Medical image analysis often involves time-consuming annotation processes. Pediatric image analysis introduces additional complexity due to the scarcity of data, noise, and growth-related anatomical variations, particularly in bone analysis, where bone structures evolve more slowly compared to other organs. This study aims to develop a segmentation model that scales across different age groups, reduces annotation effort, and ensures high accuracy, particularly in low-quality images. To address these challenges, we propose a segmentation pipeline (PedVision) that first uses a Region of Interest (ROI) network to identify relevant regions, followed by a foundation model that translates each region into meaningful instances. These instances are then mapped to segmentation classes through an instance classifier (IC) network. To initiate rounds of the training of ROI and IC networks, we developed a fast, semi-automated annotation framework that leverages foundation models to annotate a subset of images using an object-level approach. In subsequent rounds, a human discriminator selects promising predictions from the last round, which are fed by unseen data, progressively enriching the model's training dataset for further fine-tuning of the networks. The networks are expanded from low-parameter to high-parameter models across rounds, incorporating a curriculum learning approach to capture increasingly complex features. We evaluated PedVision on 552 hand X-ray images of children, retrieved from the publicly available Radiological Society of North America (RSNA) and Digital Hand Atlas (DHA) datasets, which represent a diverse range of ages and racial backgrounds. PedVision performed segmentation of 19 hand bones, grouped in five classes, and was compared against U-Net and DeepLabV3+ models using ResNet34 and ResNet101 backbones, as well as the SegFormer model with four different encoder variants. For pediatric cases (i.e., 0–7 years), the PedVision pipeline outperforms the best-performing models, achieving an 11.08 % improvement in Dice score over U-Net in the RSNA dataset and a 7.68 % improvement in the DHA dataset. When compared to DeepLabV3+, the improvements are even more substantial, with gains of 14.43 % in RSNA and 14.78 % in DHA. Additionally, PedVision shows notable advantages over the best SegFormer model, with improvements of 8.16 % in RSNA and 1.91 % in DHA. The project is open source at github.com/mohofar/PedVision.

Living biological tissue is a complex system, constantly growing and changing in response to external and internal stimuli. These processes lead to remarkable and intricate changes in shape. Modeling and understanding both natural and pathological (or abnormal) changes in the shape of anatomical structures is highly relevant, with applications in diagnostic, prognostic, and therapeutic healthcare. Nevertheless, modeling the longitudinal shape change of biological tissue is a non-trivial task due to its inherent nonlinear nature. In this review, we highlight several existing methodologies and tools for modeling longitudinal shape change (i.e., spatiotemporal shape modeling). These methods range from diffeomorphic metric mapping to deep-learning based approaches (e.g., autoencoders, generative networks, recurrent neural networks, etc.). We discuss the synergistic combinations of existing technologies and potential directions for future research, underscoring key deficiencies in the current research landscape.

Study Design: Microstructural investigation of mechanical load induced acute disc herniation on five animal models. Objective: To compare how spinal discs in different animal models herniate under a standardized complex compressive load. Summary of Background Data: Animal models in disc herniation research offer reduced degeneration-associated variability, lower cost, and greater availability compared to human specimens. However, there is limited consensus regarding which species is best suited for modeling human herniation, making a comprehensive comparison of species-specific herniation mechanisms necessary. Materials and Methods: A standardized shear and compressive load, designed to herniate intervertebral discs, was applied to isolated discs of five cadaveric animal models (n = 30, 6 specimens per group): bovine tail, bovine lumbar, ovine lumbar, porcine lumbar, and porcine cervical. The segments were flexed (7°), and a shear-compressive load was applied at a crosshead displacement rate of 40 mm min⁻¹, until a force drop, or a displacement limit was reached (~80% of disc height). Microstructural analysis was undertaken to identify failure modes. Results: Clinically relevant herniation features were observed in all models—including endplate and annulus fibrosus (AF) tearing, AF delamination, vertebral body (VB) fracture, nucleus pulposus (NP) extrusion into VB, and radial NP movement. Bovine lumbar, porcine cervical, and porcine lumbar segments exhibited high rates of radial NP movement (84%, 100%, and 67%, respectively), with ovine lumbar discs displaying VB fracture (84%) and NP extrusions into the VB (67%). Bovine tail discs showed minimal damage but were characterized by sequential lamellar AF tears (67%). Conclusions: Porcine cervical, bovine lumbar, and porcine lumbar discs are suitable for annulus-failure herniation research, although porcine cervical discs may be the most appropriate due to exhibiting the highest rate of relevant damages. Ovine lumbar discs are relevant for studying endplate junction failure herniations, and bovine tail discs are appropriate for implant-related studies.

