Aliado - A design concept of AI for decision support in oncological liver surgery.

BACKGROUND: The interest in artificial intelligence (AI) is increasing. Systematic reviews suggest that there are many machine learning algorithms in surgery, however, only a minority of the studies integrate AI applications in clinical workflows. Our objective was to design and evaluate a concept to use different kinds of AI for decision support in oncological liver surgery along the treatment path. METHODS: In an exploratory co-creation between design experts, surgeons, and data scientists, pain points along the treatment path were identified. Potential designs for AI-assisted solutions were developed and iteratively refined. Finally, an evaluation of the design concept was performed with n = 20 surgeons to get feedback on the different functionalities and evaluate the usability with the System Usability Scale (SUS). Participating surgeons had a mean of 14.0 ± 5.0 years of experience after graduation. RESULTS: The design concept was named "Aliado". Five different scenarios were identified where AI could support surgeons. Mean score of SUS was 68.2 ( ± 13.6 SD). The highest valued functionalities were "individualized prediction of survival, short-term mortality and morbidity", and "individualized recommendation of surgical strategy". CONCLUSION: Aliado is a design prototype that shows how AI could be integrated into the clinical workflow. Even without a fleshed out user interface, the SUS already yielded borderline good results. Expert surgeons rated the functionalities favorably, and most of them expressed their willingness to work with a similar application in the future. Thus, Aliado can serve as a surgical vision of how an ideal AI-based assistance could look like.

A surgical activity model of laparoscopic cholecystectomy for co-operation with collaborative robots.

BACKGROUND: Laparoscopic cholecystectomy is a very frequent surgical procedure. However, in an ageing society, less surgical staff will need to perform surgery on patients. Collaborative surgical robots (cobots) could address surgical staff shortages and workload. To achieve context-awareness for surgeon-robot collaboration, the intraoperative action workflow recognition is a key challenge. METHODS: A surgical process model was developed for intraoperative surgical activities including actor, instrument, action and target in laparoscopic cholecystectomy (excluding camera guidance). These activities, as well as instrument presence and surgical phases were annotated in videos of laparoscopic cholecystectomy performed on human patients (n = 10) and on explanted porcine livers (n = 10). The machine learning algorithm Distilled-Swin was trained on our own annotated dataset and the CholecT45 dataset. The validation of the model was conducted using a fivefold cross-validation approach. RESULTS: In total, 22,351 activities were annotated with a cumulative duration of 24.9 h of video segments. The machine learning algorithm trained and validated on our own dataset scored a mean average precision (mAP) of 25.7% and a top K = 5 accuracy of 85.3%. With training and validation on our dataset and CholecT45, the algorithm scored a mAP of 37.9%. CONCLUSIONS: An activity model was developed and applied for the fine-granular annotation of laparoscopic cholecystectomies in two surgical settings. A machine recognition algorithm trained on our own annotated dataset and CholecT45 achieved a higher performance than training only on CholecT45 and can recognize frequently occurring activities well, but not infrequent activities. The analysis of an annotated dataset allowed for the quantification of the potential of collaborative surgical robots to address the workload of surgical staff. If collaborative surgical robots could grasp and hold tissue, up to 83.5% of the assistant's tissue interacting tasks (i.e. excluding camera guidance) could be performed by robots.

Ensuring privacy protection in the era of big laparoscopic video data: development and validation of an inside outside discrimination algorithm (IODA).

BACKGROUND: Laparoscopic videos are increasingly being used for surgical artificial intelligence (AI) and big data analysis. The purpose of this study was to ensure data privacy in video recordings of laparoscopic surgery by censoring extraabdominal parts. An inside-outside-discrimination algorithm (IODA) was developed to ensure privacy protection while maximizing the remaining video data. METHODS: IODAs neural network architecture was based on a pretrained AlexNet augmented with a long-short-term-memory. The data set for algorithm training and testing contained a total of 100 laparoscopic surgery videos of 23 different operations with a total video length of 207 h (124 min ± 100 min per video) resulting in 18,507,217 frames (185,965 ± 149,718 frames per video). Each video frame was tagged either as abdominal cavity, trocar, operation site, outside for cleaning, or translucent trocar. For algorithm testing, a stratified fivefold cross-validation was used. RESULTS: The distribution of annotated classes were abdominal cavity 81.39%, trocar 1.39%, outside operation site 16.07%, outside for cleaning 1.08%, and translucent trocar 0.07%. Algorithm training on binary or all five classes showed similar excellent results for classifying outside frames with a mean F1-score of 0.96 ± 0.01 and 0.97 ± 0.01, sensitivity of 0.97 ± 0.02 and 0.0.97 ± 0.01, and a false positive rate of 0.99 ± 0.01 and 0.99 ± 0.01, respectively. CONCLUSION: IODA is able to discriminate between inside and outside with a high certainty. In particular, only a few outside frames are misclassified as inside and therefore at risk for privacy breach. The anonymized videos can be used for multi-centric development of surgical AI, quality management or educational purposes. In contrast to expensive commercial solutions, IODA is made open source and can be improved by the scientific community.

