Marc E. Levenston

Background: Meniscal repair is increasingly performed in pediatric patients, with capsular-based techniques remaining the gold standard despite limitations such as high failure rates and risk of meniscal extrusion. Recent studies highlight the potential role of accessory knee ligaments in improving meniscal stability and repair outcomes. The meniscotibial ligament complex (MTLC) has emerged as a potential area of interest to produce more normal anatomic and biomechanical meniscal function in meniscal repair. Purpose: To evaluate the native anatomy and biomechanical strength of the MTLC of the medial and lateral meniscus of pediatric knees. Study Design: Descriptive laboratory study. Methods: Fourteen fresh-frozen pediatric human knees (mean age, 7.5 years; range, 5-10 years; 6 male, 8 female) were used in this study. The depth of the recess between the MTLC and the meniscocapsular complex was measured. Subsequently, the medial and lateral menisci were divided into approximate thirds, creating anterior, central, and posterior testing zones for each meniscus. Each meniscus/MTLC complex underwent monotonic load-to-failure testing on an Instron 5944 test frame with a 2-kN load cell with load applied superiorly. Biomechanical properties were analyzed using linear mixed models with donor as a random factor and aspect (medial/lateral) and position (anterior/central/posterior) as fixed factors. Results: = .01). Conclusion: This study defines a clear space in which the MTLC is distinct from the joint capsule, which is deepest in the posterior third of the medial and lateral meniscus. Our results demonstrate that the posterior region of the MTLC can withstand higher loads than the anterior region in pediatric knees. Clinical Relevance: These findings offer foundational insights into the native anatomy and biomechanics of the MTLC, guiding future studies involving the MTLC in meniscal repair. This knowledge may be particularly relevant to ramp lesions, other posterior meniscal tear patterns, and meniscal transplants.

Photon counting CT (PCCT) uses energy-resolving detectors to count and assign individual incident x-ray photons to preset energy bins, offering improved image quality, energy discrimination capability, and dose efficiency. Existing PCCT studies typically explore the spatial resolution and spectral performance improvement of PCCT separately. In this work, we leverage spectral information to improve spatial resolution through the non-linear partial volume (NLPV) effect and demonstrate its utility in PCCT images with simulated phantom studies. A fictitious “third material” was defined to represent the magnitude of the sub-pixel iodine transition sharpness, or the NLPV effect. After a projection-domain “three-material decomposition” of iodine/water/NLPV, the iodine and NLPV components were used to characterize the sub-pixel iodine profile and generate two sub-pixel values to replace the original pixel value at detector pixels with large iodine transition. With the improved sub-pixel iodine profile characterization, we generated the NLPV-enhanced iodine projections and reconstructed the iodine images. Phantoms pertinent to knee anatomy were simulated, and pig stifle experiments will be performed in the future. We show that with the improved NLPV algorithm, the image-domain spatial resolution improved by ~62% in the noiseless case and ~40% in the noisy case.

• To mimic animal meat, plant-based meat must match mouthfeel, taste, and texture. • To quantify texture, we tested eight meats using texture profile analysis and rheology. • Sample stiffnesses varied from 419 kPa for plant-based turkey to 57 kPa for tofu. • Animal turkey, sausage, and hotdog ranked within these plant-based extremes. • Plant-based meat can replicate the full stiffness spectrum of comminuted animal meat. Plant-based meat can help combat climate change and health risks associated with high meat consumption. To create adequate mimics of animal meats, plant-based meats must match in mouthfeel, taste, and texture. The gold standard to characterize the texture of meat is the double compression test, but this test suffers from a lack of standardization and reporting inconsistencies. Here we characterize the texture of five plant-based and three animal meats using texture profile analysis and rheology, and report ten mechanical features associated with each product’s elasticity, viscosity, and loss of integrity. Our findings suggest that, of all ten features, the stiffness, storage, and loss moduli are the most meaningful and consistent parameter to report, while other parameters suffer from a lack of interpretability and inconsistent definitions. We find that the sample stiffness varies by an order of magnitude, from 418.9 ± 41.7 kPa for plant-based turkey to 56.7 ± 14.1 kPa for tofu. Similarly, the storage and loss moduli vary from 50.4 ± 4.1 kPa and 25.3 ± 3.0 kPa for plant-based turkey to 5.7 ± 0.5 kPa and 1.3 ± 0.1 kPa for tofu. All three animal products, animal turkey, sausage, and hotdog, consistently rank in between these two extremes. Our results suggest that–with the right ingredients, additives, and formulation–modern food fabrication techniques can create plant-based meats that successfully replicate the full viscoelastic texture spectrum of processed animal meat.