High levels of physical activity or high BMI during puberty could negatively influence bone and cartilage development. Little is known about the effects of loading on patellar and femoral bone shape in a young population. Therefore, we aim to identify the association between 3D patella and femur shape and biomechanical loading in a young adolescent population. Participants were selected from an ongoing cohort study (Generation-R study). Participants that underwent knee-MRI at 13 years-old follow-up were included. Patellae and femora were segmented from these MRIs and using these 3D models, statistical shape modeling was performed. Generalized estimating equations were used to analyze the association between loading (BMI, physical activity and sports participation) and shape variation. Bonferroni correction was used to correct for multiple testing. 1912 participants underwent MRI of which 3638 patellae and 3355 femora were included in the statistical shape models. Nine patellar (modes 1–7, 10 and 11) and nine femoral (modes 1–3, 6–10 and 14) shape modes were associated with BMI. Sports participation at thirteen years old was associated with one patellar (mode 1) and two femoral (modes 1 and 6) shape modes. One shape mode (mode 12) was associated with sports participation at 9 and 13 years old. Sports participation and BMI were significantly associated with bone shape variations. BMI was associated with most shape variations found in our statistical shape models, emphasizing the significant impact of BMI on bone morphology during adolescence with implications for musculoskeletal health and injury prevention.

Existing deep learning (DL) networks are primarily trained on adult datasets and may not always generalize to pediatric populations, where growth plays a major role. Here, we investigated improving semantic segmentation outcomes of pediatric hand phalanges from radiographs without relying on fully pediatric training datasets, which are scarce. First, alternative DL networks (FCN-8, FCN-32, U-Net, Inception U-Net, and DeepLabv3+) were trained with manually segmented radiographs of near-skeletally-mature (NSM) subjects and their performances were evaluated using mean intersection-over-union (Mean IoU) and multiclass Dice scores. DeepLabv3+ and Inception U-Net performed the best for NSM segmentation, with Mean IoU scores of 0.899 ± 0.035 and 0.887 ± 0.062, respectively. These networks were then used to investigate zero pediatric data (scaling-based data augmentation) and minimal pediatric data (incremental pediatric data substitution) approaches to improve age-domain generalizability. The minimal pediatric data approach proved effective, with a 20 % pediatric data inclusion leading to an up to 21.1 % increase in Mean IoU for pediatric subjects compared to networks trained exclusively on NSM subjects. Furthermore, no adverse effects of this approach were found when tested on NSM subjects, and there were even improvements in performance for Inception U-Net. To conclude, we highlight that networks utilizing multi-scale filters perform best for the semantic segmentation of hand phalanges. We further demonstrate that a minimal inclusion of pediatric training data can markedly improve age-domain generalizability for semantic segmentation tasks. This removes the difficult task of gathering large training datasets of pediatric subjects, which is often impractical, if not impossible.

Temporomandibular joint (TMJ) replacement prostheses often face limitations in accommodating translational movements, leading to unnatural kinematics and loading conditions, which affect functionality and longevity. Here, we investigate the potential of functionally graded materials (FGMs) in TMJ prostheses to enhance mandibular kinematics and reduce joint reaction forces. We develop a functionally graded artificial cartilage for the TMJ implant and evaluate five FGM designs: hard, hard-soft, and three FGM gradients with gradual transitions from 90% hard material to 0%, 10%, and 20%. These designs are 3D printed, mechanically tested under quasi-static compression, and simulated under physiological conditions. Results from computational modeling and experiments are compared to an intact mandible during incisal clenching and left group biting. The FGM design with a transition from 90% to 0% hard material improves kinematics by 19% and decreases perfomance by 3%, reduces joint reaction forces by 8% and 10%, and increases mandibular movement by 20% and 88% during incisal clenching and left group biting, respectively. These findings provide valuable insights for next-generation TMJ implants.