Does speed equal quality? Time pressure impairs minimally invasive surgical skills in a prospective crossover trial.

BACKGROUND: Time pressure can cause stress, subsequently influencing surgeons during minimally invasive procedures. This trial aimed to investigate the effect of time pressure on surgical quality, as assessed by force application and errors during minimally invasive surgical tasks. METHODS: Sixty-three participants (43 surgical novices trained to proficiency and 20 surgeons) performed four laparoscopic tasks (PEG transfer, precise Cutting, balloon resection, surgical knot) both with and without time pressure. The primary endpoint was the mean and maximal force exertion during each task. Secondary endpoints were the occurrence of predefined errors and the self-assessed stress level. RESULTS: Time pressure led to a significant shortening of the task time in all four tasks. However, significantly more errors were noticed under time pressure in one task (suture precision P < 0.001). Moreover, time pressure led to a significant increase in mean force in all tasks (PEG: P < 0.001; precision cutting: P = 0.001; surgical knot: P < 0.001; balloon: P = 0.004). In three tasks the maximal force application (PEG: P < 0.001; precision cutting: P < 0.001; surgical knot: P = 0.006) increased significantly. Performing the tasks under time pressure significantly increased the stress level. Cohort analysis revealed that time pressure impaired the performance of both, surgical novices and surgeons but novices were more strongly affected compared to surgeons. CONCLUSION: Time pressure during minimally invasive surgery may improve procedural time but impair the quality of surgical performance in terms of the incidence of errors and force exertion. Experience may only partially compensate for the negative influence of time pressure.

[Technical innovations and future perspectives]. / Technische Innovationen und Blick in die Zukunft.

BACKGROUND: Digital systems have increasingly become integrated into the modern operating room in the last few decades. This has brought about a massive change, especially in minimally invasive surgery. OBJECTIVE: The article provides an overview of the current technical innovations and the perspectives of digitalization and artificial intelligence (AI) in surgery. MATERIAL AND METHODS: The article is based on a literature search via PubMed and research work by the participating coauthors. RESULTS: Current research is increasingly looking at machine learning techniques that take advantage of the complex data in surgery; however, the integration of artificial intelligence systems into the operating room and clinical practice has only just begun. DISCUSSION: Translational research of artificial intelligence in surgery is still in its infancy but has great potential to improve patient care; however, to accelerate the incorporation of intelligent systems into the clinical practice, the creation of interdisciplinary research groups led by surgeons is necessary.

A learning robot for cognitive camera control in minimally invasive surgery.

BACKGROUND: We demonstrate the first self-learning, context-sensitive, autonomous camera-guiding robot applicable to minimally invasive surgery. The majority of surgical robots nowadays are telemanipulators without autonomous capabilities. Autonomous systems have been developed for laparoscopic camera guidance, however following simple rules and not adapting their behavior to specific tasks, procedures, or surgeons. METHODS: The herein presented methodology allows different robot kinematics to perceive their environment, interpret it according to a knowledge base and perform context-aware actions. For training, twenty operations were conducted with human camera guidance by a single surgeon. Subsequently, we experimentally evaluated the cognitive robotic camera control. A VIKY EP system and a KUKA LWR 4 robot were trained on data from manual camera guidance after completion of the surgeon's learning curve. Second, only data from VIKY EP were used to train the LWR and finally data from training with the LWR were used to re-train the LWR. RESULTS: The duration of each operation decreased with the robot's increasing experience from 1704 s ± 244 s to 1406 s ± 112 s, and 1197 s. Camera guidance quality (good/neutral/poor) improved from 38.6/53.4/7.9 to 49.4/46.3/4.1% and 56.2/41.0/2.8%. CONCLUSIONS: The cognitive camera robot improved its performance with experience, laying the foundation for a new generation of cognitive surgical robots that adapt to a surgeon's needs.

