10.1007/s11999-008-0293-5

Nicole Ehrhart¹, Susan Kraft², David Conover³, Randy N. Rosier⁴ and Edward M. Schwarz⁴

Received: 16 October 2007 Accepted: 24 April 2008 Published online: 10 June 2008

Abstract Although massive allografts are widely used for reconstruction of critical defects in long bones caused by tumor or trauma, many will have inadequate long-term outcomes. Toward a tissue engineering solution to this problem, we developed experimental stem cell and gene therapy adjuvants that induce angiogenesis, osteogenesis, and remodeling of the structural allografts. We present data from pilot studies to show the utility of dynamic contrast enhanced MRI (DCE-MRI) to quantify vascularity after femoral osteotomy in a canine femur model and cone beam CT (CB-CT) to quantify bone volume in a patient after composite prosthetic-allograft reconstructive surgery. The results demonstrate our ability to suppress the artifacts generated by the metal implants required to secure massive allografts such that precise quantification of cortical bone revascularization (>10-fold increase at 3 weeks postoperatively) and new bone formation (accurate to about 193 μm³) around the graft can be performed longitudinally via DCE-MRI and CB-CT, respectively.

Introduction

Grafting of bone harvested from human cadavers (allograft) is commonly performed during orthopaedic reconstruction surgeries such as spinal fusion, revision of failed THA, or repair of skeletal defects resulting from the removal of tumor or from massive trauma [6, 13]. While the success of these techniques is largely due to the biocompatibility and biomechanical and osteoconductive properties of human bone, allografts suffer from their lack of angiogenic and osteogenic potential [14]. These deficiencies limit healing, which only occurs as a result of creeping substitution from the host. Clinicopathologic studies on retrieved allografts demonstrate healing is slow. Cortical-cortical union from internal cancellous-cancellous junctions is confined to only 20% of the superficial surface and the ends of the graft by 5 years [9, 10]. Furthermore, the necrotic bone provokes a foreign body reaction from the host that encases the allograft in a fibrous tissue that inhibits vascular ingrowth and remodeling [5, 26, 27]. As a result, these shortcomings are directly associated with 25% to 35% failure rate of massive allografts due to nonunion and fracture [3, 20]. Moreover, the 10-year survival rate of massive allografts is estimated to be between 40%–60% due to the accumulation of unremodeled microfractures, which decrease their torsional properties leading to catastrophic failure [21, 30, 31]. Adjuvants that can stimulate angiogenesis and bone formation around massive allografts might improve clinical outcomes of reconstructive surgery.

Three candidate approaches have emerged as potential osteogenic adjuvants for massive allografts. The first is incorporation of recombinant bone morphogenetic proteins (BMP) with intercalary allografts [22, 33], which is based on the remarkable success of combination BMP-2 and cancellous allograft for spinal fusion [4, 7], fracture healing [15, 17], and periodontal applications [12, 25]. The second is the addition of mesenchymal stem cell to the allograft to generate a pseudoperiosteum [28, 32, 34]. The third approach is a gene therapy designed to introduce the angiogenic, osteogenic, and remodeling signals in the local environment by freeze-drying recombinant adeno-associated viruses (rAAV) onto the cortical surface of the allograft [16, 18].

While the preclinical data with these “revascularizing,” “osteogenic,” and “remodeling” massive allografts are promising, current methods of assessment of revitalization are largely limited to histology but these do not allow longitudinal assessment. Standard two-dimensional (2D) radiographs and bone scans are not sufficiently quantitative in longitudinal studies [19], and three-dimensional (3D) MRI and CT images contain metal artifacts due to the extensive amount of hardware required to secure massive allografts [11, 23].

To address this limitation, we asked the following questions: (1) Is dynamic contrast enhanced MRI (DCE-MRI) a feasible outcome measure of intramedullar vascularity at the osteotomy? (2) Is cone beam CT (CB-CT) with iodine contrast a feasible outcome measure of intramedullar vascularity and bridging bone volume of structural allografts in patients?

Materials and Methods

The overall study design involved DCE-MRI of a dog immediately postoperative, 3 weeks and 6 weeks after a mid-diaphyseal osteotomy of the femur, which was compared to the results of CB-CT scans obtained at 2 weeks and 6 months postoperatively from a tumor patient who received a composite allograft to reconstruct his proximal tibia.