Eating less meat is associated with a healthier body and planet. Yet, we remain reluctant to switch to a plant-based diet, largely due to the sensory experience of plant-based meat. Food scientists characterize meat using a double compression test, which only probes one-dimensional behavior. Here we use tension, compression, and shear tests-combined with constitutive neural networks-to automatically discover the behavior of eight plant-based and animal meats across the entire three-dimensional spectrum. We find that plant-based sausage and hotdog, with stiffnesses of 95.9 ± 14.1 kPa and 38.7 ± 3.0 kPa, successfully mimic their animal counterparts, with 63.5 ± 45.7 kPa and 44.3 ± 13.2 kPa, while tofurky is twice as stiff, and tofu is twice as soft. Strikingly, a complementary food tasting survey produces in nearly identical stiffness rankings for all eight products (ρ = 0.833, p = 0.015). Probing the fully three-dimensional signature of meats is critical to understand subtle differences in texture that may result in a different perception of taste. Our data and code are freely available at https://github.com/LivingMatterLab/CANN.

Abstract Plant-based meat can help combat climate change and health risks associated with high meat consumption. To create adequate mimics of animal meats, plant-based meats must match in mouthfeel, taste, and texture. The gold standard to characterize the texture of meat is the double compression test, but this test suffers from a lack of standardization and reporting inconsistencies. Here we characterize the texture of five plant-based and three animal meats using texture profile analysis and rheology, and report ten mechanical features associated with each product’s elasticity, viscosity, and loss of integrity. Our findings suggest that, of all ten features, the stiffness, storage, and loss moduli are the most meaningful and consistent parameter to report, while other parameters suffer from a lack of interpretability and inconsistent definitions. We find that the sample stiffness varies by an order of magnitude, from 418.9±41.7kPa for plant-based turkey to 56.7±14.1kPa for tofu. Similarly, the storage and loss moduli vary from 50.4±4.1kPa and 25.3±3.0kPa for plant-based turkey to 5.7±0.5kPa and 1.3±0.1kPa for tofu. All three animal products, animal turkey, sausage, and hotdog, consistently rank in between these two extremes. Our results suggest that–with the right ingredients, additives, and formulation–modern food fabrication techniques can create plant-based meats that successfully replicate the full viscoelastic texture spectrum of processed animal meat.

Abstract Eating less meat is associated with a healthier body and planet. Yet, we remain reluctant to switch to a plant-based diet, largely due to the sensory experience of plant-based meat. Food scientists characterize meat using a double compression test, which only probes one-dimensional behavior. Here we use tension, compression, and shear tests–combined with constitutive neural networks–to automatically discover the behavior of eight plant-based and animal meats across the entire three-dimensional spectrum. We find that plant-based sausage and hotdog, with stiffnesses of 95.9±14.1kPa and 38.7±3.0kPa, successfully mimic their animal counterparts, with 63.5±45.7kPa and 44.3±13.2 kPa, while tofurky is twice as stiff, and tofu is twice as soft. Strikingly, a complementary food tasting survey produces in nearly identical stiffness rankings for all eight products ( ρ =0.833, p=0.015). Probing the fully three-dimensional signature of meats is critical to understand subtle differences in texture that may result in a different perception of taste. Our data and code are freely available at https://github.com/LivingMatterLab/CANN

MRI-driven computational constitutive modeling can be used to obtain subject-specific myocardial passive stiffness. Verifying the accuracy and precision of this technique requires overcoming the challenge of obtaining ground-truth in vivo myocardial stiffness. We developed a controllable in vitro diastolic filling setup which incorporates a soft heart phantom of known myocardium-mimicking mechanical stiffness and MRI properties. Using the setup we demonstrate that uncertainties in quantifying cardiac reference geometry can lead to errors in estimating myocardial passive stiffness. The in vitro setup is designed to enable us to achieve our overarching goal: to extensively validate in vivo MRI-based myocardial passive stiffness estimation.