Genome-wide association study of Stayability and Heifer Pregnancy in Red Angus cattle.

Reproductive performance is the most important component of cattle production from the standpoint of economic sustainability of commercial beef enterprises. Heifer Pregnancy (HPG) and Stayability (STAY) genetic predictions are 2 selection tools published by the Red Angus Association of America (RAAA) to assist with improvements in reproductive performance. Given the importance of HPG and STAY to the profitability of commercial beef enterprises, the objective of this study was to identify QTL associated with both HPG and STAY in Red Angus cattle. A genome-wide association study (GWAS) was performed using deregressed HPG and STAY EBV, calculated using a single-trait animal model and a 3-generation pedigree with data from the Spring 2015 RAAA National Cattle Evaluation. Each individual animal possessed 74,659 SNP genotypes. Individual animals with a deregressed EBV reliability > 0.05 were merged with the genotype file and marker quality control was performed. Criteria for sifting genotypes consisted of removing those markers where any of the following were found: average call rate less than 0.85, minor allele frequency < 0.01, lack of Hardy-Weinberg equilibrium (P < 0.0001), or extreme linkage disequilibrium (r2 > 0.99). These criteria resulted in 2,664 animals with 62,807 SNP available for GWAS. Association studies were performed using a Bayes Cπ model in the BOLT software package. Marker significance was calculated as the posterior probability of inclusion (PPI), or the number of instances a specific marker was sampled divided by the total number of samples retained from the Markov chain Monte Carlo chains. Nine markers, with a PPI ≥ 3% were identified as QTL associated with HPG on BTA 1, 11, 13, 23, and 29. Twelve markers, with a PPI ≥ 75% were identified as QTL associated with STAY on BTA 6, 8, 9, 12, 15, 18, 22, and 23.

SNP detection using RNA-sequences of candidate genes associated with puberty in cattle.

Fertility traits, such as heifer pregnancy, are economically important in cattle production systems, and are therefore, used in genetic selection programs. The aim of this study was to identify single nucleotide polymorphisms (SNPs) using RNA-sequencing (RNA-Seq) data from ovary, uterus, endometrium, pituitary gland, hypothalamus, liver, longissimus dorsi muscle, and adipose tissue in 62 candidate genes associated with heifer puberty in cattle. RNA-Seq reads were assembled to the bovine reference genome (UMD 3.1.1) and analyzed in five cattle breeds; Brangus, Brahman, Nellore, Angus, and Holstein. Two approaches used the Brangus data for SNP discovery 1) pooling all samples, and 2) within each individual sample. These approaches revealed 1157 SNPs. These were compared with those identified in the pooled samples of the other breeds. Overall, 172 SNPs within 13 genes (CPNE5, FAM19A4, FOXN4, KLF1, LOC777593, MGC157266, NEBL, NRXN3, PEPT-1, PPP3CA, SCG5, TSG101, and TSHR) were concordant in the five breeds. Using Ensembl's Variant Effector Predictor, we determined that 12% of SNPs were in exons (71% synonymous, 29% nonsynonymous), 1% were in untranslated regions (UTRs), 86% were in introns, and 1% were in intergenic regions. Since these SNPs were discovered in RNA, the variants were predicted to be within exons or UTRs. Overall, 160 novel transcripts in 42 candidate genes and five novel genes overlapping five candidate genes were observed. In conclusion, 1157 SNPs were identified in 62 candidate genes associated with puberty in Brangus cattle, of which, 172 were concordant in the five cattle breeds. Novel transcripts and genes were also identified.

Heritabilities and genetic correlations of pulmonary arterial pressure and performance traits in Angus cattle at high altitude.