One skeletally mature Walker Hound (25 kg) underwent a transverse osteotomy of the right femoral diaphysis and repair with a titanium dynamic compression plate and screws. All procedures were performed in accordance with NIH guidelines for animal use and were approved by the institutional IACUC. Before surgery, a fentanyl transdermal patch was applied and the dog was premedicated with acepromazine and oxymorphone and induced using intravenous thiopental. Anesthesia was maintained using isoflurane in 100% oxygen. The fur was clipped circumferentially from tarsus to dorsal and ventral midline. A surgical scrub using alternating chlorhexidine and alcohol 360° around the limb using a hanging limb technique was used to prepare the limb for aseptic surgery. The dog received cefazolin (4.5 mg/kg body weight) immediately before surgery and every 90 minutes throughout the surgical procedure. Sterile drapes were used to cover the limb in standard four-quadrant fashion. A betadine-impregnated adhesive drape was used to cover the skin and a large fenestrated over-drape placed before beginning surgery. A 12-cm incision extending from the greater trochanter to the patella was performed along the craniolateral aspect of the femur. The fascia lata was incised along the cranial border of the biceps femoris. Caudal retraction of the biceps and cranial retraction of the vastus lateralis muscles were performed to allow access to the diaphysis of the femur. Using a saline-cooled oscillating CO₂ driven saw, an osteotomy was performed of the femur at mid-diaphysis. The femur was stabilized using a 12-hole titanium 3.5 DCP (Synthes Inc, West Chester, PA, USA) and screws using AO technique. The surgical site was lavaged with warmed physiologic saline. The soft tissues and skin were closed in three layers using monofilament absorbable suture for the muscles, fascia, and subcutaneous layers and nylon suture for the skin. Immediate postoperative planar radiographs were obtained to confirm correct hardware placement and allograft or autograft congruency. Before anesthetic recovery, the immediate postoperative DCE-MRI scan was performed. DCE-MRI was repeated at 3 weeks postoperatively and at 6 weeks postoperatively. Postoperative analgesia was achieved using a combination of the fentanyl patch placed before surgery and adjunctive oral morphine at a dose of 1 to 2 mg/kg orally every 8 hours as needed. The dog recovered uneventfully and was weightbearing on the second postoperative day. Sutures were removed 10 days after surgery.

DCE-MRI was performed at the described intervals with the dog under general anesthesia and positioned in lateral recumbency, using a 1.5-T GE LX Signa instrument (GE Health Care, Princeton, NJ, USA). After routine anatomic imaging of the hind limbs, DCE-MRI was performed by intravenous injection of 0.1 mmol/kg gadolinium Diethylene triamine pentaacetic acid (DTPA) (Magnevist^®; Berlex, Princeton NJ, USA) using a power injector at 3 mL/second, followed by twice the volume of normal physiologic saline. The femur was imaged during DCE-MRI in the coronal plane using a fast spoiled gradient echo (FSPGR) pulse sequence (TR minimum, TE 1.6 ms), 30° flip angle, and 8-mm slice thickness. Four slices through the femur and orthopaedic appliance were repeatedly scanned for a total of 40 phases before, during, and after contrast injection (with five having been acquired before contrast injection) with a temporal resolution of 12 seconds.

Analysis of DCE-MRI was compartmental-based, performed by region-of-interest (ROI) analysis of the bone marrow surrounding the osteotomy site by manual selection of the approximate contour of the osteotomy site and then allowing the 3D geometrical shape of the bone shaft at the osteotomy to be defined by an automated 3D geometrically constrained region growth drawing mode (Perfusion Analyzer; VirtualScopics Inc, Rochester NY, USA) [1]. The largest regional artery was also identified manually by viewing the temporal image series and finding an appropriately enhancing vessel pattern. An ROI placed in that artery was used by the software program to guide the derivation of an automated arterial input function. The volume transfer rate constant between arterial plasma and extracellular extravascular space (Ktrans) was calculated as an indicator of flow and vascular permeability. Analysis was carried out using the difference in signal intensity from baseline rather than using estimated gadolinium concentration values. The relationship between signal intensity change and gadolinium concentration over the range of concentrations that are biologically plausible in muscle or bone marrow with a 0.1-mmol/kg injection is largely linear and independent of baseline T1 using this acquisition protocol. It has been demonstrated under these circumstances analysis based on signal intensity delta is equivalent to that based on gadolinium concentration changes [29].

