Patient-Specific Planning Literature Roundup

Posted on 20 May 2024 by Kerim Genc


Accurate patient-specific planning using 3D models provides opportunities to reduce time, improve anatomical understanding, and virtually test different techniques before procedures. Simpleware software provides a comprehensive range of tools for processing MRI and CT image data, and exporting models to 3D printing, design, and simulation workflows. Our customers are conducting diverse research and clinical projects using Simpleware software, as highlighted in our previous roundup in 2023. Since then, we have seen even more exciting applications with Simpleware, coming at a time when our recent MDR certification ensures that our software can be used to achieve clinical benefits for users and patients.

The Feasibility of a Novel 3D-Printed Patient specific Cutting Guide for Extended Trochanteric Osteotomies

Bergemann, R., Roytman, G.R., Ani, L., Ramji, A.F., Leslie, M.P., Tommasini, S.M., Wiznia, D.H., 2024. The feasibility of a novel 3D-Printed patient specific cutting guide for extended trochanteric osteotomies. 3D Printing in Medicine, 10(7).

Virtual modeling of surgical guide and femur using Simpleware (CC BY 4.0)

Virtual modeling of surgical guide and cadaveric femur. a. Low-resolution model of femur (grey) and cutting guide (green) as designed in Solidworks. b. Segmented femur (white) with finalized cutting guide (green), cutting planes (red) and K-wires (grey) as modeled in ScanIP (Image by Bergemann et al. / CC BY 4.0 / Resized from original).


"The extended trochanteric osteotomy (ETO) is a surgical technique utilized to expose the intramedullary canal of the proximal femur, protect the soft tissues and promote reliable healing. However, imprecise execution of the osteotomy can lead to fracture, soft tissue injury, non-union, and unnecessary morbidity. We developed a technique to create patient specific, 3D-printed cutting guides to aid in accurate positioning of the ETO and improve osteotomy quality and outcomes.

Patient specific cutting guides were created based on CT scans using Synopsys Simpleware ScanIP and Solidworks. Custom 3D printed cutting guides were tested on synthetic femurs with foam cortical shells and on cadaveric femurs. To confirm accuracy of the osteotomies, dimensions of the performed osteotomies were compared to the virtually planned osteotomies.

Use of the patient specific ETO cutting guides resulted in successful osteotomies, exposing the femoral canal and the femoral stem both in synthetic sawbone and cadaveric testing. In cadaveric testing, the guides allowed for osteotomies without fracture and cuts made using the guide were accurate within 6 percent error from the virtually planned osteotomy.

The 3D-printed patient specific cutting guides used to aid in ETOs proved to be accurate. Through the iterative development of cutting guides, we found that a simple design was key to a reliable and accurate guide. While future clinical trials in human subjects are needed, we believe our custom 3D printed cutting guide design to be effective at aiding in performing ETOs for revision total hip arthroplasty surgeries."

Use of Simpleware Software

"Using Synopsys Simpleware ScanIP (Version T-2022.03-SP2, 2022, Mountain View, CA, USA) image processing software to segment CT scans, 3D models of the femur were generated. For cadavers with total hips implanted, 3D models of the implants were generated as well. The osteotomies were modeled as 1.2 mm planes to account for the width of the sawblade and planned and positioned in consultation with adult reconstruction orthopaedic surgeons with more than five years of post-fellowship experience. Virtual models of the femur and osteotomies were then imported as reference geometry into Dassault Systèmes SolidWorks (Version 2021–2022, Vélizy, France) and used to design the surgical guide (Fig. 2). Once a 3D model of the cutting guide was generated, the model was brought into ScanIP once more for the final planning. In ScanIP, 1.6 mm Kirshner wires (K-wires), modeled as simple cylinders, were placed to aid in fixing the cutting guide to the femur. The topology of the femur and the K-wire was subtracted from the surgical guide model, so that the guide would fit tightly onto the surface of the femur. The topology of the femur and the K-wire was subtracted from the surgical guide model, so that the guide would fit tightly onto the surface of the femur. The overall geometry of the surgical guide was developed to respect the soft tissue as much as possible and was designed to conform primarily to the exposed bone on the posterior surface, requiring minimal stripping of vastus lateralis soft tissue from the bone and protecting the gluteus medius insertion."

"Prior to 3D printing, the finalized design was reviewed by an orthopaedic surgeon in ScanIP. ScanIP enabled the surgeon to view the surgical guide, osteotomy locations and the femur and femoral stem in three dimensions. The final model of the cutting guide was printed on a FormLabs Form 3BL stereolithography SLA 3D printer."