Pulmonary arterial pressure (PAP) is an indicator trait for pulmonary hypertension and for the risk of developing high-altitude disease (HAD) in cattle. Pulmonary arterial pressures provide a tool for selection of breeding cattle for tolerance to high altitude in mountainous regions of the United States. The objective of this study was to evaluate relationships between growth performance traits and yearling PAP (42.4 ± 9.9 mmHg; = 5,776; elevation 2,150 m) using data from 1993 to 2014 in the John E. Rouse Colorado State University Beef Improvement Center (CSU-BIC) Angus herd. The breeding program used sires ( = 299) from both low- and high-elevation environments. We hypothesized that little to no genetic relationship exists between PAP and birth weight (BWT; direct and maternal), weaning weight (WW; direct and maternal), yearling weight (YW; direct and maternal), and postweaning gain (PWG). Historic selection of natural service sires from within the herd required a PAP of ≤ 42 mmHg. Outside AI sires ( = 156) used in this breeding program were not PAP tested and therefore were used with little knowledge of these sires' high-altitude adaptability. Performance traits (± SD) routinely recorded included BWT (36.2 ± 5.1 kg; = 8,695), WW (213.5 ± 31.8 kg; = 8,010), YW (345.6 ± 83.8 kg; = 5,580), and PWG (122.0 ± 63.7 kg; = 5,449), where PWG represented the total weight gained from weaning to yearling age. Four-trait analyses using REML were conducted with an animal model. The heritability estimates (± SE) for PAP (0.26 ± 0.03), BWT direct (0.42 ± 0.04) and maternal (0.14 ± 0.02), WW direct (0.29 ± 0.04) and maternal (0.19 ± 0.03), YW direct (0.45 ± 0.04) and maternal (0.23 ± 0.03), and PWG (0.14 ± 0.02) were in the range of those reported in previous literature. Estimates of genetic correlations (± SE) revealed weak relationships between PAP and direct and maternal BWT, direct and maternal WW, direct and maternal YW, and PWG of 0.15 ± 0.09, 0.14 ± 0.10, 0.23 ± 0.09, -0.01 ± 0.10, 0.12 ± 0.08, 0.00 ± 0.09, and -0.10 ± 0.10, respectively. The results of this study suggest that selection for lower PAP measures should have minimal influence on the growth performance of yearling Angus bulls and heifers at the CSU-BIC, supporting our hypothesis.

Genetic parameters estimated at receiving for circulating cortisol, immunoglobulin G, interleukin 8, and incidence of bovine respiratory disease in feedlot beef steers.

Bovine respiratory disease complex (i.e., shipping fever and bacterial bronchopneumonia) is a multifaceted respiratory illness influenced by numerous environmental factors and microorganisms. Bovine respiratory disease (BRD) is just one component of BRD complex. Because BRD is moderately heritable, it may be possible to reduce the incidence of BRD through genetic selection. The objectives of this study were to determine the heritability and associative genetic relationships among immune system traits (i.e., cortisol, total IgG, IgG isotypes, and IL-8) in cattle monitored for BRD incidence. At an average of 83 d after weaning (219 d age and mean = 221.7 kg [SD 4.34]), crossbred steer calves ( = 2,869) were received at a commercial feedlot in southeastern Colorado over a 2-yr period. At receiving, jugular blood samples were collected at 212 (yr 1) and 226 d (yr 2) of age for immune trait analyses. The BRD phenotype was defined as a binomial variable (0 = no and 1 = yes) and compared with immune system traits measured at receiving (prior to illness onset). An animal identified as BRD positive exhibited ≥ 2 clinical signs (i.e., eye or nasal discharge, cough, lethargy, rapid breathing, acute interstitial pneumonia, or acute upper respiratory syndrome and/or a rectal temperature > 39.7°C). Heritability and genetic correlation estimates for categorical variable BRD, cortisol, IgG, IgG1, IgG2, and IL-8 were estimated from a sire model using ASREML. Heritability estimates were low to moderate for BRD (0.17 ± 0.08), cortisol (0.13 ± 0.05), IgG (0.15 ± 0.05), IgG1 (0.11 ± 0.05), IgG2 (0.24 ± 0.06), and IL-8 (0.30 ± 0.06). A moderate negative genetic correlation was determined between BRD and cortisol ( = -0.19 ± 0.32). Moderate positive correlations were found between BRD with IgG (0.42 ± 0.28), IgG1 (0.36 ± 0.32), and IL-8 ( = 0.26 ± 0.26). Variation in the BRD phenotype and immune system traits suggested herd health improvement may be achieved through genetic selection.

Random regression models for the prediction of days to weight, ultrasound rib eye area, and ultrasound back fat depth in beef cattle.