An initial study to evaluate the sensitivity and accuracy of the CB-CT with artifact suppression was performed on a 22-kg canine cadaver, which received a saline perfusion shortly after euthanasia, followed by an infusion of iodinated contrast (Omnipaque™ 240 mg I/mL; GE Health Care, Princeton, NJ , USA) into its femoral artery through gravity assist. Afterward, a titanium compression plate with screws (Synthes Inc) was implanted into the diaphysis of its left femur. The cadaver was then scanned three times at different positions in the CB-CT, and the primary data were manipulated to subtract the metal artifacts and reconstruct the ROI, which is the bone tissue directly under the plate. These data (CB-CT1) were then used to quantify the cortical bone and vascular volume (mm³)/graft length (72.3 mm) and were calculated as the mean ± standard deviation. The plate and screws were then removed, the cadaver was rescanned in the CB-CT three times, and the data were processed by automated analyses without manual manipulation. These data were then used to identify the bone and iodine contrast and the quantified volume/graft length are presented as (CB-CT2) for each. To validate the CB-CT bone volume measurements, we scanned the femur without the implant in a micro-CT research scanner at a resolution of 35 μm (Scanco VivaCT 40; Scanco Medical AG, Bassersdorf, Switzerland).

CB-CT scans of a composite allograft in the proximal tibia of a patient after reconstructive surgery to remove a parosteal osteosarcoma, with multifocal intraarticular involvement of the knee, were performed after informed consent under the University of Rochester Research Subjects Review Board approved protocol #15198. The allograft/prosthetic composite reconstruction consisted of a titanium modular rotating hinge component (Biomet Inc, Warsaw, IN, USA) with a 17-cm distal femoral component with a 150-mm porous-coated stem, which was combined with an 83-mm-wide by 80-mm-long modular tibial component with an attached 150-mm × 10-mm-diameter titanium distal intramedullary stem. The tibial component was cemented into a 6-cm-long proximal tibial allograft (Musculoskeletal Transplant Foundation, Edison, NJ, USA), which was attached to the host tibia with a stainless steel four-hole, large-fragment dynamic compression plate using four 4.5-mm-diameter unicortical stainless steel screws (Synthes Inc).

The subject was scanned before and after a bolus of contrast (Omnipaque™ 300 mg I/mL, 120 mL), which was intravenously hand injected over about 30 seconds. The delay before the start of the postcontrast CB-CT scan was 3 minutes. The experimental CB-CT used consisted of a modified GE HighSpeed Advantage spiral CT system (GE Medical Systems, Milwaukee, WI, USA), a PaxScan 4030CB (Varian Medical Systems, Salt Lake City, UT, USA) flat panel detector, an onboard 64-kW high-frequency generator (SHF635ROCH-480VAC; Sedecal USA, Arlington Heights, IL, USA), an xray tube (G1593BI; Varian Medical Systems), and a full-field collimator (302A; Ralco, Biassono, Italy). Two computers are required to operate the CB-CT: (1) an onboard computer (Industrial computer, Pentium 4, 2.4 GHz, 2 GB RAM; UMA Computers, Nashua, NH, USA) mounted on the rotating gantry, which is preprogrammed for data acquisition control and temporarily stored the cone beam projection data; and (2) an operator’s console computer (Dell Dimension 9150, Pentium D, 2.8 GHz, 2 GB RAM; Windows X OS) that remotely performs prescan data acquisition setup tasks. Trigger commands, gantry rotation motor control, and monitoring of the gantry angle position encoder during xray pulsing were accomplished through an I/O board (daqBoard 2000; IOtech, Cleveland, OH, USA). The system typically acquires approximately 300 projection images at 30 fps for about 10 seconds to produce a full-volume reconstruction with true isotropic resolution (approximately (83–193 μm)³) depending on the focal spot and detector binning used. To be conservative, we used a voxel size of (244 μm)³ for 3D reconstruction. These volume renderings and segmentation were produced with Amira^® 4.1 3D visualization software (Mercury Computer Systems, Inc-TGS, San Diego, CA). Phantom studies using proven cone beam reconstruction algorithms were used to validate full system performance of the acquisition protocols.

Results

DCE-MRI seemed a feasible approach to longitudinally quantify revascularization at the osteotomy as evidenced by detection of a greater than 10-fold increase in signal intensity. The MR images of the plated femur and the ROIs in the bone marrow surrounding the osteotomy and muscle were subsequently studied by DCE-MRI (Fig. 1). By quantifying the signal intensity data from the DCE-MRI for each tissue we observed an absence of increased signal intensity in the bone marrow after delivery of the intravenous contrast in the postoperative scans versus the dramatic enhancement of the adjacent muscle (Fig. 2A). However, this region of bone marrow demonstrates increasing enhancement after intravenous contrast over time (Fig. 2B–C), demonstrating our ability to quantify revascularization of the cortical bone longitudinally, as these dynamic results cannot be explained by diffusion into avascular tissue. The use of an automated 3D Constrained Region Growth drawing mode leads to smoother contour boundaries and limits growth outside of a structure of interest based on pixels’ mathematical characteristics, thus lessening interobserver variation.