"There were several design iterations that led to continuous improvement of the cutting guide. For the first iteration of the design, the 3D model of the cutting guide was evaluated in ScanIP and was determined to likely interfere with the soft tissue not visible on the CT scan. A soft tissue sparing second iteration was created, though upon 3D printing of the guide, it was found to be too bulky and too flexible, and thus would not function accurately."

"All testing was performed by an orthopaedic surgeon five years post fellowship training. The first two iterations were qualitatively evaluated in ScanIP to evaluate any potential issues. The third iteration surgical guide was tested on a synthetic femur sawbone model with foam cortical shell."

"Finally, the osteotomy was measured for comparison to the planned procedure, and error was calculated based on measurements made in ScanIP."

Outcomes and Impact

"The final 3D printed custom ETO cutting guide design was accurate in guiding the osteotomy within a few millimeters of error compared to the virtual planned osteotomy. In our iteration through multiple designs, we discovered the importance of simplicity for a robust and precise cutting guide. While further testing in clinical trials is needed, this study illustrates the potential of patient specific 3D-printed cutting guides to improve ETOs and their outcomes."

Accuracy of 3D Printed Spine Models for Pre-Surgical Planning of Complex Adolescent Idiopathic Scoliosis (AIS) in Spinal Surgeries: A Case Series

Dutta, A., Singh, M., Kumar, K., Navarro, A.D., Santiago, R., Kaul, R.P., Patil, S., Kalaskar, D.M., 2023. Bahl, J. S., Arnold, J. B., Saxby, D. J., Taylor, M., Solomon, L. B., Thewlis, D., 2023. Accuracy of 3D printed spine models for pre-surgical planning of complex adolescent idiopathic scoliosis (AIS) in spinal surgeries: a case series. Annals of 3D Printed Medicine, 11, 100117.

Superimposition and surface deviation analysis using Simpleware (CC BY 4.0)

Superimposition and surface deviation analysis using Simpleware ScanIP: (A) CT-scan of 3D printed spinal models with region of deformity of interest, (B) six corresponding landmark placements on the patient ‘ground-truth’(red) and model (green) virtual 3D reconstructions (C) axial view of superimposed images (D) final superimposition of 3D reconstructions (Image by Dutta et al. / CC BY 4.0 / Resized from original).


"Adolescent idiopathic scoliosis (AIS) is a noticeable spinal deformity in both adult and adolescent population. In majority of the cases, the gold standard of treatment is surgical intervention. Technological advancements in medical imaging and 3D printing have revolutionised the surgical planning and intraoperative decision making for surgeons in spinal surgery. However, its applicability for planning complex spinal surgeries is poorly documented with human subjects. The objective of this study is to evaluate the accuracy of 3D printed models for complex spinal deformities based on Cobb angles between 40° to 95°.This is a retrospective cohort study where, five CT scans of the patients with AIS were segmented and 3D printed for evaluating the accuracy. Consideration was given to the Inter-patient and acquisition apparatus variability of the CT-scan dataset to understand the effect on trueness and accuracy of the developed CAD models. The developed anatomical models were re-scanned for analysing quantitative surface deviation to assess the accuracy of 3D printed spinal models. Results show that the average of the root mean square error (RMSE) between the 3DP models and virtual models developed using CT scan of mean surface deviations for the five 3d printed models was found to be 0.5±0.07 mm. Based on the RMSE, it can be concluded that 3D printing based workflow is accurate enough to be used for presurgical planning for complex adolescent spinal deformities. Image acquisition and post processing parameters, type of 3D printing technology plays key role in acquiring required accuracy for surgical applications."

Use of Simpleware Software

"The 3D solid models of the patient's scoliotic spines were obtained using an image analysis software package from Simpleware ScanIP (Synopsys, Inc., UK). The process comprised of the following steps: segmentation of the CT-scan images based on Hounsfield Units (HU) of cortical bone (HU 100-2000), mask development, smoothing of the contours of each slice using manual segmentation, and preparing a solid model of the spine from the masks. The segmentation and surface mesh quality were checked for irregularities, holes and overlapping edges. The segmentation of each spine data formed the ground-truth (models developed from the patients CT scan data) comparison for the corresponding 3D printed model segmentation, which was used to evaluate the accuracy of the 3D printing workflow. The methodology from data acquisition to generation of 3D printed model is described in Fig. 1. The created 3D surface model from patient CT-Scan was then exported for 3D printing in STL file format for 3D printing of the spinal models."