Genetic evaluation research designed to reduce the required days to a specified end point has received very little attention in pertinent scientific literature, given that its economic importance was first discussed in 1957. There are many production scenarios in today's beef industry, making a prediction for the required number of days to a single end point a suboptimal option. Random regression is an attractive alternative to calculate days to weight (DTW), days to ultrasound back fat (DTUBF), and days to ultrasound rib eye area (DTUREA) genetic predictions that could overcome weaknesses of a single end point prediction. The objective of this study was to develop random regression approaches for the prediction of the DTW, DTUREA, and DTUBF. Data were obtained from the Agriculture and Agri-Food Canada Research Centre, Lethbridge, AB, Canada. Data consisted of records on 1,324 feedlot cattle spanning 1999 to 2007. Individual animals averaged 5.77 observations with weights, ultrasound rib eye area (UREA), ultrasound back fat depth (UBF), and ages ranging from 293 to 863 kg, 73.39 to 129.54 cm, 1.53 to 30.47 mm, and 276 to 519 d, respectively. Random regression models using Legendre polynomials were used to regress age of the individual on weight, UREA, and UBF. Fixed effects in the model included an overall fixed regression of age on end point (weight, UREA, and UBF) nested within breed to account for the mean relationship between age and weight as well as a contemporary group effect consisting of breed of the animal (Angus, Charolais, and Charolais sired), feedlot pen, and year of measure. Likelihood ratio tests were used to determine the appropriate random polynomial order. Use of the quadratic polynomial did not account for any additional genetic variation in days for DTW ( > 0.11), for DTUREA ( > 0.18), and for DTUBF ( > 0.20) when compared with the linear random polynomial. Heritability estimates from the linear random regression for DTW ranged from 0.54 to 0.74, corresponding to end points of 293 and 863 kg, respectively. Heritability for DTUREA ranged from 0.51 to 0.34 and for DTUBF ranged from 0.55 to 0.37. These estimates correspond to UREA end points of 35 and 125 cm and UBF end points of 1.53 and 30 mm, respectively. This range of heritability shows DTW, DTUREA, and DTUBF to be highly heritable and indicates that selection pressure aimed at reducing the number of days to reach a finish weight end point can result in genetic change given sufficient data.

Electromagnetic organ tracking allows for real-time compensation of tissue shift in image-guided laparoscopic rectal surgery: results of a phantom study.

BACKGROUND: Laparoscopic resection is a minimally invasive treatment option for rectal cancer but requires highly experienced surgeons. Computer-aided technologies could help to improve safety and efficiency by visualizing risk structures during the procedure. The prerequisite for such an image guidance system is reliable intraoperative information on iatrogenic tissue shift. This could be achieved by intraoperative imaging, which is rarely available. Thus, the aim of the present study was to develop and validate a method for real-time deformation compensation using preoperative imaging and intraoperative electromagnetic tracking (EMT) of the rectum. METHODS: Three models were compared and evaluated for the compensation of tissue deformation. For model A, no compensation was performed. Model B moved the corresponding points rigidly to the motion of the EMT sensor. Model C used five nested linear regressions with increasing level of complexity to compute the deformation (C1-C5). For evaluation, 14 targets and an EMT organ sensor were fit into a silicone-molded rectum of the OpenHELP phantom. Following a computed tomography, the image guidance was initiated and the rectum was deformed in the same way as during surgery in a total of 14 experimental runs. The target registration error (TRE) was measured for all targets in different positions of the rectum. RESULTS: The mean TRE without correction (model A) was 32.8 ± 20.8 mm, with only 19.6% of the measurements below 10 mm (80.4% above 10 mm). With correction, the mean TRE could be reduced using the rigid correction (model B) to 6.8 ± 4.8 mm with 78.7% of the measurements being <10 mm. Using the most complex linear regression correction (model C5), the error could be reduced to 2.9 ± 1.4 mm with 99.8% being below 10 mm. CONCLUSION: In laparoscopic rectal surgery, the combination of electromagnetic organ tracking and preoperative imaging is a promising approach to compensating for intraoperative tissue shift in real-time.

Optimum measurement period for evaluating feed intake traits in beef cattle.

