Medtronic to Acquire French Spinal Surgery Maker Medicrea, Strengthening 3D Printed Implants

As part of medical device maker Medtronic‘s push toward a fully integrated solution for surgical planning, the company announced its intent to acquire Medicrea, a French pioneer in innovative surgical technologies for the treatment of complex spinal pathologies, in a transaction valued at €7 ($8) per share. The all-cash agreement, set to purchase all of Medicrea’s outstanding shares, had unanimous approval by both companies and is expected to close by the end of 2020, subject to regulatory approvals and other customary closing conditions from both France and the United States.

Medtronic treats the first U.S. patients with spinal surgery robot (Image courtesy of Medtronic)

“Combining Medtronic’s innovative portfolio of spine implants, robotics, navigation, and 3D imaging technology with Medicrea’s capabilities and solutions in data analytics, artificial intelligence, and personalized implants, would enhance Medtronic’s fully-integrated procedural solution for surgical planning and delivery. This marks another important step in furthering our commitment to improving outcomes in spine care,” said Jacob Paul, senior vice president and president of the Cranial and Spinal Technologies division, which is part of the Restorative Therapies Group at Medtronic, headquartered in Ireland. “Medtronic will become the first company to be able to offer an integrated solution including artificial intelligence-driven surgical planning, personalized spinal implants and robotic-assisted surgical delivery, which will significantly benefit our customers and their patients.”

Following news of the deal, Medicrea shares jumped by 20% in regular trading, most likely due to the premium the acquiring company was set to pay on the target’s share price, in this case, 22 percent over the closing price of Medicrea shares on 14 July 2020.

Medicrea’s UNiD technology (Image courtesy of Medicrea)

The deal will allow Medtronic to incorporate Medicrea’s latest innovations, which include the UNiD ASI (Adaptive Spine Intelligence) technology, designed to support surgeon workflow in pre-operative planning and incorporating 3D printing processes to create personalized implant solutions for surgery. The company’s portfolio also consists of artificial intelligence-driven surgical planning using predictive modeling and sophisticated algorithms that measure and digitally reconstruct the spine to its optimal profile. As well as an ultra-modern manufacturing facility in Lyon, France housing the development and production of 3D printed titanium patient-specific implants.

“Spine surgery is one of the more complex procedures in healthcare because of the high number of different parameters to take into consideration. It is impossible for the human brain to compute all of them for one single patient,” said Denys Sournac, founder, chairman and CEO of Medicrea. “The medical world has been waiting for the arrival of customization in spinal surgery. With scientific progress in understanding sagittal balance and spinal injury, combined with the advent of new digital technologies, it is now possible to offer spinal patients entirely customized implants. We are thrilled to be joining forces with Medtronic because we share a similar mission to restore the long-term quality of life for patients. Now, together, we can help more patients in more places benefit from consistently high-quality surgical care.”

3D-printed spinal implants from Medicrea (Image courtesy of Medicrea)

The news comes amid expectations of an eventual recovery from the coronavirus pandemic and as Medtronic’s stock bounces back from a significant fall in the early months after COVID-19 emerged. The overall decline in procedures and supply chain disruptions have been among the key causes of concern for Medtronic, as well as impacted sales generated from China.

Medtronic said in a statement that the completion of the deal was subject to Medtronic getting at least 66.67% of Medicrea’s share capital. Up until now, Medtronic has entered into agreements with Medicrea shareholders totaling 44.4% of the company’s current outstanding share capital. The tender offer is expected to be filed with the French Markets Authority (AMF) in September 2020 and will be opened once the foreign investment approval in France and the merger control clearance in the United States are finalized.