"Image acquisition and segmentation form the backbone in determining the accuracy of printed models. Image acquisition needs to be performed by software for medical purposes. This study used commercially available Simpleware ScanIP (Synopsys Inc., UK). Auto segmentation is helpful for most bone segmentation, but complex structures demand manual segmentation. Knowledge of human anatomy helps to understand anatomical structures to perform complex segmentation such as in AIS. Auto segmentation was checked manually for any inaccuracies and corrected, to ensure accuracy of segmentation process for complex spinal anatomies."

Outcomes and Impact

"This work critically examined the capabilities of patient specific 3D printed spinal models for complex scoliosis surgery with Cobb angle varying from 40 to 95°. The work demonstrated that FFF based 3D printing workflow could be adapted for presurgical planning of complex adolescent scoliotic patients. This provides clinically acceptable level of accuracy for surgical planning and screw placements practice within 0.5 mm accuracy, shows promise for this technology adoption for safer surgical planning for complex AIS. The benefits and drawbacks for both patients and staff and the long-term clinical efficacy and safety of using 3D printed models need to be further evaluated if we are to see more widespread uptake. This would require larger patient cohorts and long-term studies to investigate this expanding clinical field."

Optimising Total Knee Replacement Imaging: A Novel 3D Printed PET/CT Anthropomorphic Phantom for Metal Artefact Simulation

Segmented knee from MRI using Simpleware software (CC BY 4.0)

A Coronal, sagittal, and axial, view of knee MRI scan of one of the participants. b Segmented cortical and trabecular bone of knee joint MRI Images. c the exported 3D STL model of the segmented cortical, trabecular bone of the knee joint (Image by Assiri et al. / CC BY 4.0 / Resized from original).


"Arthroplasty phantoms, including total knee replacement (TKR) phantoms, have been frequently used to test metal artefact reduction methods applied to positron emission tomography/computed tomography (PET/CT) images. These phantoms generally simulate either simple anatomical features or simple activity distribution around the metal inserts in the PET/CT scans. 3D printing has been used recently to fabricate fillable anthropomorphic phantoms that accurately simulate volume and geometry. This study aims to describe the process of image segmentation, phantom modelling, 3D printing and validation of a population-based fillable TKR phantom that simulates human TKR PET/CT metal artefacts.

10 participants (5 male and 5 female) were scanned using 3T MRI and the images were segmented to create average male and average female 3D knee models, inversely with void cortical and porous trabecular compartments for 3D printing and contrast media. Virtual total knee replacement (TKR) surgery was implemented on these models to prepare the insertion locations for knee prosthetic implants. Subsequently, TKR models were printed using a 3D photopolymer resin printer and then injected with normal saline to test the phantoms for any leaks. Subsequently, diluted iodinated contrast media was injected into the cortical compartment and saline with 18F-FDG was injected into the trabecular compartment and the phantom was scanned with PET/CT. The images were then evaluated and compared to the human knee radiographic features reported in the literature.

Phantoms were shown to be fluid-tight with distinct compartments. They showed comparable volume and geometry to the segmented human MRI knees. The phantoms demonstrated similar values for x-ray attenuation and Hounsfield units (HU) to the literature for both cortical and trabecular compartments. The phantoms displayed a uniform distribution for the radioactive tracer, resembling that seen in human trabecular bone PET. TKR phantom PET/CT images with metal inserts replicated the clinical metal artefacts seen clinically in the periprosthetic area.

This novel, 3D-printed, and customisable phantom effectively mimics the geometric, radiographic and radiotracer distribution features of real TKRs. Importantly, it simulates TKR image metal artefacts, making it suitable for repeatable and comprehensive evaluation of various metal artefact reduction methods in future research."

Use of Simpleware Software

"The cortical and trabecular bones were segmented from the MRI DICOM images of the tibia and femur using ScanIP software (Synopsys Simpleware, Ver. 2020, Sunnyvale US) to create a 3D knee surface model consisting of cortical and trabecular compartments in every subject scan. A threshold for image pixel intensity values was used to segment each compartment automatically which was then edited manually to delete any pixels segmented outside of the compartments. The surface models were then exported into stereolithography STL file format."

"ScanIP and Geomagic Wrap were used for generating and editing the TKR model because as they were already available in the lab and the authors had prior knowledge of their use."

Outcomes and Impact

"In conclusion, this study shows the process of segmenting, modelling, printing, and validation of 3D-printed TKR phantoms that simulate the geometry, shape, and radiological features of human PET/CT TKR. This demonstrates that 3D printing is a valuable method in the fabrication of nuclear medicine and PET/CT phantoms that can be injected with a range of attenuating solutions and radiopharmaceuticals. Future work could focus on adding varying-sized lesion-like compartments within the trabecular bone compartment around the metal implant. This would allow for testing the performance of MAR methods in the detection of periprosthetic lesions."

