians in optimizing therapy plans by providing quantitative assessment of cancer treatment response.
- Offers quantitative assessment of lesion response heterogeneity.
- Integrates with serial radiographic images (e.g., PET, CT) and PACS systems.
- Provides cloud-based image upload and comprehensive reporting for oncologists.
- Utilizes machine learning for skeletal and anatomic structure segmentation and threshold-based ROI identification and contouring.
Limitations
- Limited public reviews from physicians, healthcare IT, or tech reviewers specifically for QTxI, making it difficult to gauge widespread user experience.
- Some general AIQ reviews (not specific to QTxI) mention limitations in custom field setup for lower versions and time-consuming manual project code setup.
- One general AIQ review noted a non-user-friendly platform and unhelpful customer support.
- Lack of readily available detailed pricing information.
- No specific reviews found on Reddit, G2, or Capterra directly addressing QTxI, making it challenging to assess broader user sentiment from these platforms.
Based on reviews from: HealthAidb, accessdata.fda.gov, Indeed.com, PubMed - NIH, G2, PMC - NIH, AuntMinnie, QIPCM, ClinicalTrials.gov, Capterra, Signify Research, Reddit, Trustpilot
Last updated: 2026-07-17
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