Over the last seven decades, Medtronic has introduced a wide range of products to treat up to 70 health conditions, from cardiac devices and surgical tools to cranial and spine robotics, even insulin pumps, and patient monitoring systems. In the last few years, teams of scientists and engineers at the company have been working on new possibilities for personalized medicine using 3D printing technology, like its titanium 3D printing platform for spinal surgery implants. At the company’s facility, seven 3D printers work around the clock filling orders for rapid prototyping and medical models that allow doctors to practice procedures on life-like simulations. Additionally, researchers from Medtronic teamed up with academia to create a new operating room system powered by personalized 3D images, to give neurosurgeons better tools to remove brain tumors.

Medtronic headquarters in Dublin, Ireland (Image courtesy of Medtronic)

As of 2017, Medtronic was the leader in the U.S. market for spinal implants with a share of over one third. Once the acquisition is complete, the company will be able to expand and strengthen its position as a global innovator in further enabling technologies and solutions for spine surgery.

Spinal procedures are considered by experts as one of the most painful in neurosurgery and orthopedics, with over 1.62 million instrumented interventions performed every year. ResearchMoz analysts predicted the global spine surgery products market to hit $16.7 billion by 2025, mainly due to an increase in spine disorder cases among the geriatric population. The demand for innovative, minimally invasive solutions to this problem is critical for patient healthcare, which is why Medtronic is looking towards the predictive medicine opportunity that Medicrea has been developing, by collecting an unprecedented amount of data to develop its proprietary predictive models and employing disruptive technologies in every step of the way. Overall, the combination of the companies’ technical know-how would probably improve the clinical experience for patients and strengthen the future of spinal health.

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Ireland: Characterizing Mechanisms of Metallic 3D Printing Powder Recycling

In order to cut down on material waste, and save money, laboratories will often reuse leftover metal AM powder. A trio of researchers from the I-Form Advanced Manufacturing Research Centre in Ireland published a paper, “X-ray Tomography, AFM and Nanoindentation Measurements for Recyclability Analysis of 316L Powders in 3D Printing Process,” focusing on better understanding and characterizing the mechanisms of metallic powder recycling, and evaluating ” the extent of porosity in the powder particles,” in order to optimize how many times recycled powder can actually be reused in the powder bed fusion process.

Many “risk-tolerant applications,” like in the aviation and biomedical industries, will not use recycled powder, because any part abnormalities that can be traced back to the material can be unsafe and expensive. Parts 3D printed out of recycled powder need to have mechanical properties, like hardness and effective modulus, that are comparable to those of fresh powder parts.

“In order to reuse the recycled powders in the secondary manufacturing cycles, a thorough characterization is essential to monitor the surface quality and microstructure variation of the powders affected by the laser heat within the 3D printer. Most powders are at risk of surface oxidation, clustering and porosity formation during the AM process and it’s environment [1,2],” they explained. “Our latest analysis confirms the oxidation and the population of porous particles increase in recycled powders as the major risky changes in stainless steel 316L powder [3,4].”

A common practice before reusing recycled powders is sieving, but this doesn’t lower the porosity or surface oxidation of the particles. Additionally, “the subsequent use of recycled powder” can change the final part’s mechanical strength, and not for the better.

“Here, we report our latest effort to measure the distribution of porosity formed in the recycled powders using the X-ray computing technique and correlate those analyses to the mechanical properties of the powders (hardness and effective modulus) obtained through AFM roughness measurements and nanoindentation technique,” the researchers wrote.

They used stainless steel 316L powder, and printed nine 5 x 5 x 5 mm test cubes on an EOSINT M 280 SLM 3D printer. They removed the recycled powder from the powder bed with a vacuum, and then sieved it before use; after the prints were complete, they collected sample powders again and labeled them as recycled powders.

“Both virgin and recycled powders were analyzed by number of techniques including XCT and Nanoindentation. XCT was performed by X-ray computed tomography (XCT) measurements were performed with a Xradia 500 Versa X-ray microscope with 80 KV, 7 W accelerating voltage and 2 µm threshold for 3D scan,” they wrote.