Fabricating Patient-Specific 3D Printed Drill Guides to Treat Femoral Head Avascular Necrosis

Bell, C.E., Feizi, A., Roytman, G.R., Ramji. A.F., Tommasini, S.M., Wiznia, D.H., 2023. Fabricating patient-specific 3D printed drill guides to treat femoral head avascular necrosis. 3D Printing in Medicine, 10(10).

3D printed drill guide: comparing needle placement position (CC BY 4.0)

(A) 3D-printed guide fitted to a foam cortical shell femur is displayed. The femur was modeled using a dual-energy CT scan and the custom device was fitted using 3D modeling software. A Jamshidi needle, utilized subsequently for an AVN decompression device, was positioned using the modeled femur. A second dual-energy CT-scan was obtained after drilling the foam cortical shell femur with the Jamshidi needle. (B and C) The position of the Jamshidi needle after drilling was compared to the 3D-modeled position (Image by Bell et al. / CC BY 4.0 / Resized from original).


"Background: Femoral head avascular necrosis (AVN), or death of femoral head tissue due to a lack of blood supply, is a leading cause of total hip replacement for non-geriatric patients. Core decompression (CD) is an effective treatment to re-establish blood flow for patients with AVN. Techniques aimed at improving its efficacy are an area of active research. We propose the use of 3D printed drill guides to accurately guide therapeutic devices for CD.

Methods: Using femur sawbones, image processing software, and 3D modeling software, we created a custom-built device with pre-determined drill trajectories and tested the feasibility of the 3D printed drill guides for CD. A fellowship trained orthopedic surgeon used the drill guide to position an 8 ga, 230 mm long decompression device in the three synthetic femurs. CT scans were taken of the sawbones with the drill guide and decompression device. CT scans were processed in the 3D modeling software. Descriptive statistics measuring the angular and needle-tip deviation were compared to the original virtually planned model.

Results: Compared to the original 3D model, the trials had a mean displacement of 1.440±1.03 mm and a mean angle deviation of 1.093±0.749º.

Conclusions: The drill guides were demonstrated to accurately guide the decompression device along its predetermined drill trajectory. Accuracy was assessed by comparing values to literature-reported values and considered AVN lesion size. This study demonstrates the potential use of 3D printing technology to improve the efficacy of CD techniques."

Use of Simpleware Software

"A foam cortical shell femur (Model SKU 1103, Sawbones, Vashon, WA, USA) was scanned using a LightSpeed VCT GE Medical Systems CT Scanner with a slice thickness of 0.625 mm and 80 kVp. The CT scan was segmented using Synopsys Simpleware ScanIP software (Version 2022, Sunnyvale, CA, USA), creating a 3D femur model. To represent the necrotic lesion, a virtual lesion was positioned in the head of the 3D femur model, which was based on previously described lesions in the literature."

"The device was constructed in 3D modeling software, Simpleware ScanIP, by initially positioning a cylindrical geometry with dimensions of 30 mm in diameter by 30 mm in height near the vastus ridge."

"The foam femur CT scans were rendered as 3D model masks using ScanIP image processing software. The 3D model masks from the accuracy tests were individually overlaid on the original modeled femur with the ideal drill trajectory (Fig. 2). The ScanIP measurement tool was used to find the positional deviation and angular deviation between theoretical and experimental drill trajectories. Positional deviation was determined by measuring the difference in drill tip location between the ideal drill trajectory and the test drill trajectories. Angular deviation was determined by measuring the angle between the guidewire and the ideal drill trajectory from the cortical entry point. Descriptive statistics (mean and range) were collected for the angle deviation and needle tip deviation."

Outcomes and Impact

"Our 3D printed drill guide prototype was determined to be accurate and reliable. Using this technique in surgical practice can provide several advantages over conventional techniques such as reducing time and thereby infection risk in CD surgery as well as lowering the cost of surgery. Although the 3D printed drill guide has the potential to improve the accuracy of core decompression procedures, further research is needed to fully evaluate its effectiveness and feasibility in a surgical setting."

Experimental and Virtual Testing of Bone-implant Systems Equipped with the AO Fracture Monitor with Regard to Interfragmentary Movement

Wickert, K., Roland, M., Andres, A., Diebels, S., Ganse, B., Kerner, D., Frenzel, F., Tschernig, T., Ernst, M., Windolf, M., Muller, M., Pohlemann, T., Orth, M., 2024. Experimental and virtual testing of bone-implant systems equipped with the AO Fracture Monitor with regard to interfragmentary movement. Front. Bioeng. Biotechnol., 12.