Objectives: Meniscal injuries are among the most common orthopedic injuries in the United States. Radial meniscus tears were historically treated with partial meniscectomy, often leading to poor outcomes. Radial tear repair preserves meniscal tissue, may delay knee degeneration, and leads to better long-term outcomes. Repair techniques for radial tears vary and should be evaluated for differences in biomechanical properties and failure mechanisms. All-inside, meniscus-based suture repairs have shorter operating times, minimize risk of nerve injury, and are increasingly possible with novel devices. Our objective was to evaluate the strength based on load-to-failure of four all-inside meniscus-based repair techniques for radial tears in human cadaveric lateral menisci. We chose two techniques that bridged the tear directly – the Double Vertical (DV, Figure 1) and Double Vertical Cross (DVX, Figure 2). We chose two other techniques that added horizontal reinforcing stitches to engage the bridging stitches – the All-inside Rebar (AR, Figure 3) and our novel Oblique Box (OB, Figure 4). We hypothesized that AR and OB would have higher load to failure than DV and DVX. Methods: 36 fresh-frozen human adult lateral menisci were randomized into four groups of nine. Dissection, repair, and testing were completed one meniscus at a time to minimize the time period from thawing to testing. Each meniscus was dissected from its tibial bone block, and a complete radial tear was created at the midbody of the meniscus. Suture repairs were performed using 2-0 braided suture and a straight needle. Menisci were repaired using the DV, DVX, AR, and OB techniques with meniscus- based suturing to simulate the all-inside, meniscus-based approach. All suture dimensions were standardized as indicated on Figures 1-4, and all knots were tied on the superior surface of the menisci. The suture patterns for all repair types used loops that passed above the superior and below the inferior surfaces of the meniscus. The DV repair used two sutures in loops perpendicular to the tear. DVX used two sutures in loops that crossed over the tear. AR used two sutures in loops parallel to the tear acting as reinforcing rebar and two bridging sutures perpendicular to the tear and outside the rebar sutures. OB used two sutures to create a trapezoidal reinforcing box on either side of the tear and two bridging sutures in loops perpendicular to the tear and inside the box. The repaired menisci were loaded on an Instron 5944 test frame with 2 kN load cell using custom clamps. They underwent cyclic loading of 5-30 N for 500 cycles at 10 mm/min, a 30-minute resting period, and a single trial of load-to-failure at 10 mm/min. The ultimate load at failure was analyzed via one-way ANOVA with Tukey’s test for pairwise comparisons and significance set at p<0.05. Results: Failure occurred due to suture cutout in all specimens. Repair constructs that lacked a reinforcing-type suture (DV and DVX) cut through or “cheese-wired” at lower loads than repairs with reinforcing sutures (AR and OB). Mean ± standard deviation ultimate load values for each repair group were 60 N ± 24.5 for DV, 58 N ± 17.4 for DVX, 168 N ± 33.9 for AR, and 105 N ± 9.0 for OB. The ultimate load for all repair techniques were significantly different from each other by Tukey’s test with the exception of the DV and DVX comparison. These results show that reinforcing vertical suture meniscus repairs with some type of horizontal suture (e.g. AR or OB) significantly increases ultimate load at failure for all-inside, meniscus-based techniques. Conclusions: In a cadaveric lateral meniscus model, all-inside radial repairs using rebar suture, or horizontal suture reinforcing techniques, had higher ultimate load at failure and reduced risk of “cheese wiring”. The AR repair sustained the highest ultimate load at failure, nearly 3x stronger than the two non-reinforcing type repair constructs. These data may provide useful information for surgeons during repair to radial meniscus tears. Future biomechanical study should compare all-inside vs. inside-out repairs to maximize patient outcomes. Cross reference of repair patterns with clinical outcomes using the prospective registry data may support optimal surgical techniques to improve meniscus repair outcomes.