“To measure the roughness of the virgin and recycled powder particles, we performed Atomic Force Microscopy (AFM) and confocal microscopy using the Bruker Dimension ICON AFM. The average roughness was calculated using the Gwyddion software to remove the noise and applying the Median Filter on the images as a non-linear digital filtering technique.”

The researchers also ran nanoindentation on multiple powder particles, under a force of 250 µN for no more than ten seconds, in order to determine “the impact of porosity on the hardness and effective modulus of the recycled powders,” and used an optical microscope to identify pore areas on the powder.

XCT imaging of powder. (a) 3D rendered image of 900 recorded CT images, (b) region of interest, (c) internal pores in particles indicated in a 2D slice, (d) identified pores inside particles after image processing.

The XCT images were analyzed, and “a region of interest” was chosen, seen above, from which pore size and interior particle distribution were extracted.

AFM image on a particle showing the boundary of mold and steel and the area where surface roughness was measured.

Software was used to process the AFM topography images of both the virgin and recycled powders, and the team applied nanoindentation on different locations of the particles, with a force of 250 µm.

(a) powder particles placed on hardening mold for nanoindentation, and (b) an indent applied on a particle surface.

They determined that the reused powder particles had about 10% more porosity than the virgin powder, and the average roughness of the powder particle surfaces was 4.29 nm for the virgin powder and 5.49 nm for the recycled; this means that 3D printing “may increase the surface roughness of the recycled particles.” Nanoindentation measurements show that the recycled powder has an average hardness of 207 GPa, and an average effective modulus of 9.60 GPa, compared to an average of 236 GPa and 9.87 GPa for the virgin powder, “which can be correlated to porosities created beneath the surface.”

Pore size distribution in virgin and recycled powders extracted from image processing on XCT measurements.

“The pore size in recycled powders has a wider distribution compared to virgin counterpart. The main population of pore size is around 1-5 µm in virgin powder which slightly reduces to bigger size but for a smaller population. There are also bigger pores in recycled powder but with a smaller population,” they noted. “On the other hand, looking at higher pore population in virgin powder (around 10 µm size), we believe that the out-diffusion of metallic elements to the surface occurs during laser irradiation.”

Surface roughness plots from AFM measurements on powder particles. Average roughness calculated by Gwyiddion software.

The recycled powder hardness, which is smaller than in the virgin powder, “could be attributed to higher pore density in recycled particles,” since porosity causes the powder to be “more vulnerable to the applied force resulted in smaller hardness.”

While change in grain size of the powder particles can lead to reduced mechanical properties, the team’s AFM and SEM results did not show much grain redistribution in the recycled powder. But, their nanoindentation and XCT results did find that higher powder porosity can decrease both the hardness and modulus of the particles, which “will damage the mechanical properties of the manufactured parts.”

Hardness and effective modulus of fresh and virgin particles by nanoindentation.

“We have previously presented our achievement on surface and size analysis using SEM and XPS analysis. Here, we focused on pore distribution in both powders and correlated that to surface roughness, hardness and effective modulus obtained from nanoindentation analysis of the powder particles,” the researchers concluded. “The results indicate that pores population is about 10% more in recycled powders affected by the laser heat and oxygen inclusion/trap in the powder, which in turn, increases the surface roughness but reduces the hardness and modulus of the recycled powders. The pores are filled with gases (such as Argon or Oxygen) since these gases are not able to skip the melt and have a lower solubility in the melt throughout the solidification process.”

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Ireland: Researchers Create Open-Source 3D Printer for Neurophysiology

Researchers Thomas Campbell and James F.X. Jones, both of the School of Medicine, University College Dublin, Ireland, have a created a new 3D printer for the medical field, detailing their work in the recently published ‘Design and implementation of a low cost, modular, adaptable and open-source XYZ positioning system for neurophysiology.’

