Anterior Cruciate Ligament Injuries, Anterior Cruciate Ligament Rupture, Anterior Cruciate Ligament Tear, Osteo Arthritis Knee
Conditions
Keywords
acl tear, acl, acl rupture, acl injury, osteo arthritis
Brief summary
The purpose of this study is to assess if a zoledronic acid injection can alter the trajectory of joint degeneration following an acute anterior cruciate ligament (ACL) injury.
Detailed description
After being informed about the study and potential risks and all participants giving written informed consent, this project will establish a cohort of young men and women who within six weeks have sustained an acute rupture of the ACL. The cohort is randomized into a control and treatment group, where the treatment group receives a zoledronic acid injection at baseline. The cohort will be followed radiographically with high resolution peripheral quantitative computed tomography (HR-pQCT), dual-energy computed tomography (DECT), digital radiography (X-Ray), bi-planar X-ray (EOS) and magnetic resonance imaging (MRI) for eighteen months to monitor the progression of joint changes and the effects of zoledronic acid.
Interventions
5 mg / 100 mL intravenous infusion
DRUGPlacebo
100 mL intravenous infusion
Sponsors
University of Calgary
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Subject)
Intervention model description
The cohort is randomized into a control and treatment group, where the treatment group receives a zoledronic acid injection within 6 weeks of ACL injury.
Eligibility
Sex/Gender
ALL
Age
25 Years to 45 Years
Healthy volunteers
No
Inclusion criteria
* Clinical evidence of an acute unilateral ACL tear (full-thickness, complete tear) will be recruited. This age range is chosen to ensure participants have fully developed adult bone structures and to exclude participants with menopause as this could affect study results. * Participants with combined ligament deficiencies (posterior cruciate, medial and/or lateral collateral) or meniscal injury will be included. Participants must be able to fully extend the knee while supported at the time of the baseline measurement in order to conduct the HR-pQCT scan. * Participants with a serum calcium level in the normal range (2.10-2.60 mmol/L) and a creatinine level above 59 (reported as eGFR) will be included.
Exclusion criteria
* Individuals with contraindications to zoledronic acid (see below) * Prior knee ligament and/or meniscus tears, and/or intra-articular fractures. * Females who are pregnant or planning pregnancy within a year will not be eligible. The research team will recommend participants who are planning to become pregnant within the next five years to withdraw their participation. * Individuals with knees larger than the CT scanner's circular field of view. * Individuals with a history of disease and/or treatment affecting bone turnover in the past 12 months. * Individuals with injuries or implants that are not MRI-safe. Zoledronic acid is contraindicated for: * Patients who are hypersensitive to this drug or to any ingredient in the formulation, or to any bisphosphonates or component of the container. * Severe renal impairment with creatinine clearance \<35 mL/min and in those with evidence of acute renal impairment. For this study, participants with a creatinine clearance \<50 mL/min may be excluded. * Non-corrected hypocalcaemia at the time of infusion. * Pregnant and nursing mothers. * Patients who are already taking another bisphosphonate (ex. for osteoporosis).
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Bone microarchitecture changes at 6 months as assessed by high resolution peripheral quantitative computed tomography (HR-pQCT) | Baseline, 6 months | To determine morphological parameters from HR-pQCT scans, the trabecular portion must be isolated from the cortical shell of the bone in order to analyse the components separately. This is accomplished with an already developed auto-segmentation algorithm. In addition, the raw HR-pQCT images must be converted to binary images, wherein each voxel (3D pixel) is either labelled 'bone' or 'not bone.' This segmentation is performed by an algorithm which applies either a Gaussian or Laplace-Hamming filter in addition to a threshold to the grey-scale images. The binary images can then be analysed and morphological parameters can be determined. The changes in bone microarchitecture will be assessed at 6 months in comparison to baseline. |