Objectives: Meniscal injuries are among the most common orthopedic injuries in the United States. Meniscus repairs frequently achieve stability via capsular based repair techniques. Recent studies on meniscal ramp lesions, postero-lateral tears, and meniscus transplants demonstrate some shortcomings of meniscus suture techniques that incorporate menisco-capsular complex (MCC) repair. 1-3 Meniscus extrusion may also be affected by the function and integrity of the meniscus/menisco-tibial ligament complex (MTLC). 4 Inclusion of the MTLC in some repair/transplant constructs may produce more normal anatomic and biomechanical meniscus function, including the prevention of meniscus extrusion. However, the biomechanical properties of the MTCL in pediatric tissue has not been studied. Our objective was to evaluate the anatomy and biomechanical strength of the MTLC of the medial and lateral meniscus of pediatric knees. We hypothesized: 1) posterior anatomy of the medial and lateral knee would demonstrate a consistent recess or space between the posterior meniscus/MTLC complex and the MCC; and 2) the MTLC would demonstrate unique biomechanical characteristics between the posterior, middle, and anterior 1/3 zones of the medial and lateral meniscus. Methods: 14 fresh-frozen pediatric human knees from 10 donors (mean 7.5 years, range 5-10 years) were used in this study. The distance between the mensico-tibial ligament at the joint capsule and the height of the meniscus was measured with a depth gauge and digital caliper. We define this distance as the depth of the recess between MTLC and MCC (Fig. 1). Subsequently, the medial and lateral menisci were divided into approximate thirds with radial cuts extending through the menisco-tibial ligaments, creating anterior, central, and posterior testing zones for each meniscus (Fig. 2A). The posterior and anterior roots of each meniscus were released from the tibial attachment. Sandpaper was glued to each meniscus segment. Each tibial specimen was potted in fiberglass resin and mounted on an Instron 5944 test frame with a 2 kN load cell. Each meniscus/MTLC complex underwent 10 cycles of preconditioning from 3-5N at 10 mm/min followed by monotonic load to failure testing (Fig. 2B). The depth of recess, load-to-failure, and stiffness (maximum slope of load-displacement curve) were analyzed using linear mixed models with donor and limb as random factors and compartment (M/L) and position as fixed factors. Significance was at p<0.05 and pairwise comparisons used Bonferroni’s test. Results are reported as mean ± s.d. Results: A clear separation of the posterior 1/3 of each meniscus/MTLC and the posterior MCC was seen for each specimen, with a less obvious separation in anterior and central thirds. The depth of recess was significantly larger (p=0.049) in the posterior region (5.41 ± 2.05 mm) than in the anterior region (3.40 ± 2.00 mm), with no significant difference between medial and lateral menisci (Fig. 3). This confirms a distinct separation between the MTLC and the MCC. The load to failure in the anterior region (66.8 ± 31.3 N) was significantly lower than that in the central (91.7 ± 28.0 N, p=0.014) or posterior (93.5 ± 36.5 N, p=0.005) regions, with no significant difference between medial and lateral menisci (Fig. 4A). The stiffness of the central MTLC complex was significantly lower (p=0.014) in lateral menisci (10.0 ± 4.2 N/m) than in medial menisci (18.8 ± 9.4 N/m), with no other significant differences between regions (Fig. 4B). Conclusions: This study defines a clear space in the posterior 1/3 of the medial and lateral meniscus, in which the MTLC complex is distinct from the posterior MCC of the knee joint. This anatomic finding may suggest alternative techniques of meniscus repair/transplant fixation that include direct repair of some meniscus regions to the menisco-tibial ligament instead of meniscus repair to the capsular layer or MCC. This may be of particular importance to Ramp meniscus lesions, other posterior meniscus tear patterns, and meniscus transplant fixation techniques. Our results demonstrate that the central and posterior region of the MTLC can withstand higher loads than the anterior region, indicating that meniscus repairs in the central/posterior region may be of particular importance. These findings support continued development and evaluation of MTLC repair techniques that seek to reproduce the biomechanical and anatomic function of the MTLC, the MCC, and posterior meniscus. Future studies will need to evaluate the impact of MTLC repair on meniscus repair/transplant outcomes and meniscus extrusion. Abrams GD, Frank RM, Gupta AK, Harris JD, McCormick FM, Cole BJ. Trends in meniscus repair and meniscectomy in the United States, 2005-2011. Am J Sports Med. 2013;41(10):2333-2339. doi:10.1177/0363546513495641. Paxton ES, Stock MV, Brophy RH. Meniscal repair versus partial meniscectomy: a systematic review comparing reoperation rates and clinical outcomes. Arthrosc J Arthrosc Relat Surg Off Publ Arthrosc Assoc N Am Int Arthrosc Assoc. 2011;27(9):1275-1288. doi:10.1016/j.arthro.2011.03.088. Vint H, Quartley M, Robinson JR. All-inside versus inside-out meniscal repair: A systematic review and meta-analysis. The Knee. 2021;28:326-337. doi:10.1016/j.knee.2020.12.005. Paletta GA Jr, Crane DM, Konicek J, Piepenbrink M, Higgins LD, Milner JD, Wijdicks CA. Surgical Treatment of Meniscal Extrusion: A Biomechanical Study on the Role of the Medial Meniscotibial Ligaments With Early Clinical Validation. Orthop J Sports Med. 2020;8(7):2325967120936672. Published 2020 Jul 29. doi:10.1177/2325967120936672.

