Quantitative BOLD imaging at 3T: Temporal changes in hepatocellular carcinoma and fibrosis following oxygen challenge.

PURPOSE: To evaluate the utility of oxygen challenge and report on temporal changes in blood oxygenation level-dependent (BOLD) contrast in normal liver, hepatocellular carcinoma (HCC) and background fibrosis. MATERIALS AND METHODS: Eleven volunteers (nine male and two female, mean age 33.5, range 27-41 years) and 10 patients (nine male and one female, mean age 68.9, range 56-87 years) with hepatocellular carcinoma on a background of diffuse liver disease were recruited. Imaging was performed on a 3T system using a multiphase, multiecho, fast gradient echo sequence. Oxygen was administered via a Hudson mask after 2 minutes of free-breathing. Paired t-tests were performed to determine if the mean pre- and post-O2 differences were statistically significant. RESULTS: In patients with liver fibrosis (n = 8) the change in T2* following O2 administration was elevated (0.88 ± 0.582 msec, range 0.03-1.69 msec) and the difference was significant (P = 0.004). The magnitude of the BOLD response in patients with HCC (n = 10) was larger, however the response was more variable (1.07 ± 1.458 msec, range -0.93-3.26 msec), and the difference was borderline significant (P = 0.046). The BOLD response in the volunteer cohort was not significant (P = 0.121, 0.59 ± 1.162 msec, range -0.81-2.44 msec). CONCLUSION: This work demonstrates that the BOLD response following oxygen challenge within cirrhotic liver is consistent with a breakdown in vascular autoregulatory mechanisms. Similarly, the elevated BOLD response within HCC is consistent with the abnormal capillary vasculature within tumors and the arterialization of the blood supply. Our results suggest that oxygen challenge may prove a viable BOLD contrast mechanism in the liver. J. Magn. Reson. Imaging 2016;44:739-744.This study was supported by the Addenbrooke’s Charitable Trust, Cambridge’s Experimental Cancer Medicine Centre and a NIHR comprehensive Biomedical Research Centre award to Cambridge University Hospitals NHS Foundation Trust in partnership with the University of Cambridge.This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/jmri.2518

Turning Fake Data into Fake News: AI Training Set as a Trojan Horse of Misinformation

Generative artificial intelligence (AI) offers tremendous benefits to society. However, these benefits must be carefully weighed against the societal damage AI can also cause. Dangers posed by inaccurate training sets have been raised by many authors. These include racial discrimination, sexual bias, and other pernicious forms of misinformation. One remedy to such problems is to ensure that training sets used to teach AI models are correct and that the data upon which they rely are accurate. An assumption behind this correction is that data inaccuracies are inadvertent mistakes. However, a darker possibility exists: the deliberate seeding of training sets with inaccurate information for the purpose of skewing the output of AI models toward misinformation. As United States Supreme Court Justice Oliver Wendell Holmes, Jr., suggested, laws are not written for the “good man,” because good people will tend to obey moral and legal principles in manners consistent with a well-functioning society even in the absence of formal laws. Rather, Justice Holmes proposed, that laws should be written with the “bad man” in mind, because bad people will push the limits of acceptable behavior, engaging in cheating, dishonesty, crime, and other societally- damaging practices, unless constrained by carefully-designed laws and their accompanying penalties. This Article raises the spectre of the deliberate sabotage of training sets used to train AI models, with the purpose of perverting the outputs of such models. Examples include fostering revisionist histories, unjustly harming or rehabilitating the reputations of people, companies, or institutions, or even promoting as true ideas that are not. Strategic and clever efforts to introduce ideas into training sets that later manifest themselves as facts could aid and abet fraud, libel, slander, or the creation of “truth,” the belief in which promote the interests of particular individuals or groups. Imagine, for example, a first investor who buys grapefruit futures, who then seeds training sets with the idea that grapefruits will become the new gold, with the result that later prospective investors who consult AI models for investment advice are informed that they should invest in grapefruit, enriching the first investor. Or, consider a malevolent political movement that hopes to rehabilitate the reputation of an abhorrent leader; if done effectively, this movement could seed training sets with sympathetic information about this leader, resulting in positive portrayals of this leader in the future outputs of trained AI models. This Article adopts the cautious attitude necessitated by Justice Holmes’ bad man, applying it to proactively stopping, or retroactively punishing and correcting, deliberate attempts to subvert the training sets of AI models. It offers legal approaches drawn from doctrines ranging from fraud, nuisance, libel, and slander, to misappropriation, privacy, and right of publicity. It balances these with protections for speech afforded by the First Amendment and other doctrines of free speech. The result is the first comprehensive attempt to prevent, respond to, and correct deliberate attempts to subvert training sets of AI models for malicious purposes

Errors of Measurement for Blood Parameters and Physiological and Performance Measures After the Decay of Short-Term Heat Acclimation