Objective: Mandibular reconstruction using patient-specific cage implants is a promising alternative to the vascularized free flap reconstruction for nonirradiated patients with adequate soft tissues, or for patients whose clinical condition is not conducive to microsurgical reconstruction. This study aimed to assess the biomechanical performance of 3D printed patient-specific cage implants designed with a semi-automated workflow in a combined cadaveric and retrospective case series study. Methods: We designed cage implants for two human cadaveric mandibles using our previously developed design workflow. The biomechanical performance of the implants was assessed with the finite element analysis (FEA) and quasi-static biomechanical testing. Digital image correlation (DIC) was used to measure the full-field strains and validate the FE models by comparing the distribution of maximum principal strains within the bone. The retrospective study of a case series involved three patients, each of whom was treated with a cage implant of similar design. The biomechanical performance of these implants was evaluated using the experimentally validated FEA under the scenarios of both mandibular union and nonunion. Results: No implant or screw failure was observed prior to contralateral bone fracture during the quasi-static testing of both cadaveric mandibles. The FEA and DIC strain contour plots indicated a strong linear correlation (r = 0.92) and a low standard error (SE=29.32με), with computational models yielding higher strain values by a factor of 2.7. The overall stresses acting on the case series’ implants stayed well below the yield strength of additively manufactured (AM) commercially pure titanium, when simulated under highly strenuous chewing conditions. Simulating a full union between the graft and remnant mandible yielded a substantial reduction (72.7±1.5%) in local peak stresses within the implants as compared to a non-bonded graft. Conclusions: This study shows the suitability of the developed semi-automated workflow in designing patient-specific cage implants with satisfactory mechanical functioning under demanding chewing conditions. The proposed workflow can aid clinical engineers in creating reconstruction systems and streamlining pre-surgical planning. Nevertheless, more research is still needed to evaluate the osteogenic potential of bone graft insertions.

Objective: To examine the association between 3D patellar shape and 1) isolated magnetic resonance imaging (MRI)-based patellofemoral osteoarthritis (PFOA), 2) the morphological features of PFOA, and 3) the clinical symptoms of PFOA. Design: MRI data from 66 women with isolated MRI-based PFOA and 66 age- and BMI-matched healthy women were selected from a cohort study. The patellae were manually segmented from MRI scans and used to create a 3D statistical shape model (SSM) of the patella. Structural abnormalities were semi-standardized scored on MRI using MRI osteoarthritis knee score (MOAKS). Regression analyses were applied to determine the associations between the shape parameters retrieved from the SSM, group status, clinical symptoms, and structural abnormalities. Results: Four shape variants showed a statistically significant (<0.05) association with the group status. The mode responsible for most of the shape variations showed participants with PFOA possess a relatively thicker dorsal bump on the articular part of the patella, compared to patellae of control participants. Three of these variants showed an association with the presence of osteophytes and cartilage loss on the patella. Multiple associations were found between patellar shape and the clinical symptoms of PFOA. Conclusions: Patellar shape is associated with the prevalence of MRI-based PFOA in women. Some shape variants were also associated with clinical symptoms. Interestingly, one particular shape variant associated with the presence of MRI-based PFOA was earlier shown to be associated with structural abnormalities associated with OA in a population aged under 40. This may suggest that patellar shape may be an early detectable risk factor for PFOA.

We designed and fabricated a simple setup for the controlled crumpling of nanopatterned, surface-porous flat metallic sheets for the fabrication of volume-porous biomaterials and showed that crumpling can be considered as an efficient alternative to origami-inspired folding. Before crumpling, laser cutting was used to introduce pores to the sheets. We then fabricated titanium (Ti) nanopatterns through reactive ion etching on the polished Ti sheets. Thereafter, nanopatterned porous Ti sheets were crumpled at two deformation velocities (i.e., 2 and 100 mm/min). The compression tests of the scaffolds indicated that the elastic modulus of the specimens vary in the range of 11.8–13.9 MPa. Micro-computed tomography scans and computational simulations of crumpled scaffolds were performed to study the morphological properties of the resulting meta-biomaterials. The porosity and pore size of the scaffolds remained within the range of those reported for trabecular bone. Finally, the in vitro cell preosteoblasts culture demonstrated the cytocompatibility of the nanopatterned scaffolds. Moreover, the aspect ratio of the cells residing on the nanopatterned surfaces was found to be significantly higher than those cultured on the control scaffolds, indicating that the nanopatterned surface may have a higher potential for inducing the osteogenic differentiation of the preosteoblasts.