| Bone microarchitecture changes at 18 months as assessed by high resolution peripheral quantitative computed tomography (HR-pQCT) | Baseline, 18 months | To determine morphological parameters from HR-pQCT scans, the trabecular portion must be isolated from the cortical shell of the bone in order to analyse the components separately. This is accomplished with an already developed auto-segmentation algorithm. In addition, the raw HR-pQCT images must be converted to binary images, wherein each voxel (3D pixel) is either labelled 'bone' or 'not bone.' This segmentation is performed by an algorithm which applies either a Gaussian or Laplace-Hamming filter in addition to a threshold to the grey-scale images. The binary images can then be analysed and morphological parameters can be determined. The changes in bone microarchitecture will be assessed at 18 months in comparison to baseline. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Bone marrow lesions (BML) and soft tissue injury changes at 18 months as assessed by MRI | Baseline, 18 months | MRI data will be segmented to identify the bone surface in a similar fashion as described for HR-pQCT data. Using a threshold-based approach BMLs will be identified, and their location and volume will be recorded in cubic millimetres (mm\^3). This analysis will be performed using custom algorithms in Python and the visualization toolkit. The changes in the location and volume of the BMLs will be assessed at 18 months comparison to baseline. |
| Knee alignment as assessed by bi-planar x-ray | Baseline | Joint alignment by bi-planar x-ray (EOS) In a standing position, the baseline study visit will capture the alignment of the tibia and femur bones bilaterally so that alignment of the knee joint can be assessed. This is a standard clinical imaging device, and the software for measurement of knee alignment is built into the system. |
| Patient reported outcomes using ACL Quality of Life Questionnaire - Baseline | Baseline | Patient reported outcomes at baseline will be assessed using \- ACL Quality of Life Questionnaire Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using ACL Quality of Life Questionnaire - 2 Months | 2 Months | Patient reported outcomes at baseline will be assessed using \- ACL Quality of Life Questionnaire Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using ACL Quality of Life Questionnaire - 6 Months | 6 Months | Patient reported outcomes at baseline will be assessed using \- ACL Quality of Life Questionnaire Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using ACL Quality of Life Questionnaire - 18 Months | 18 Months | Patient reported outcomes at baseline will be assessed using \- ACL Quality of Life Questionnaire Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using Knee injury and Osteoarthritis Outcome Score (KOOS) - Questionnaire - Baseline | Baseline | Patient reported outcomes will be assessed using \- Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire Minimum Value: 1 (best outcome); Maximum Value: 5 (worse outcome) |
| Patient reported outcomes using Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire - 2 Months | 2 months | Patient reported outcomes will be assessed using \- Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire Minimum Value: 1 (best outcome); Maximum Value: 5 (worse outcome) |
| Patient reported outcomes using Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire - 6 Months | 6 months | Patient reported outcomes will be assessed using \- Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire Minimum Value: 1 (best outcome); Maximum Value: 5 (worse outcome) |
| Patient reported outcomes using Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire - 18 Months | 18 months | Patient reported outcomes will be assessed using \- Knee injury and Osteoarthritis Outcome Score (KOOS) Questionnaire Minimum Value: 1 (best outcome); Maximum Value: 5 (worse outcome) |
| Patient reported outcomes using 36-Item Short Form Survey (SF-36) Questionnaire - Baseline | Baseline | Patient reported outcomes will be assessed using \- 36-Item Short Form Survey (SF-36) Questionnaire Questions 1, 2, 20, 22, 34, 36 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 3-12 - Minimum Value: 1 (worst outcome); Maximum Value: 3 (best outcome) Question 13-19 - Minimum Value: 1 (worst outcome); Maximum Value: 2 (best outcome) Questions 21, 23, 26, 27, 30 - Minimum Value: 1 (best outcome); Maximum Value: 6 (worst outcome) Questions 24, 25, 28, 29, 31 - Minimum Value: 1 (worst outcome); Maximum Value: 6 (best outcome) Questions 32, 33, 35 - Minimum Value: 1 (worst outcome); Maximum Value: 5 (best outcome) |
| Bone marrow lesions (BML) and soft tissue injury changes at 2 months as assessed by Magnetic Resonance Imaging (MRI) | Baseline, 2 months | MRI data will be segmented to identify the bone surface in a similar fashion as described for HR-pQCT data. Using a threshold-based approach BMLs will be identified, and their location and volume will be recorded in cubic millimetres (mm\^3). This analysis will be performed using custom algorithms in Python and the visualization toolkit. The changes in the location and volume of the BMLs will be assessed at 2 months comparison to baseline. |