Abstract Artificial meat is an eco-friendly alternative to real meat that is marketed to have a similar taste and feel. The mechanical properties of artificial meat significantly influence our perception of taste, but how precisely the mechanics of artificial meat compare to real meat remains insufficiently understood. Here we perform mechanical tension, compression, and shear tests on isotropic artificial meat (Tofurky® Plant-Based Deli Slices), anisotropic artificial meat (Daring™ Chick’n Pieces) and anisotropic real meat (chicken) and analyze the data using constitutive neural networks and automated model discovery. Our study shows that, when deformed by 10%, artificial and real chicken display similar maximum stresses of 21.0 kPa and 21.8 kPa in tension, -7.2 kPa and -16.4 kPa in compression, and 2.4 kPa and 0.9 kPa in shear, while the maximum stresses for tofurky were 28.5 kPa, -38.3 kP, and 5.5 kPa. To discover the mechanics that best explain these data, we consulted two constitutive neural networks of Ogden and Valanis-Landel type. Both networks robustly discover models and parameters to explain the complex nonlinear behavior of artificial and real meat for individual tension, compression, and shear tests, and for all three tests combined. When constrained to the classical neo Hooke, Blatz Ko, and Mooney Rivlin models, both networks discover shear moduli of 94.4 kPa for tofurky, 35.7 kPa for artificial chick’n, and 21.4 kPa for real chicken. Our results suggests that artificial chicken succeeds in re-producing the mechanical properties of real chicken across all loading modes, while tofurky does not, and is about three times stiffer. Strikingly, all three meat products display shear softening and their resistance to shear is about an order of magnitude lower than their resistance to tension and compression. We anticipate our study to inspire more quantitative, mechanistic comparisons of artificial and real meat. Our automated-model-discovery based approach has the potential to inform the design of more authentic meat substitutes with an improved perception of taste, with the ultimate goal to reduce environmental impact, improve animal welfare, and mitigate climate change, while still offering the familiar taste and texture of traditional meat. Our source code, data, and examples will be available at https://github.com/LivingMatterLab/CANNs .