Porous biodegradable Mg and its alloys are considered to have a great potential to serve as ideal bone substitutes. The recent progress in additive manufacturing (AM) has prompted its application to fabricate Mg scaffolds with geometrically ordered porous structures. Extrusion-based AM, followed by debinding and sintering, has been recently demonstrated as a powerful approach to fabricating such Mg scaffolds, which can avoid some crucial problems encountered when applying powder bed fusion AM techniques. However, such pure Mg scaffolds exhibit a too high rate of in vitro biodegradation. In the present research, alloying through a pre-alloyed Mg-Zn powder was ultilized to enhance the corrosion resistance and mechanical properties of AM geometrically ordered Mg-Zn scaffolds simultaneously. The in vitro biodegradation behavior, mechanical properties, and electrochemical response of the fabricated Mg-Zn scaffolds were evaluated. Moreover, the response of preosteoblasts to these scaffolds was systematically evaluated and compared with their response to pure Mg scaffolds. The Mg-Zn scaffolds with a porosity of 50.3% and strut density of 93.1% were composed of the Mg matrix and MgZn₂ second phase particles. The in vitro biodegradation rate of the Mg-Zn scaffolds decreased by 81% at day 1, as compared to pure Mg scaffolds. Over 28 days of static immersion in modified simulated body fluid, the corrosion rate of the Mg-Zn scaffolds decreased from 2.3 ± 0.9 mm/y to 0.7 ± 0.1 mm/y. The yield strength and Young's modulus of the Mg-Zn scaffolds were about 3 times as high as those of pure Mg scaffolds and remained within the range of those of trabecular bone throughout the biodegradation tests. Indirect culture of MC3T3-E1 preosteoblasts in Mg-Zn extracts indicated favorable cytocompatibility. In direct cell culture, some cells could spread and form filopodia on the surface of the Mg-Zn scaffolds. Overall, this study demonstrates the great potential of the extrusion-based AM Mg-Zn scaffolds to be further developed as biodegradable bone-substituting biomaterials.

The treatment of femoral nonunion with large segmental bone defect is still challenging. Although magnesium alloys have been considered potential materials for such a treatment, their application is limited by their fast degradation. Adding bioceramic particles into magnesium to form Mg-matrix composites is a promising strategy to adjust their biodegradation rates and to improve their mechanical properties and cytocompatibility further. Here, we developed an extrusion-based additive manufacturing technique to fabricate biodegradable Mg-Zn/bioceramic composite scaffolds ex-situ. Inks carrying a Mg-Zn powder and 5, 10 and 15% β-tricalcium phosphate (TCP) powder particles were investigated regarding the dispersion of β-TCP particles in the inks and viscoelastic properties. Optimally formulated inks were then employed for subsequent 3D printing of porous composite scaffolds. The in vitro biodegradation rate of the scaffolds containing 5% β-TCP decreased to 0.5 mm/y, which falls within the range desired for critical-sized bone substitution. As compared to the monolithic Mg-Zn scaffolds, the elastic moduli and yield strengths of the composite scaffolds were much enhanced, which remained in the range of the cancellous bone properties even after 28 d of in vitro degradation. The Mg-Zn/5TCP and Mg-Zn/10TCP scaffolds also exhibited improved biocompatibility when cultured with preosteoblasts, as compared to Mg-Zn scaffolds. In addition, the ALP activity and mineralization level of the composite scaffolds were much enhanced in the extracts of the composite scaffolds. Taken together, this research marks a great breakthrough in fabricating porous Mg-matrix composite scaffolds that meet several design criteria in terms of appropriate biodegradation rate, mechanical properties, and bioactivity. Statement of significance: The treatment of posttraumatic femoral nonunion with large segmental bone defect is still challenging. In this study, we developed a multi-material extrusion-based additive technique to fabricate porous Mg/bioceramic composite scaffolds for such a treatment. The technique allowed for the fine-tuning of printable inks to optimize the dispersion of micro-sized particles. The relative densities of the struts of the fabricated composite scaffolds reached 99%. The added bioceramic particles (β-TCP) exhibited proper interfacial bonding with the Mg alloy matrix. The porous Mg-based composite possessed desired biodegradability, bone-mimicking mechanical properties throughout the in vitro biodegradation period and improved bioactivity to bone cells. These results demonstrated great prospects of extrusion-based 3D printed porous Mg materials to be developed further as ideal biodegradable bone-substituting materials.