| Patient reported outcomes using 36-Item Short Form Survey (SF-36) Questionnaire - 6 months | 6 months | Patient reported outcomes will be assessed using \- 36-Item Short Form Survey (SF-36) Questionnaire Questions 1, 2, 20, 22, 34, 36 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 3-12 - Minimum Value: 1 (worst outcome); Maximum Value: 3 (best outcome) Question 13-19 - Minimum Value: 1 (worst outcome); Maximum Value: 2 (best outcome) Questions 21, 23, 26, 27, 30 - Minimum Value: 1 (best outcome); Maximum Value: 6 (worst outcome) Questions 24, 25, 28, 29, 31 - Minimum Value: 1 (worst outcome); Maximum Value: 6 (best outcome) Questions 32, 33, 35 - Minimum Value: 1 (worst outcome); Maximum Value: 5 (best outcome) |
| Patient reported outcomes using 36-Item Short Form Survey (SF-36) Questionnaire - 18 months | 18 months | Patient reported outcomes will be assessed using \- 36-Item Short Form Survey (SF-36) Questionnaire Questions 1, 2, 20, 22, 34, 36 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 3-12 - Minimum Value: 1 (worst outcome); Maximum Value: 3 (best outcome) Question 13-19 - Minimum Value: 1 (worst outcome); Maximum Value: 2 (best outcome) Questions 21, 23, 26, 27, 30 - Minimum Value: 1 (best outcome); Maximum Value: 6 (worst outcome) Questions 24, 25, 28, 29, 31 - Minimum Value: 1 (worst outcome); Maximum Value: 6 (best outcome) Questions 32, 33, 35 - Minimum Value: 1 (worst outcome); Maximum Value: 5 (best outcome) |
| Patient reported outcomes using EQ-5D-5L Questionnaire - Baseline | Baseline | Patient reported outcomes will be assessed using \- EQ-5D-5L Questionnaire Questions 1-5 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 6 - Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using EQ-5D-5L Questionnaire - 2 months | 2 months | Patient reported outcomes will be assessed using \- EQ-5D-5L Questionnaire Questions 1-5 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 6 - Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using EQ-5D-5L Questionnaire - 6 months | 6 months | Patient reported outcomes will be assessed using \- EQ-5D-5L Questionnaire Questions 1-5 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 6 - Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes using EQ-5D-5L Questionnaire - 18 months | 18 months | Patient reported outcomes will be assessed using \- EQ-5D-5L Questionnaire Questions 1-5 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 6 - Minimum Value: 0 (worst outcome); Maximum Value: 100 (best outcome) |
| Patient reported outcomes Health History Questionnaire (HHQ) - Baseline | Baseline | Patient reported outcomes will be assessed using \- Health History Questionnaire (HHQ) (No scale) |
| Patient reported outcomes Health History Questionnaire (HHQ) - 2 months | 2 months | Patient reported outcomes will be assessed using \- Health History Questionnaire (HHQ) (No scale) |
| Patient reported outcomes Health History Questionnaire (HHQ) - 6 months | 6 months | Patient reported outcomes will be assessed using \- Health History Questionnaire (HHQ) (No scale) |
| Patient reported outcomes Health History Questionnaire (HHQ) - 18 months | 18 months | Patient reported outcomes will be assessed using \- Health History Questionnaire (HHQ) (No scale) |
| Patient reported outcomes using 36-Item Short Form Survey (SF-36) Questionnaire - 2 months | 2 months | Patient reported outcomes will be assessed using \- 36-Item Short Form Survey (SF-36) Questionnaire Questions 1, 2, 20, 22, 34, 36 - Minimum Value: 1 (best outcome); Maximum Value: 5 (worst outcome) Question 3-12 - Minimum Value: 1 (worst outcome); Maximum Value: 3 (best outcome) Question 13-19 - Minimum Value: 1 (worst outcome); Maximum Value: 2 (best outcome) Questions 21, 23, 26, 27, 30 - Minimum Value: 1 (best outcome); Maximum Value: 6 (worst outcome) Questions 24, 25, 28, 29, 31 - Minimum Value: 1 (worst outcome); Maximum Value: 6 (best outcome) Questions 32, 33, 35 - Minimum Value: 1 (worst outcome); Maximum Value: 5 (best outcome) |
| Bone marrow lesions (BML) and soft tissue injury changes at 6 months as assessed by MRI | Baseline, 6 months | MRI data will be segmented to identify the bone surface in a similar fashion as described for HR-pQCT data. Using a threshold-based approach BMLs will be identified, and their location and volume will be recorded in cubic millimetres (mm\^3). This analysis will be performed using custom algorithms in Python and the visualization toolkit. The changes in the location and volume of the BMLs will be assessed at 6 months comparison to baseline. |
Countries
Canada
Outcome results
None listed