Introduction: It is important to determine the accuracy of measurements relative to potential treatment effects, with time intervals between tests. Purpose: The aim of this study was to assess the error of measurement for blood parameters, physiological, and performance measures after the decay of short-term heat acclimation. Methods: Ten trained males (Mean±SD: age 28±7 y; body mass 74.6±4.4 kg; 4.26±0.37 L.min-1; peak power output (PPO) 329±42 W) completed an exercising heat stress test (HST) at baseline, 2nd day after acclimation and then during decay at 1, 2, 3 and 5-6 wks. CoV (95% CI), SE (95% CI) and Pearsons (r) were used for analysis of blood volume (blood, plasma, red cell volume, mean hemoglogin mass); plasma (aldosterone, arginine vasopressin [AVP], total protein, albumin, sodium); physiological (rectal temperature, cardiac frequency) and performance (exercise performance capacity, PPO). Results: The CoV (95% CI), SE (95% CI) and r with a 1-wk interval for blood volume was 2.3% (1.6 to 4.3; 1.9 [1.3 to 3.4 mL.Kg-1]; r=0.93; n=10). After 2-wk and 5-6 wks this had increased to 4.9% (3.4 to 9.3; 3.8 [2.6 to 7.0 mL.Kg-1]; r=0.76; n=9) and 5.5% (3.6 to 12.8; 4.5 [2.9 to 10.0 mL.Kg-1]; r=0.65; n=7) respectively. Conclusions: Blood volume and physiological measures demonstrated the least error one week apart but increased thereafter. Plasma concentrations and performance markers had the greatest error with repeat measures after one week. Therefore, for greater reliability and low measurement error measures should be taken no more than one week a part in repeated experimentation

Errors of measurement for blood parameters, physiological and performance measures after the decay of short-term heat acclimation

Introduction: It is important to determine the accuracy of measurements relative to potential treatment effects, with time intervals between tests. Purpose: The aim of this study was to assess the error of measurement for blood parameters, physiological, and performance measures after the decay of short-term heat acclimation. Methods: Ten trained males (Mean±SD: age 28±7 y; body mass 74.6±4.4 kg; 4.26±0.37 L.min-1; peak power output (PPO) 329±42 W) completed an exercising heat stress test (HST) at baseline, 2nd day after acclimation and then during decay at 1, 2, 3 and 5-6 wks. CoV (95% CI), SE (95% CI) and Pearsons (r) were used for analysis of blood volume (blood, plasma, red cell volume, mean hemoglogin mass); plasma (aldosterone, arginine vasopressin [AVP], total protein, albumin, sodium); physiological (rectal temperature, cardiac frequency) and performance (exercise performance capacity, PPO). Results: The CoV (95% CI), SE (95% CI) and r with a 1-wk interval for blood volume was 2.3% (1.6 to 4.3; 1.9 [1.3 to 3.4 mL.Kg-1]; r=0.93; n=10). After 2-wk and 5-6 wks this had increased to 4.9% (3.4 to 9.3; 3.8 [2.6 to 7.0 mL.Kg-1]; r=0.76; n=9) and 5.5% (3.6 to 12.8; 4.5 [2.9 to 10.0 mL.Kg-1]; r=0.65; n=7) respectively. Conclusions: Blood volume and physiological measures demonstrated the least error one week apart but increased thereafter. Plasma concentrations and performance markers had the greatest error with repeat measures after one week. Therefore, for greater reliability and low measurement error measures should be taken no more than one week a part in repeated experimentation

The use of error-category mapping in pharmacokinetic model analysis of dynamic contrast-enhanced MRI data.

This study introduces the use of 'error-category mapping' in the interpretation of pharmacokinetic (PK) model parameter results derived from dynamic contrast-enhanced (DCE-) MRI data. Eleven patients with metastatic renal cell carcinoma were enrolled in a multiparametric study of the treatment effects of bevacizumab. For the purposes of the present analysis, DCE-MRI data from two identical pre-treatment examinations were analysed by application of the extended Tofts model (eTM), using in turn a model arterial input function (AIF), an individually-measured AIF and a sample-average AIF. PK model parameter maps were calculated. Errors in the signal-to-gadolinium concentration ([Gd]) conversion process and the model-fitting process itself were assigned to category codes on a voxel-by-voxel basis, thereby forming a colour-coded 'error-category map' for each imaged slice. These maps were found to be repeatable between patient visits and showed that the eTM converged adequately in the majority of voxels in all the tumours studied. However, the maps also clearly indicated sub-regions of low Gd uptake and of non-convergence of the model in nearly all tumours. The non-physical condition ve ≥ 1 was the most frequently indicated error category and appeared sensitive to the form of AIF used. This simple method for visualisation of errors in DCE-MRI could be used as a routine quality-control technique and also has the potential to reveal otherwise hidden patterns of failure in PK model applications.This work was supported by GlaxoSmithKline UK, Wellcome Trust, Cambridge NIHR Biomedical Research Centre, Cambridge Experimental Cancer Medicine Centre, Cancer Research UKThis is the published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0730725X1400321X

Safe Supervisory Control of Soft Robot Actuators

Although soft robots show safer interactions with their environment than traditional robots, soft mechanisms and actuators still have significant potential for damage or degradation particularly during unmodeled contact. This article introduces a feedback strategy for safe soft actuator operation during control of a soft robot. To do so, a supervisory controller monitors actuator state and dynamically saturates control inputs to avoid conditions that could lead to physical damage. We prove that, under certain conditions, the supervisory controller is stable and verifiably safe. We then demonstrate completely onboard operation of the supervisory controller using a soft thermally-actuated robot limb with embedded shape memory alloy (SMA) actuators and sensing. Tests performed with the supervisor verify its theoretical properties and show stabilization of the robot limb's pose in free space. Finally, experiments show that our approach prevents overheating during contact (including environmental constraints and human contact) or when infeasible motions are commanded. This supervisory controller, and its ability to be executed with completely onboard sensing, has the potential to make soft robot actuators reliable enough for practical use