The Beef Improvement Federation recommends residual feed intake (RFI) be calculated from 70-d tests preceded by a 21-d adjustment period. Individual animal feed intake and gain measurements are expensive and time consuming, which limits the number of animals available for national genetic evaluation of feed intake. If a shorter test period of comparable accuracy could be used, the cost would decrease and more animals could be tested annually. The objective of this study was to determine if data from shortened tests is equally as predictive of average daily DMI (ADMI) and RFI values from 70-d tests. Feed intake and weight measures were collected after weaning from Bos taurus bulls, steers, and heifers (n = 612) during four 70-d performance tests. For each individual, ADMI and RFI were calculated. Residual feed intake was calculated by regressing ADMI on metabolic midweight (MMWT) and ADG with the effect of breed included where appropriate. Based on four 70-d intake tests, ADMI, RFI, ADG, and MMWT were evaluated using shortened test lengths in a post hoc analysis where shortened test lengths were imposed on the full-period tests. The ADMI, RFI, ADG, and MMWT values from the full 70-d test were regressed on ADMI, RFI, ADG, and MMWT values resulting from the constructed shorter data subsets. The 8 subsets ranged from 14 to 56 d in length. The fixed effects of test, breed, animal's origin, and sex were included in each comparison for ADMI, ADG, and MMWT. Estimates for regression coefficients of ADMI values from a full test on various subsets ranged from 0.63 to 1.02. Likewise, estimated coefficients obtained from the regression of full test RFI, ADG, and MMWT values on subsets ranged from 0.50 to 1.00, 0.09 to 0.85, and 0.48 to 1.02, respectively. We conclude that ADMI values from a 42-d test ( < 0.0001) and RFI values from a 56-d test (P < 0.0001) adequately predict ADMI and RFI when compared to a 70-d test. These results suggest that testing periods of 42 d for determining ADMI and 56 d for RFI could ultimately reduce testing costs and result in collection of data on a larger number of animals per year, in turn resulting in more data for genetic evaluation.

OpenHELP (Heidelberg laparoscopy phantom): development of an open-source surgical evaluation and training tool.

BACKGROUND: Apart from animal testing and clinical trials, surgical research and laparoscopic training mainly rely on phantoms. The aim of this project was to design a phantom with realistic anatomy and haptic characteristics, modular design and easy reproducibility. The phantom was named open-source Heidelberg laparoscopic phantom (OpenHELP) and serves as an open-source platform. METHODS: The phantom was based on an anonymized CT scan of a male patient. The anatomical structures were segmented to obtain digital three-dimensional models of the torso and the organs. The digital models were materialized via rapid prototyping. One flexible, using an elastic abdominal wall, and one rigid method, using a plastic shell, to simulate pneumoperitoneum were developed. Artificial organ production was carried out sequentially starting from raw gypsum models to silicone molds to final silicone casts. The reproduction accuracy was exemplarily evaluated for ten silicone rectum models by comparing the digital 3D surface of the original rectum with CT scan by calculating the root mean square error of surface variations. Haptic realism was also evaluated to find the most realistic silicone compositions on a visual analog scale (VAS, 0-10). RESULTS: The rigid and durable plastic torso and soft silicone organs of the abdominal cavity were successfully produced. A simulation of pneumoperitoneum could be created successfully by both methods. The reproduction accuracy of ten silicone rectum models showed an average root mean square error of 2.26 (0-11.48) mm. Haptic realism revealed an average value on a VAS of 7.25 (5.2-9.6) for the most realistic rectum. CONCLUSION: The OpenHELP phantom proved to be feasible and accurate. The phantom was consecutively applied frequently in the field of computer-assisted surgery at our institutions and is accessible as an open-source project at www.open-cas.org for the academic community.

Comparative validation of single-shot optical techniques for laparoscopic 3-D surface reconstruction.

Intra-operative imaging techniques for obtaining the shape and morphology of soft-tissue surfaces in vivo are a key enabling technology for advanced surgical systems. Different optical techniques for 3-D surface reconstruction in laparoscopy have been proposed, however, so far no quantitative and comparative validation has been performed. Furthermore, robustness of the methods to clinically important factors like smoke or bleeding has not yet been assessed. To address these issues, we have formed a joint international initiative with the aim of validating different state-of-the-art passive and active reconstruction methods in a comparative manner. In this comprehensive in vitro study, we investigated reconstruction accuracy using different organs with various shape and texture and also tested reconstruction robustness with respect to a number of factors like the pose of the endoscope as well as the amount of blood or smoke present in the scene. The study suggests complementary advantages of the different techniques with respect to accuracy, robustness, point density, hardware complexity and computation time. While reconstruction accuracy under ideal conditions was generally high, robustness is a remaining issue to be addressed. Future work should include sensor fusion and in vivo validation studies in a specific clinical context. To trigger further research in surface reconstruction, stereoscopic data of the study will be made publically available at www.open-CAS.com upon publication of the paper.

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery.

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-operative morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon's navigation capabilities by observing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted instruments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D optical imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions.