Background: The objective consisted of 2 elements, primarily to define 2 bone geometry variations of the ankle that may be of prognostic value on ankle instability and secondly to translate these bone variations from a 3D model to a simple 2D radiographic measurement for clinical use. Methods: The 3D tibial and talar shape differences derived from earlier studies were translated to two 2D radiographic parameters: the medial malleolar height angle (MMHA) and talar convexity angle (TCA) respectively to ensure clinical use. To assess validity, the MMHA and TCA were measured on 3D polygons derived from lower leg computed tomographic (CT) scans and 2D digitally reconstructed radiographs (DRRs) of these polygons. To assess reliability, the MMHA and TCA were measured on standard radiographs by 2 observers calculating the intraclass correlation coefficient (ICC). Results: The 3D angle measurements on the polygons showed substantial to excellent agreement with the 2D measurements on DRR for both the MMHA (ICC 0.84-0.93) and TCA (ICC 0.88-0.96). The interobserver reliability was moderate with an ICC of 0.58 and an ICC of 0.64 for both the MMHA and TCA, respectively. The intraobserver reliability was excellent with an ICC of 0.96 and 0.97 for the MMHA and the TCA, respectively. Conclusion: Two newly defined radiographic parameters (MMHA and TCA) are valid and can be assessed with excellent intraobserver reliability on standard radiographs. The interobserver reliability was moderate and indicates training is required to ensure uniformity in measurement technique. The current method may be used to translate more variations in bone shape prior to implementation in clinical practice. Level of Evidence: Level III, cohort study.

The reconstruction of large mandibular defects with optimal aesthetic and functional outcomes remains a major challenge for maxillofacial surgeons. The aim of this study was to design patient-specific mandibular reconstruction implants through a semi-automated digital workflow and to assess the effects of topology optimization on the biomechanical performance of the designed implants. By using the proposed workflow, a fully porous implant (LA-implant) and a topology-optimized implant (TO-implant) both made of Ti-6Al-4V ELI were designed and additively manufactured using selective laser melting. The mechanical performance of the implants was predicted by performing finite element analysis (FEA) and was experimentally assessed by conducting quasi-static and cyclic biomechanical tests. Digital image correlation (DIC) was used to validate the FE model by comparing the principal strains predicted by the FEM model with the measured distribution of the same type of strain. The numerical predictions were in good agreement with the DIC measurements and the predicted locations of specimen failure matched the actual ones. No statistically significant differences (p < 0.05) in the mean stiffness, mean ultimate load, or mean ultimate displacement were detected between the LA- and TO-implant groups. No implant failures were observed during quasi-static or cyclic testing under masticatory loads that were substantially higher (>1000 N) than the average maximum biting force of healthy individuals. Given its relatively lower weight (16.5%), higher porosity (17.4%), and much shorter design time (633.3%), the LA-implant is preferred for clinical application. This study clearly demonstrates the capability of the proposed workflow to develop patient-specific implants with high precision and superior mechanical performance, which will greatly facilitate cost- and time-effective pre-surgical planning and is expected to improve the surgical outcome.

Quantitative Magnetic Resonance Imaging (MRI) can enable early diagnosis of knee cartilage damage if imaging is performed during the application of load. Mechanical loading via ropes, pulleys and suspended weights can be obstructive and require adaptations to the patient table. In this paper, a new lightweight MRI-compatible elastic loading mechanism is introduced. The new device showed sufficient linearity (|α/β| = 0.42 ± 0.25), reproducibility (CoV = 5 ± 2%), and stability (CoV = 0.5 ± 0.1%). In vivo and ex vivo scans confirmed the ability of the device to exert sufficient force to study the knee cartilage under loading conditions, inducing up to a 29% decrease in T2 of the central medial cartilage. With this device mechanical loading can become more accessible for researchers and clinicians, thus facilitating the translational use of MRI biomarkers for the detection of cartilage deterioration.

Additive manufacturing (AM) offers great design freedom that enables objects with desired unique and complex geometry and topology to be readily and cost-effectively fabricated. The overall benefits of AM are well known, such as increased material and resource efficiency, enhanced design and production flexibility, the ability to create porous structures and on-demand manufacturing. When AM is applied to medical devices, these benefits are naturally assumed. However, hard clinical evidence collected from clinical trials and studies seems to be lacking and, as a result, systematic assessment is yet difficult. In the present work, we have reviewed 23 studies on the clinical use of AM patient-specific surgical guides (PSGs) for the mandible surgeries (n = 17) and temporomandibular joint (TMJ) patient-specific implants (PSIs) (n = 6) with respect to expected clinical outcomes. It is concluded that the data published on these AM medical devices are often lacking in comprehensive evaluation of clinical outcomes. A complete set of clinical data, including those on time management, costs, clinical outcomes, range of motion, accuracy of the placement with respect to the pre-operative planning, and extra complications, as well as manufacturing data are needed to demonstrate the real benefits gained from applying AM to these medical devices and to satisfy regulatory requirements.