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Fig. 1 A MR image of the plated canine femoral osteotomy demonstrates the ROIs for DCE-MRI. A T1-weighted postcontrast coronal MR image of the plated canine femoral osteotomy obtained at baseline is shown and is representative of the MRI at 3- and 6-week postoperative scans. The red circle in the bone marrow at the osteotomy and the blue circle in the adjacent muscle indicate the ROIs examined by DCE-MRI and correspond to the graphs depicted in Fig. 2.

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Fig. 2A–C Longitudinal DCE-MRI of a plated canine femoral osteotomy demonstrates revascularization over time. The graphs show the increase in T1 signal intensity (SI) of bone marrow and muscle through time during and after intravenous contrast injection from the DCE-MRI taken of the ROIs described in Fig. 1. Arrows indicated the delivery of the intravenous contrast. Of note is the lack of enhancement in signal intensity of the bone marrow ROI (red) after intravenous contrast at (A) baseline versus the marked increase seen at (B) 3 weeks postoperatively and (C) 6 weeks postoperatively. Compare to the relatively consistent increase in signal intensity of muscle ROI (blue) at all time points. Bone marrow Ktrans values (min⁻¹) were 0.0034, 0.0405, and 0.0425, respectively, for the three time points.

CB-CT seemed a feasible approach to longitudinally quantify bone volume (accurate to approximately 193 μm³) of structural allografts in patients, but considerable improvements in iodine contrast imaging would be needed to assess intramedullar vascularity. The resolution of the CB-CT was demonstrated by comparing the volumetric data with that obtained via a validated micro-CT (Fig. 3A–E). Quantification of the vascular and bone volume from serial CB-CT scans of the femur with and without the titanium plate and screws demonstrated similar results of the technique and the lack of image distortion caused by our metal artifact suppression (Table 1). Moreover, the bone volumes were similar to that obtained by the micro-CT. Radiographs and CB-CT of the patient who had a composite allograft with plates, screws, and a total knee prosthesis after removal of an osteosarcoma in his proximal tibial were obtained at 2-weeks and 8-months postoperative (Fig. 4A–F). As expected, there were no remarkable differences between the radiographs, and the radiolucent gap between the allograft and host tibia appeared similar in size at the two time points. However, after artifact suppression of the CB-CT data, we were able to generate high-resolution 3D reconstructed images of the bone and metal implants that clearly demonstrated new bridging bone callus at 8 months (Fig. 4F). Furthermore, these images could be segmented for volumetric quantification of the allograft, host bone, and implants, which demonstrated a −5.4%, +4.5% and +0.6% change respectively. Our interpretation of these results is the decrease in allograft volume is due to increased porosity, the increase in host tibia volume is due to new callus formation, and the small change in implant volume represents the experimental error of our methods. Unfortunately, the postcontrast CB-CT was not remarkably different from the precontrast scan. Thus, we were unable to perform quantification of the vascular volume.

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Fig. 3A–E Quantitation of cortical bone and vascular volume via CB-CT with micro-CT validation. The left femur of a canine cadaver was infused with iodine contrast and subjected to three CB-CT scans. (A) The primary data were manipulated to subtract the metal artifacts and reconstruct the ROI, which is the bone tissue directly under the plate. These data (CB-CT1) were then used to quantify the cortical bone and vascular volume (mm³)/graft length (72.3 mm) and are presented as the mean ± standard deviation in Table 1. (B) The plate and screws were then removed, and the cadaver was rescanned three times, and the data were processed by automated analyses without manual manipulation. These data were then used to identify the (C) bone and (D) iodine contrast and the quantified volume/graft length are presented as CB-CT2 for each in Table 1. To validate the CB-CT bone volume measurements, we scanned the femur without the implant in a Scanco micro-CT 40, which is validated to 35-μm resolution. (E) A reconstructed 3D image of the femur from the micro-CT scan is shown to demonstrate the gross similarity to the CB-CT reconstructed image in (C). Unfortunately, the iodine contrast could not be preserved to validate the vascular volume. These results demonstrated all CB-CT measurements have a reproducibility error of less than 1.5% and an accuracy error of less than 2.6% versus micro-CT.

Table 1 Reproducibility and validation of CB-CT volumetric measurements

Tissue	1st CB-CT volume	2nd CB-CT volume	Micro-CT volume
Bone	91.71 ± 0.71	91.90 ± 1.28	94.04
Vasculature	22.04 ± 1.29	22.90 ± 0.65	N.D.