Computational models of tibiae segmented in Simpleware software (CC BY 4.0)

(A–C) Illustration of the computational models of the three different treated tibiae. (D) Plot of the bone mineral density of the two specimens 21311 and 21391 with respect to the apparent density and the corresponding number of CT voxels (Image by Wickert et al. / CC BY 4.0 / Resized from original).


"The management of fractured bones is a key domain within orthopedic trauma surgery, with the prevention of delayed healing and non-unions forming a core challenge. This study evaluates the efficacy of the AO Fracture Monitor in conjunction with biomechanical simulations to better understand the local mechanics of fracture gaps, which is crucial for comprehending mechanotransduction, a key factor in bone healing. Through a series of experiments and corresponding simulations, the study tests four hypotheses to determine the relationship between physical measurements and the predictive power of biomechanical models.

Employing the AO Fracture Monitor and Digital Image Correlation techniques, the study demonstrates a significant correlation between the surface strain of implants and interfragmentary movements. This provides a foundation for utilizing one-dimensional AO Fracture Monitor measurements to predict three-dimensional fracture behavior, thereby linking mechanical loading with fracture gap dynamics. Moreover, the research establishes that finite element simulations of bone-implant systems can be effectively validated using experimental data, underpinning the accuracy of simulations in replicating physical behaviors.

The findings endorse the combined use of monitoring technologies and simulations to infer the local mechanical conditions at the fracture site, offering a potential leap in personalized therapy for bone healing. Clinically, this approach can enhance treatment outcomes by refining the assessment precision in trauma trials, fostering the early detection of healing disturbances, and guiding improvements in future implant design. Ultimately, this study paves the way for more sophisticated patient monitoring and tailored interventions, promising to elevate the standard of care in orthopedic trauma surgery."

Use of Simpleware Software

"The segmentation procedure as well as the following meshing strategy were performed in the image processing and model generation software Simpleware™ ScanIP (Synopsys, Mountain View, CA, United States)."

"After the material assignment, the areas close to the joints (foot and knee) were also marked in the ScanIP software during the meshing in order to be able to apply the boundary conditions correctly in the simulation environment and thus be able to represent the clamping in the testing device realistically in the simulations. Figures 2A–C shows the generated computational models of the three specimens."

Outcomes and Impact

"The present study confirmed a significant correlation between the surface strain data of the implant and the IFM as both were derived from the same experiments evaluated via DIC (hypothesis 1). It also established that the 1D measurements captured by the AO Fracture Monitor could predict the IFM measured by DIC, thus linking the implant loading to the behavior of the fracture gap (hypothesis 2). Additionally, the study showed that the simulation results could be reliably evaluated using the experimental DIC data for IFM, especially under partial weight bearing conditions (hypothesis 3). Finally, a strong connection was found between the AO Fracture Monitor’s signals and the simulated IFM, which enabled a transition from 1D to 3D understanding via the strain energy density within the bone-implant system, with linear regression models providing a strong predictive relationship (hypothesis 4). These results, in turn, may be used for clinical application analyses of the AO Fracture Monitor in translational studies.

Both the experiments performed and the simulations based on them are subject to various limitations and few simplifications made. One simplification that had to be made is the use of knee forces from the Orthoload database. These represent the data of the selected patient (k8l) and are only a simplifying assumption as knee forces for the bone donors. In addition, the body weight of the donors was not known, so the body weight of the patient selected from the Orthoload database was adopted here as a simplification. In retrospect, this might have been chosen too high for sample 21391 and could be the reason for the failure of the osteoporotic bone under high weight bearing conditions. Another difficulty that always arises in this type of experiment is the clamping of the specimens. Since bones as a biological and a natural grown structure have a relatively complex geometry compared to standard industrial specimens, a good clamping and alignment of the specimens is challenging. This potentially leads to minor errors in both axial alignment (z-axis) and in maintaining the x- and y-axes of the clamped bones. The corresponding bone areas are marked in the simulation and the boundary conditions are set there in analogy to the real test execution. Inaccuracies may occur due to the possible slightly offset of the angles caused by the alignment of the specimens and the perfectly aligned simulation models.