The authors have created an open-source system that can be customized for a wide range of projects, relying on an XYZ positioning system capable of moving a sensor or probe. Like a gantry crane, this new FDM printer is run by a standard Raspberry Pi 3, Arduino Mega, RAMPS 1.4 motor shield, and NEMA17 bipolar stepper motors. The frame consists of 20×20 mm aluminum extrusion made with 3D printed parts, bolted together by brackets. ‘Entry cost’ for such a 3D printer was calculated at approximately $670.20.

With the integration of the Raspberry Pi 3, the authors were also able to incorporate the Open Computer Vision Library (OpenCV) stating that feature is what makes the system unique in comparison to other XYZ positioning systems. The open-source machine learning software library is used with automated movement, and the creators expect it to transform the exploration of mechanotransduction, the method for sensory neurons to change a mechanical stimulus to an electrical signal.

Movement of the 3D printer is controlled by the Arduino Mega, which in turn is controlled by the Raspberry Pi 3:

“Arranging the microcontrollers in this master-slave configuration permits the automation of complex movement paradigms through the Python3 programming language. The power source for the system depends on the intended use case. For neurophysiology a linear regulated 12 V DC power supply must be used to ensure low EMI how-ever for other applications a 12 V DC switching power supply suffices.”

Campbell and Jones chose PLA for the materials to print components, using a Prusa i3 MK3, modeling the calibration cube in Autodesk Fusion360, and stating that dimensions for each cube were measured with digital calipers six times. Supports were not necessary for any of the fabricated parts, all of which were designed with minimal overhang.

Wiring of XYZ System. (A) RAMPS 1.4 shield (top) and Arduino Mega (bottom). (B) RAMPS 1.4 shield and microstepping jumpers (top). RAMPS 1.4shield with microstepping jumper pins installed (bottom). Note, to enable 1/16 microstepping for each stepper motor, it is necessary to install three jumpers per motor as encircled. (C) A4988 stepper motor drivers shown individually (top) and installed on RAMPS 1.4 shield (bottom). (D) Connecting the LCD screen to the RAMPS 1.4 shield. First, the smart adapter module is seated on the pins at the end of the RAMPS 1.4 shield. Next, EXP1 and EXP2 on the smart module should be connected to their corresponding ports on the reverse of the LCD screen. (E) The Arduino Mega and Raspberry Pi 3 can be connected over USB using a type A male to type B male connector. (F) Wiring of limit switches and stepper motors to RAMPS 1.4 shield. Note both the color orientation for stepper motor wiring and the highlighted pins for limit switch wiring.10T. Campbell, J.F.X. Jones /HardwareX 7 (2020) e00098

Build instructions include:

  • Y-axis carriage assembly
  • X and Z axes assembly
  • Axis alignment
  • Electronics and wiring
  • Preparation of and uploading of Marlin firmware
  • Setup of the Raspberry Pi 3 & OpenCV
  • Creation of a terminal based operating system

For use in functional neurophysiology applications, the authors tested the machine to see if it was capable of prompting mechanotransduction within the muscle spindle. Activation thresholds were successfully shown for:

  • Stretch distance
  • Stretch velocity
  • Stretch acceleration

Stretching the muscle spindle to study mechanotransduction. (A) Afferent nerve activity from a stretched muscle spindle. Brief pulses of stretch wereapplied to the lumbrical every two seconds in order to elicit mechanotransduction from the muscle spindle. Each Stimulus pulse indicates the initiation of a stretch. Filtered nerve activity is represented in blue, unfiltered in green. (B) Mechanotransduction activation thresholds were assessed with gradual increments in the stretch distance, speed or acceleration. For this filtered unit, activation thresholds were observed at 14.0 mms x 1and 50 mms x 2. Increased stretch distance, speed or acceleration are associated with increased nerve activity (Filtered Spike Rate). (C) Overdraw of filtered nerve activity observed in(B) indicates that this was a single-unit recording. All data was recorded in Spike2 (Cambridge Electronic Design). ENG, Electroneurogram. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)18T. Campbell, J.F.X. Jones /HardwareX 7 (2020) e00098.