We studied the three-dimensional (3-D) shape variations and symmetry of the lunate to evaluate whether a contralateral shape-based approach to design patient-specific implants for treatment of Kienböck’s disease is accurate. A 3-D statistical shape model of the lunate was built using the computed tomography scans of 54 lunate pairs and shape symmetry was evaluated based on an intraclass correlation analysis. The lunate shape was not bilaterally symmetrical in (1) the angle scaphoid surface – radius-ulna surface, (2) the dorsal side and the length of the side adjacent to the triquetrum, (3) the orientation of the volar surface, (4) the width of the side adjacent to the scaphoid, (5) the skewness in the coronal plane and (6) the curvature of bone articulating with the hamate and capitate. These findings suggest that using the contralateral lunate to design patient-specific lunate implants may not be as accurate as it is intended.

Additively manufactured (AM) biodegradable magnesium (Mg) scaffolds with precisely controlled and fully interconnected porous structures offer unprecedented potential as temporary bone substitutes and for bone regeneration in critical-sized bone defects. However, current attempts to apply AM techniques, mainly powder bed fusion AM, for the preparation of Mg scaffolds, have encountered some crucial difficulties related to safety in AM operations and severe oxidation during AM processes. To avoid these difficulties, extrusion-based 3D printing has been recently developed to prepare porous Mg scaffolds with highly interconnected structures. However, limited bioactivity and a too high rate of biodegradation remain the major challenges that need to be addressed. Here, we present a new generation of extrusion-based 3D printed porous Mg scaffolds that are coated with MgF2 and MgF2-CaP to improve their corrosion resistance and biocompatibility, thereby bringing the AM scaffolds closer to meeting the clinical requirements for bone substitutes. The mechanical properties, in vitro biodegradation behavior, electrochemical response, and biocompatibility of the 3D printed Mg scaffolds with a macroporosity of 55% and a strut density of 92% were evaluated. Furthermore, comparisons were made between the bare scaffolds and the scaffolds with coatings. The coating not only covered the struts but also infiltrated the struts through micropores, resulting in decreases in both macro- and micro-porosity. The bare Mg scaffolds exhibited poor corrosion resistance due to the highly interconnected porous structure, while the MgF2-CaP coatings remarkably improved the corrosion resistance, lowering the biodegradation rate of the scaffolds down to 0.2 mm y-1. The compressive mechanical properties of the bare and coated Mg scaffolds before and during in vitro immersion tests for up to 7 days were both in the range of the values reported for the trabecular bone. Moreover, direct culture of MC3T3-E1 preosteoblasts on the coated Mg scaffolds confirmed their good biocompatibility. Overall, this study clearly demonstrated the great potential of MgF2-CaP coated porous Mg prepared by extrusion-based 3D printing for further development as a bone substitute. This journal is

The design of advanced functional devices often requires the use of intrinsically curved geometries that belong to the realm of non-Euclidean geometry and remain a challenge for traditional engineering approaches. Here, it is shown how the simple deflection of thick meta-plates based on hexagonal cellular mesostructures can be used to achieve a wide range of intrinsic (i.e., Gaussian) curvatures, including dome-like and saddle-like shapes. Depending on the unit cell structure, non-auxetic (i.e., positive Poisson ratio) or auxetic (i.e., negative Poisson ratio) plates can be obtained, leading to a negative or positive value of the Gaussian curvature upon bending, respectively. It is found that bending such meta-plates along their longitudinal direction induces a curvature along their transverse direction. Experimentally and numerically, it is shown how the amplitude of this induced curvature is related to the longitudinal bending and the geometry of the meta-plate. The approach proposed here constitutes a general route for the rational design of advanced functional devices with intrinsically curved geometries. To demonstrate the merits of this approach, a scaling relationship is presented, and its validity is demonstrated by applying it to 3D-printed microscale meta-plates. Several applications for adaptive optical devices with adjustable focal length and soft wearable robotics are presented.