Another limitation is the load input to the bone-implant system from the clamping itself and the associated machine setup that occurs as a type of preload or bias and is reflected in the AO Fracture Monitor data because the AO Fracture Monitor cannot technically perform a calibration step after the specimens are installed. The manual calibration step of the AO Fracture Monitor was always done before the start of the particular testing protocols after the installation of the specimens and the alignment and calibration of the camera system. If it were technically possible to combine the calibration step of the AO Fracture Monitor and its data acquisition with the triggering of the testing device, the significance of the data and its subsequent use could be increased even further.

Within the evaluation of the DIC and the software used for this purpose, averaging processes take place that cannot be fully represented in the simulation evaluation. The goal to compare the results of the simulations with the results of the experiments as good as possible can be influenced by using analysis software and the processes running in it. The biomechanical FE simulations were limited to only one step and do not represent all eight steps used as input data in the testing device. This restriction was made because the amount of data for one step in the output database (ODB) files from Abaqus is already up to 100 Gigabyte, making the evaluation time and memory intensive. When simulating the entire input data, the ODB files then reach a size of 800 Gigabyte per specimen and load case, which exceeds the available computer capacity for the evaluation process.

We are aware that the conclusions are drawn from only a small number of experiments, and more experiments from a larger number of donors will have to be provided to further analyze and strengthen the results and associations. Nevertheless, the outcomes of this study suggest that patient-specific simulations in conjunction with the AO Fracture Monitor measurements provide a viable method for assessing the local mechanics within a fracture gap, which is pivotal for understanding mechanotransduction. This methodology can enrich clinical outcomes by enabling personalized healing strategies, refining prognostic accuracy in trauma trials, and offering a sophisticated approach for early detection and intervention in cases of healing complications. Moreover, it has the potential to guide the enhancement of the design of trauma implants, thus improving overall patient care in orthopedic trauma surgery."

The Geometric Evolution of Aortic Dissections: Predicting Surgical Success Using Fluctuations in Integrated Gaussian Curvature

Khabaz, J., Yuan, K., Pugar, J., Jiang, D., Sankary, S., Dhara, S., Kim, J., Kang, J., Nguyen, N., Cao, K., Washburn, N., Bohr, N., Jun Lee, C., Kindlmann, G., Milner, R., Pocivavsek, L., 2024. The geometric evolution of aortic dissections: Predicting surgical success using fluctuations in integrated Gaussian curvature. PLOS Computational Biology, 20(2): e1011815.

Aorta segmentation from CTA imaging using Simpleware software (CC BY 4.0)

Aortas are segmented from CTA imaging scans of the chest, followed by smoothing of the segmentation, isolation of the segmentation outer surface, and triangular surface meshing. The noise reduction procedure encompasses the smoothing and meshing steps, in which multiple smoothing parameters and mesh density variations generate multiple plausible surface meshes representing the segmentation (Image by Khabaz et al. / CC BY 4.0 / Resized from original).


"Clinical imaging modalities are a mainstay of modern disease management, but the full utilization of imaging-based data remains elusive. Aortic disease is defined by anatomic scalars quantifying aortic size, even though aortic disease progression initiates complex shape changes. We present an imaging-based geometric descriptor, inspired by fundamental ideas from topology and soft-matter physics that captures dynamic shape evolution. The aorta is reduced to a two-dimensional mathematical surface in space whose geometry is fully characterized by the local principal curvatures. Disease causes deviation from the smooth bent cylindrical shape of normal aortas, leading to a family of highly heterogeneous surfaces of varying shapes and sizes. To deconvolute changes in shape from size, the shape is characterized using integrated Gaussian curvature or total curvature. The fluctuation in total curvature (δK) across aortic surfaces captures heterogeneous morphologic evolution by characterizing local shape changes. We discover that aortic morphology evolves with a power-law defined behavior with rapidly increasing δK forming the hallmark of aortic disease. Divergent δK is seen for highly diseased aortas indicative of impending topologic catastrophe or aortic rupture. We also show that aortic size (surface area or enclosed aortic volume) scales as a generalized cylinder for all shapes. Classification accuracy for predicting aortic disease state (normal, diseased with successful surgery, and diseased with failed surgical outcomes) is 92.8±1.7%. The analysis of δK can be applied on any three-dimensional geometric structure and thus may be extended to other clinical problems of characterizing disease through captured anatomic changes."