Volumes are presented as (mm³)/graft length (72.3 mm). N.D. = (no data).

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Fig. 4A–F CB-CT volumetric segmentation of a tibial composite allograft in a patient two weeks and eight months after reconstructive surgery. Radiology of the patient’s composite allograft obtained at 2 weeks (A–C) and 8 months (D–F) postoperative are shown. Standard radiographs (A, D), 2D CB-CT slices (B, E) and reconstructed 3D images of the patient’s composite allograft are shown with anteroposterior views. Of note is the lack of remarkable findings in the radiographs including a similar gap at the allograft-host junction, versus the radiographic evidence of bony union (E) and the bridging bone callus (F). These CB-CT data were also used for volumetric segmentation, which demonstrated a −5.4% change in allograft bone volume (blue: 98932.6 mm³ vs. 34367.0 mm³), a +4.5% change in tibia bone volume (green: 30139.8 mm³ vs. 23554.0 mm³), while the volume of the, compression plate and screws was unchanged (yellow: 5347.0 mm³vs. 5379.0 mm³).

Discussion

Management of critical defects in long bones remains a serious challenge to the orthopaedic surgeon. While this problem has traditionally focused on patients recovering from tumor surgery, the remarkably high incidence of orthopaedic trauma in war wounds has now forced the military to find answers for critical defects [8]. While considerable preclinical advances have been made toward tissue engineering solutions to this problem [2], including new algorithms that can assess the biomechanical properties of allograft healing from noninvasive radiology [24], exploration of this technology could be enhanced by techniques to image revascularization of the healing bone juxtaposed to an array of steel, cobalt-chrome, and titanium implants in these massive allograft patients. We therefore asked: (1) Is dynamic contrast enhanced MRI (DCE-MRI) a feasible outcome measure of intramedullar vascularity at the osteotomy? (2) Is cone beam CT (CB-CT) with iodine contrast a feasible outcome measure of intramedullar vascularity and bridging bone volume of structural allografts in patients?

Due to the limited number of subjects in our pilot studies we cannot make general conclusions about DCE-MRI and CBCT. However, our results suggest neither approach is currently able to quantify both parameters of vascularity and bone volume simultaneously. The advantage of DCE-MRI to quantify bone marrow vascularity over time is scans are taken with rapid temporal resolution (ideally less than every 12 seconds), so the rate of increase and the peak signal intensity after delivery of intravenous contrast is easily obtained (Fig. 2A–C). The pulse sequence used for DCE-MRI is specifically designed to provide T1 weighted imaging so as to measure rapid changes in signal intensity during onset of contrast enhancement of a tissue region. DCE-MRI is used most often in clinical situations to assess the rate and intensity of contrast enhancement as a method of evaluating tumor vascularity and/or angiogenesis. Its use in this situation (osteotomy healing) is relatively novel, but the same principles should apply. Multiple other T1 and T2 weighted MRI pulse sequences can be used for assessing bone healing and bone marrow characteristics, depending upon the specific situation. These are usually combined with a fat-suppressed or fat saturation technique to subdue the relatively higher signal intensity from bone marrow fat in order to optimize visualization of the signal intensity from vascular tissue and red or cellular bone marrow. Our study is also limited by assessing only primary bone healing rather than allograft healing.

One limitation of CB-CT is a single scan is taken following delivery of the intravenous contrast. In our case, we chose a 3-minute delay to allow perfusion of the bone. Thus, our failure to detect remarkable contrast enhancement could have been due to poor timing, and it may be that bolus track studies of each patient may be needed to empirically determine the appropriate delay time. Conversely, CB-CT was vastly superior to 1.5-T MRI for volumetric quantification of the allograft. This is largely due to the artifact suppression via thresholding and segmentation based on great differences in bone-implant density. Moreover, the improvements in the scanner now permit true isotropic resolution (approximately 83–193 μm³) depending on the focal spot and detector binning used. Considering this is well within the range of resolution needed to detect new bone formation around a healing massive allograft (Fig. 4F), a larger clinical pilot is warranted to see if this approach would be useful to assess the efficacy of a tissue-engineered “revitalizing” allograft.

In summary, we find DCE-MRI a feasible approach to quantitatively assess the revascularization of cortical bone following osteotomy. Conversely, CB-CT is a feasible approach to quantitatively assess massive allograft bone volume adjacent to metal implants, but i.v. contrast enhancement cannot be used to quantify vascularity with this approach. A larger prospective study to assess the value of these methods to quantify allograft healing is warranted.

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Symposium: New Approaches to Allograft Transplantation

References