“The main limitations of the XYZ positioning system are mechanical in nature,” concluded the authors. “In our implementation, the X & Z axis assembly is tall and heavy and as such we opted to reduce the Y and Z axis travel speeds to 2 mms x 1and 5 mms x 1respectively. This reduction in speed preserves positional integrity of the system by reducing the likelihood of stepper motors stepping erroneously. However, the assembly can be adjusted to the desired specific use case and a simple reduction the size of the Z-axis would greatly reduce its inertia and permit positional accuracy at greater travel speeds.”

“All components and software utilized were open-source, free to access or available at low cost. Given the ease with which these components can be accessed and the potential that such a system offers, it is believed that other research groups may find this system an attractive and useful experimental tool.”

3D printers are being used—and created—for many purposes in medical applications like dental, bioprinting, also offering a wide range of tools for doctors and surgeons like medical models and instruments. What do you think of this news? Let us know your thoughts! Join the discussion of this and other 3D printing topics at 3DPrintBoard.com.

[Source / Images: ‘Design and implementation of a low cost, modular, adaptable and open-source XYZ positioning system for neurophysiology’]

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Addihive Offers Powder Control System, Strives to Accelerate 3D Printing Uptake

[Image: Addihive]

In County Limerick, Ireland, a young company is striving to accelerate the spread of additive manufacturing technology. Addihive is working to take metal additive manufacturing out of research and development settings and onto the manufacturing floor.

“Addihive enables serial additive manufacturing in highly-regulated aerospace and medical device industries through market leading innovative solutions,” said Patrick Byrnes, Addihive Research and Development Manager. “Additive manufacturing or 3D printing in metals is disrupting these global market segments at an accelerating pace where new approaches and engineering challenges are presented for part quality, system validation and process control.”

One of Addihive’s goals is to make the technology more efficient and save money by preventing material waste. The company has created a solution called Powder Loop, which sits on top of the 3D printer and monitors the printing process through all its stages. It collects metal particles for recycling and monitors the system’s levels of oxygen, nitrogen and hydrogen to ensure chemical integrity.

Patrick Byrnes [Image: Conor McCabe]

“Our mission is to streamline, complement and scale the additive process with our customer base through the implementation of proprietary technology and market-leading solutions,” said Byrnes. “We have been in operation since January 2017 with a team of three engineers and, to date, we have developed a number of patent-pending innovations across pre- and post-processing platforms. We had seen a relatively strong push on the marketing and uptake in additive manufacturing equipment with multinational customers, but nobody seemed to cater for the pre- and post-process ecosystem and we created a number of innovations to exponentially improve environmental health and safety, overall equipment efficiency and process quality.”

One of the appeals of Powder Loop is that it is small and fits right onto additive manufacturing machines, so it doesn’t take up any extra floor space. Proper powder handling is extremely important, not just for money-saving reasons but for safety as well.

“When you are moving metallic particles around at high velocity in a confined space it is like a grain silo and particles can ignite,” said Byrnes.

Powder Loop offers a safe way to handle excess powder, and to recycle it so that nothing is wasted. It also offers automation in the powder handling process. Addihive has a lot more in the pipeline beyond Powder Loop, as well – the company is working on proprietary part and powder removal techniques and machines, as well as a large scale powder management system that is capable of powder quality control for multiple 3D printers. Automation is a big focus for Addihive, as well, and it is working to implement collaborative robotics and the Internet of Things for cost effective, 24/7 production.

Addihive’s team of material scientists, additive technology engineers, quality engineers and advanced manufacturing engineers bring to the table several years of experience in the medical and aerospace additive industries, two of the fastest-growing sectors of additive manufacturing. That experience will go a long way toward accomplishing Addihive’s goal of boosting industrial additive manufacturing.

“Our vision is to accelerate the uptake of additive manufacturing and disruptive technologies from SMEs right through to multinationals,” said Byrnes.

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[Source: Irish Times]