Use of Simpleware Software

"Three-dimensional aortic models are created from CTA image data using a custom workflow in Simpleware ScanIP (S-2021.06-SP1, Synopsys, Mountain View, CA). Aortic geometry is extracted from scans using a five-step algorithm which includes 1. segmentation, 2. noise reduction, 3. smoothing, 4. isolation of the segmentation outer surface, and 5. surface meshing. A representative schematic of the process is shown in Fig 2, and more information on the process can be found in SI Aortic Segmentation and Post-Processing from CTA Imaging. A triangular mesh for the outer surface is generated for each smoothed segmentation in ScanIP for analysis in Matlab (2021b, Mathworks, Natick, MA). A total of 15 meshed surfaces are generated for each segmentation (sampling 5 mesh densities and 3 smoothing variations), allowing for control of process-derived variance in surface curvature calculations."

Outcomes and Impact

"Type B aortic dissection (TBAD) is a life-threatening disease with significant associated morbidity and mortality [17, 19, 20]. While the old paradigm of open surgical repair was fraught with peri-operative risk, new minimally invasive approaches like TEVAR often trade a decrease in initial operative risk for a higher risk of long-term repair failure. Proper identification of patients for TEVAR is therefore critical and necessitates the definition of an appropriate classification scheme [17, 22, 66, 67]. While previous work has focused on linking changes in aortic anatomy and suitability for repair, there remains a dire need to improve our understanding of how best to define geometric changes and to understand their impact on patient outcomes.

Projection of aortic anatomy into the (δK, ℓ−1)-space provides an improved ability to differentiate aortas along the entire spectrum of growth and pathology, including both normal size-related development and pathologic shape-related changes that occur secondary to aortic dissection. We demonstrate that in normal conditions, the aorta undergoes shape-invariant growth (see Fig 7), while, in diseased states, the aorta experiences shape fluctuations defined by increasing δK. As shown in Fig 10, δK significantly outperforms all other available measures of shape in predicting clinical treatment outcomes, including tortuosity, which is prevalent in the clinical arena.

Furthermore, because of the invariant global cylindrical geometry of the aorta, the parameterization of size is dependent only on the single length scale ℓ−1. Higher-dimensional characterizations of size, including area AT and volume V, do not provide additional information [68, 69]. Thus, current efforts to replace 2Rm with area or volume [68, 69] are unlikely to yield substantially more information (Figs 5 and 10). This universal size scaling provides the quantitative basis behind the utility of maximum diameter throughout the decades of aortic management and further validates the study of shape [67].

Fig 9 compares the efficacy of a single-variable space defined by maximum diameter (2Rm), the clinical standard, with an enhanced shape-size feature space for predicting treatment outcomes. Using size as the sole metric of disease change, the cornerstone of imaging-based practice in other clinical contexts, is inherently problematic because a critical point between closely-spaced and overlapping populations is very sensitive to the available data. For instance, a well-known problem in Rm-based criteria is the bias against smaller-statured female patients because of the heavily male-weighted population-based statistics [70, 71]. This is best illustrated by Fig 9. While arbitrarily defined size classifiers did discriminate amongst normal aortas, successful TEVAR, and failed TEVAR, such scalars lack physical meaning and clinical generalizability outside of the specific cohort being analyzed. This is partly due to natural population-level variation in aortic size in addition to the inherently operator-dependent nature of aortic size measurements (such as diameter) [30].

The addition of the second axis (δK) alleviates this issue by providing a quantifiable and reproducible shape scalar. δK also captures the global geometry of the aorta and is operator-independent. The combined -feature space demonstrates greater than 90% classification accuracy for the same three cohorts. The addition of a tangible shape axis also offers enhanced interpretability of the underlying geometric trends driving aortic pathology. Such a classification space can be clinically applied to pre-operative treatment planning for aortic dissection patients. δK outperforms previously described shape metrics in both the clinical and engineering literatures. Clinically-derived shape measures, such as the tortuosity index, are predominately acquired from aortic centerlines [21, 72]. These measures underperform compared to δK and are no better than ℓ−1 alone for characterizing aortic disease pathology from geometry. As such, future analysis of δK is liable to demonstrate substantial clinical application of δK as a clinical outcomes predictor.

No general theory exists on the meaning of δK divergence. In soft matter systems such as spherical vesicles, where size weakly changes, and in dynamic systems, rapid fluctuations of Gaussian curvature have been linked to so-called ‘topologic catastrophes’ indicative of physical instability [48, 49, 73]. While we do not inherently study aortic stability as it relates to clinical rupture, we show that aortas with high δK independently classify as high risk for clinical complications and poor outcomes post-TEVAR. It is therefore reasonable to conjecture that vertical divergence in the -space is a sign of aortic instability and an indicator of suboptimal suitability for endovascular repair.

