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Cross-calibration, Least Significant Change and Quality Assurance in Multiple Dual-Energy X-ray Absorptiometry Scanner Environments: 2019 ISCD Official Position

Jankowski LG, Warner S, Gaither K, Lenchik L, Fan B, Lu Y, et al.

J Clin Densitom, 2019 09 07;22(4):472-483.
PMID: 31558404 DOI: 10.1016/j.jocd.2019.09.001

In preparation for the International Society for Clinical Densitometry Position Development Conference (PDC) 2019 in Kuala Lumpur, Malaysia, a cross-calibration and precision task force was assembled and tasked to review the literature, summarize the findings, and generate positions to answer 4 related questions provided by the PDC Steering Committee, which expand upon the current ISCD official positions on these subjects. (1) How should a provider with multiple dual-energy X-ray absorptiometry (DXA) scanners of the same make and model calculate least significant change (LSC)? (2) How should a provider with multiple DXA systems with the same manufacturer but different models calculate LSC? (3) How should a provider with multiple DXA systems from different manufacturers and models calculate LSC? (4) Are there specific phantom procedures that one can use to provide trustworthy in vitro cross calibration for same models, different models, and different makes? Based on task force deliberations and the resulting systematic literature reviews, 3 new positions were developed to address these more complex scenarios not addressed by current official positions on single scanner cross calibration and LSC. These new positions provide appropriate guidance to large multiple DXA scanner providers wishing to offer patients flexibility and convenience, and clearly define good clinical practice requirements to that end.
Use of Bone Health Evaluation in Orthopedic Surgery: 2019 ISCD Official Position

Anderson PA, Morgan SL, Krueger D, Zapalowski C, Tanner B, Jeray KJ, et al.

J Clin Densitom, 2019 08 16;22(4):517-543.
PMID: 31519473 DOI: 10.1016/j.jocd.2019.07.013

This position development conference (PDC) Task Force examined the assessment of bone status in orthopedic surgery patients. Key questions included which orthopedic surgery patients should be evaluated for poor bone health prior to surgery and which subsets of patients are at high risk for poor bone health and adverse outcomes. Second, the reliability and validity of using bone densitometry techniques and measurement of specific geometries around the hip and knee before and after arthroplasty was determined. Finally, the use of computed tomography (CT) attenuation coefficients (Hounsfield units) to estimate bone quality at anatomic locations where orthopedic surgery is performed including femur, tibia, shoulder, wrist, and ankle were reviewed. The literature review identified 665 articles of which 198 met inclusion exclusion criteria and were selected based on reporting of methodology, reliability, or validity results. We recommend that the orthopedic surgeon be aware of established ISCD guidelines for determining who should have additional screening for osteoporosis. Patients with inflammatory arthritis, chronic corticosteroid use, chronic renal disease, and those with history of fracture after age 50 are at high risk of osteoporosis and adverse events from surgery and should have dual energy X-ray absorptiometry (DXA) screening before surgery. In addition to standard DXA, bone mineral density (BMD) measurement along the femur and proximal tibia is reliable and valid around implants and can provide valuable information regarding bone remodeling and identification of loosening. Attention to positioning, selection of regions of interest, and use of special techniques and software is required. Plain radiographs and CT provide simple, reliable methods to classify the shape of the proximal femur and to predict osteoporosis; these include the Dorr Classification, Cortical Index, and critical thickness. Correlation of these indices to central BMD is moderate to good. Many patients undergoing orthopedic surgery have had preoperative CT which can be utilized to assess regional quality of bone. The simplest method available on most picture archiving and communications systems is to simply measure a regions of interest and determine the mean Hounsfield units. This method has excellent reliability throughout the skeleton and has moderate correlation to DXA based on BMD. The prediction of outcome and correlation to mechanical strength of fixation of a screw or implant is unknown.
Fulltext Measurement challenge: protocol for international case-control comparison of mammographic measures that predict breast cancer risk

Dench E, Bond-Smith D, Darcey E, Lee G, Aung YK, Chan A, et al.

BMJ Open, 2019 Dec 31;9(12):e031041.
PMID: 31892647 DOI: 10.1136/bmjopen-2019-031041

INTRODUCTION: For women of the same age and body mass index, increased mammographic density is one of the strongest predictors of breast cancer risk. There are multiple methods of measuring mammographic density and other features in a mammogram that could potentially be used in a screening setting to identify and target women at high risk of developing breast cancer. However, it is unclear which measurement method provides the strongest predictor of breast cancer risk.
METHODS AND ANALYSIS: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk.
ETHICS AND DISSEMINATION: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3).

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