Genetic parameters for intramuscular fat percentage, marbling score, scrotal circumference, and heifer pregnancy in Red Angus cattle.

Selection criteria for yearling bulls commonly include indicators of fertility and carcass merit, such as scrotal circumference (SC) and intramuscular fat percentage (IMF). Genetic correlation estimates between ultrasound traits such as IMF and carcass marbling score (MS) with fertility traits SC and heifer pregnancy (HP) have not been reported. Therefore, the objective of this study was to estimate the genetic parameters among the indicator traits IMF and SC, and the economically relevant traits MS and HP. Records for IMF (n=73,051), MS (n=15,260), SC (n=43,487), and HP (n=37,802) were obtained from the Red Angus Association of America, and a 4-generation ancestral pedigree (n=10,460) was constructed from the 8,915 sires represented in the data. (Co)variance components were estimated using a multivariate sire model and average information REML to obtain estimates of heritability and genetic correlations. Fixed effects included contemporary group and the linear effect of age at measurement for all traits, and an additional effect of age of dam for both HP and SC. The random effect of sire was included to estimate additive genetic effects, which were assumed to be continuous for IMF, MS, and SC, but a probit threshold link function was fitted for HP. Generally moderate heritability estimates of 0.29 ± 0.01, 0.35 ± 0.06, 0.32 ± 0.02, and 0.17 ± 0.01 were obtained for IMF, MS, SC, and HP on the underlying scale, respectively. The confidence interval for the estimated genetic correlation between MS and HP (0.10 ± 0.15) included zero, suggesting a negligible genetic association. The genetic correlation between MS and IMF was high (0.80 ± 0.05), but the estimate for HP and SC (0.05 ± 0.09) was near zero, as were the estimated genetic correlations of SC with MS (0.01 ± 0.08) and IMF (0.05 ± 0.06), and for HP with IMF (0.13 ± 0.09). These results suggest that concomitant selection for increased fertility and carcass merit would not be antagonistic.

Genetic analysis of longitudinal data in beef cattle: a review.

Currently, many different data types are collected by beef cattle breed associations for the purpose of genetic evaluation. These data points are all biological characteristics of individual animals that can be measured multiple times over an animal's lifetime. Some traits can only be measured once on an individual animal, whereas others, such as the body weight of an animal as it grows, can be measured many times. Data such as growth has been often referred to as "longitudinal" or "infinite-dimensional" since it is theoretically possible to observe the trait an infinite number of times over the life span of a given individual. Analysis of such data is not without its challenges, and as a result many different methods have been or are beginning to be implemented in the genetic analysis of beef cattle data, each an improvement over its predecessor. These methods of analysis range from the classic repeated measures to the more contemporary suite of random regressions that use covariance functions or even splines as their base function. Each of the approaches has both strengths and weaknesses in the analysis of longitudinal data. Here we summarize past and current genetic evaluation technology for analyzing this type of data and review some emerging technologies beginning to be implemented in national cattle evaluation schemes, along with their potential implications for the beef industry.

Genetic diversity and population structure of American Red Angus cattle.

The objective of this study was to characterize the population structure and genetic diversity of registered American Red Angus cattle. Inbreeding and average relationship coefficients, effective population size, effective number of founders, and effective number of herds supplying grandparents to the population were calculated from the recorded pedigree. Inbreeding in 1960 was 10.7% and decreased until 1974 at a rate of 0.2% per year, whereas in 1975 inbreeding was 3.2% and increased until 2005 at a rate of 0.02% per year. The numerator relationship coefficients of the 10 individual paternal grandsires (PGS; sires of sires), paternal granddams (PGD; dams of sires), maternal grandsires (MGS; sires of dams), and maternal granddams (MGD; dams of dams) that had the greatest number of registered grandprogeny, with all other registered animals, increased with their birth year from 1960 on. Average numerator relationships of these with all other PGS, PGD, MGS, MGD, bulls, and sires were greater for paternal (PGS, PGD) than maternal (MGS, MGD) pathways. The effective population size was 445, with 649 effective founders. The effective numbers of herds supplying PGS, PGD, MGS, and MGD were 435, 369, 453, and 459, respectively. Inbreeding is at a low level and the effective population size is large. The effective number of founders and effective number of herds supplying grandparents is small in relation to the total number of animals and herds, indicating the disproportionate influence of a few founders and herds on the genetics of the breed. The calculated parameters indicate satisfactory genetic diversity in American Red Angus cattle.