The morphologic evolution of biological structures is tightly integrated with disease development in many other contexts. δK is a size-independent shape metric, and because it only requires extrinsic geometric information, this procedure can be applied to any surface mesh geometry. For instance, 3D imaging is extensively used to analyze lung nodules for malignancy [1], breast lesions for tumor growth [74], liver irregularities for cirrhosis [2], cerebral aneurysms [75], and the left ventricle for heart failure [76].

As with the aorta, size-based criteria form the mainstay of clinical approaches, while shape is qualitatively used but has been proven difficult to quantify until now. This methodology is based on a general geometric and topologic foundation, and future analysis will be needed to validate its extension to other clinically relevant problems of characterizing disease through analysis of shape change in medical imaging."

The Role of Bone Remodeling in Measuring Migration of Custom Implants for Large Acetabular Defects

De Angelis, S., Di Laura, A., Ramesh, A., Henckel, J., Hart, A., 2024. The role of bone remodeling in measuring migration of custom implants for large acetabular defects. Journal of Orthopaedic Research, 1-10.

Pelvis and cup registration in Simpleware software (CC BY 4.0)

(A) Immediate postoperative pelvis and cup. (B) 1-year follow-up pelvis and cup. (C) Change in implant position at 1-year follow-up after bone-to-bone registration of the ipsilateral innominate bone (Image by De Angelis et al. / CC BY 4.0 / Resized from original).


"In revision total hip arthroplasty, achieving robust fixation is difficult and implant movement may occur over time. Bone may also rearrange around the implant as a result of mechanical loading, making the measurement of migration challenging. The study aimed to quantify changes in bone shape and implant position 1 year following acetabular reconstruction using custom three-dimensional-printed cups. This observational retrospective cohort study involved 23 patients with Paprosky type IIIB defects. Postop computed tomography scans taken within 1 week of surgery and at 1-year postsurgery were co-registered and analyzed. Three co-registration strategies were implemented including bone-to-bone and implant-to-implant. (1) Co-registration of the ipsilateral innominate bone (diseased anatomy) was used to measure changes in implant position. (2) Co-registration of the implant was carried out to quantify changes in the ipsilateral innominate bone shape. (3) Co-registration of the contralateral innominate bone (nondiseased anatomy) was performed to measure changes in the ipsilateral innominate bone shape and implant position. The median centroid distances (interquartile range [IQR]) were 2.3 mm (IQR: 3.7–1.7 mm) for changes in implant position, 2.4 mm (IQR: 3.6–1.6 mm) for changes in ipsilateral innominate bone shape, and 3.7 mm (IQR: 4.6–3.5 mm) for changes in ipsilateral innominate bone shape and implant position. Following acetabular reconstruction, implant movements and periprosthetic bone remodeling are physiological and of a similar extent. Surgeons and engineers should consider this when performing implant monitoring in these patients."

Use of Simpleware Software

"The CT scans were rendered using specialized software (Simpleware ScanIP Medical, Version 2022.12; Synopsys, Inc.) to produce 3D reconstructions of the patients' pelvis and implant at the two imaging timepoints. Bone-to-bone registration of the ipsilateral innominate bone was used to assess the change in implant position. Implant-to-implant registration was carried out to understand changes in the ipsilateral innominate bone. Bone-to-bone registration of the contralateral innominate bone was used to quantify changes in implant position and ipsilateral innominate bone shape."

"CT scanning of the pelvis was carried out for all patients during the first-week and 1-year postsurgery. Digital Imaging and Communications in Medicine files were imported into Simpleware ScanIP Medical (Version 2022.12; Synopsys, Inc.) where intensity-based thresholding and region-splitting tools were implemented to create 3D reconstructions of the pelvises and implants."

Outcomes and Impact

"This is the first study that aimed to investigate how changes of the bone affect the measurement of the migration of custom implants for large acetabular defects. When performing CT implant monitoring in patients with large acetabular defects, changes of the ipsilateral innominate bone can occur over time. It is challenging to accurately quantify implant migration when the bone is remodeling. The study revealed how the reorganization of the bone affected the implant migration results in those cases for which the co-registration of the ipsilateral innominate bone was poor. It was also shown how the contralateral innominate side could be seen as a reflection of what was occurring on the ipsilateral innominate side. By co-registering the contralateral innominate bone, we were able to assess changes in both implant position and ipsilateral innominate bone shape. Therefore, bone remodeling needs to be considered to confidently report how much implants migrate over time.

Following acetabular reconstruction, implant movements and periprosthetic bone remodeling are physiological and appear to have the same extent. Surgeons and engineers should consider this when performing implant monitoring/surveillance in these patients."

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