A novel, automated workflow to capture and analyse confocal images of Organ-Chips allowing detailed assessment of cellular phenotype in situ.

Background Millions of non-locking screws are manually tightened during surgery each year, but their insertion frequently results in overtightening and damage to the surrounding bone. We postulated that by calculating the torque limit of a screw hole, using bone and screw properties, the risk of overtightening during screw insertion could be reduced. Additionally, predicted maximum torque could be used to identify optimum screw torque, as a percentage of the maximum, based on applied compression and residual pullout strength. Methods Longitudinal cross-sections were taken from juvenile bovine tibial diaphyses, a validated surrogate of human bone, and 3.5 mm cortical non-locking screws were inserted. Fifty-four samples were used to define the association between stripping torque and cortical thickness. The relationship derived enabled prediction of insertion torques representing 40 to 100% of the theoretical stripping torque (T str) for a further 170 samples. Screw-bone compression generated during insertion was measured, followed immediately by axial pullout testing. Findings Screw-bone compression increased linearly with applied torque up to 80% of T str (R 2 =0.752, p<0.001), but beyond this, no significant further compression was generated. After screw insertion, with all screw threads engaged, more tightening did not create any significant (R 2 =0.000, p=0.498) increase in pullout strength. Interpretation Increasing screw tightness beyond 80% of the maximum did not increase screw-bone compression. Variations in torques below T str , did not affect pullout forces of inserted screws. Further validation of these findings in human bone and creation of clinical guidelines based on this research approach should improve surgical outcomes and reduce operative costs.

IntroductionIn oncological drug development, animal studies continue to play a central role in which the volume of subcutaneous tumours is monitored to assess the efficacy of new drugs. The tumour volume is estimated by taking the volume to be that of a regular spheroid with the same dimensions. However, this method is subjective, insufficiently traceable, and is subject to error in the accuracy of volume estimates as tumours are frequently irregular.Methods & resultsThis paper reviews the standard technique for tumour volume assessment, calliper measurements, by conducting a statistical review of a large dataset consisting of 2,500 tumour volume measurements from 1,600 mice by multiple operators across 6 mouse strains and 20 tumour models. Additionally, we explore the impact of six different tumour morphologies on volume estimation and the detection of treatment effects using a computational tumour growth model. Finally, we propose an alternative method to callipers for estimating volume–BioVolumeTM, a 3D scanning technique. BioVolume simultaneously captures both stereo RGB (Red, Green and Blue) images from different light sources and infrared thermal images of the tumour in under a second. It then detects the tumour region automatically and estimates the tumour volume in under a minute. Furthermore, images can be processed in parallel within the cloud and so the time required to process multiple images is similar to that required for a single image. We present data of a pre-production unit test consisting of 297 scans from over 120 mice collected by four different operators.ConclusionThis work demonstrates that it is possible to record tumour measurements in a rapid minimally invasive, morphology-independent way, and with less human-bias compared to callipers, whilst also improving data traceability. Furthermore, the images collected by BioVolume may be useful, for example, as a source of biomarkers for animal welfare and secondary drug toxicity / efficacy.

Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high health and social care costs. Given projected population ageing, the number of incident hip fractures is predicted to increase globally. As fracture classification strongly determines the chosen surgical treatment, differences in fracture classification influence patient outcomes and treatment costs. We aimed to create a machine learning method for identifying and classifying hip fractures, and to compare its performance to experienced human observers. We used 3659 hip radiographs, classified by at least two expert clinicians. The machine learning method was able to classify hip fractures with 19% greater accuracy than humans, achieving overall accuracy of 92%.

15In oncological drug development, animal studies continue to play a central role in which the 16 volume of subcutaneous tumours is monitored to assess the efficacy of new drugs. Tumour 17 volume is currently estimated by measuring length and width with callipers and then 18 estimating the volume of the tumour as if it were a regular spheroid. However, this method is 19 subjective, insufficiently traceable, and is subject to error in the accuracy of volume 20 estimates as tumours frequently are irregular. 21This paper explores the extent of inconsistencies in calliper measurements by conducting a 22 statistical review of a large dataset consisting of 2,500 tumour volume measurements from 23 1,600 mice by multiple operators across 6 mouse strains and 20 tumour models. We also 24 explore the impact of six different tumour morphologies on volume estimation and the 25 detection of treatment effects using a computational tumour growth model. Finally, we 26 propose an alternative method to callipers for estimating volume -BioVolume TM , a 3D 27 scanning technique. BioVolume simultaneously captures both stereo RGB (Red, Green and 28 Blue) images from different light sources and infrared thermal images of the tumour. It 29 detects the tumour region automatically and estimates the tumour volume in under a second. 30 BioVolume has been tested on a dataset of 297 scans from over 120 mice collected by four 31 different operators. 32 This work demonstrates that it is possible to record tumour measurements in a rapid, 33 minimally invasive, morphology-independent way, and with less human-bias compared to 34 callipers, whilst also improving data traceability. Furthermore, the images collected by 35 BioVolume may be useful, for example, as a source of biomarkers for animal welfare and 36 secondary drug toxicity / efficacy. 3 37