Swedish national prostate biopsy and MRI report template.

<p>1) Side (sagittal) view of the prostate, 2) ventral (coronal) view of the prostate, 3) transverse (axial) sections A-C of pictures 1) and 2). The study participants used this diagram without the colour lines to plot the prostate tumor location. The correctly plotted tumor location of case 3 is shown in the diagram (pink areas). For the scoring system picture 1) was divided in an anterior and posterior half (green line), picture 2) in a right and left half (red line) and picture 3 A-C in quadrants (blue, orange, yellow, turquoise). (MRI) magnetic resonance imaging; (SV) seminal vesicle; (a) anterior; (p) posterior; broken lines in picture 1) mark the urethra.</p

Scoring results (median with IQR) for group 1 (expert urologists) and group 2 (medical students), sub-classified for pictures 1–3 of the prostate template (side (sagittal) view, ventral (coronal) view, overall transverse (axial) view (ABC)) (s. Fig 1) in information tool A (written MRI report), information tool B (3D printed model) and information tool C (MRI presentation in MDT).

<p>Scoring results (median with IQR) for group 1 (expert urologists) and group 2 (medical students), sub-classified for pictures 1–3 of the prostate template (side (sagittal) view, ventral (coronal) view, overall transverse (axial) view (ABC)) (s. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199477#pone.0199477.g001" target="_blank">Fig 1</a>) in information tool A (written MRI report), information tool B (3D printed model) and information tool C (MRI presentation in MDT).</p

Summarized rates (%) of (A) major mistakes (s. Table 4A1) and (B) rates (%) of complete major accuracy (0% major mistakes) (s. Table 4A2) in group 1 (expert urologists) and group 2 (medical students) subdivided for information tools A-C.

<p>Summarized rates (%) of (A) major mistakes (s. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199477#pone.0199477.t004" target="_blank">Table 4A1</a>) and (B) rates (%) of complete major accuracy (0% major mistakes) (s. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199477#pone.0199477.t004" target="_blank">Table 4A2</a>) in group 1 (expert urologists) and group 2 (medical students) subdivided for information tools A-C.</p

Prostate cancer lesion of case 3 according to 3D printed prostate model, MRI and prostate template.

<p>In (1) corresponding side (sagittal) views and (2) according to ventral (coronal) views in 3D printed prostate model and prostate template and different sequences of the corresponding axial view in MRI (corresponds to broken line in section B). (SV) seminal vesicle, (a) anterior, (p) posterior. Arrows indicate prostate cancer in MRI.</p

Data Sheet 1_Autonomous surgical robotic systems and the liability dilemma.pdf

BackgroundAdvances in machine learning and robotics have allowed the development of increasingly autonomous robotic systems which are able to make decisions and learn from experience. This distribution of decision-making away from human supervision poses a legal challenge for determining liability.MethodsThe iRobotSurgeon survey aimed to explore public opinion towards the issue of liability with robotic surgical systems. The survey included five hypothetical scenarios where a patient comes to harm and the respondent needs to determine who they believe is most responsible: the surgeon, the robot manufacturer, the hospital, or another party.ResultsA total of 2,191 completed surveys were gathered evaluating 10,955 individual scenario responses from 78 countries spanning 6 continents. The survey demonstrated a pattern in which participants were sensitive to shifts from fully surgeon-controlled scenarios to scenarios in which robotic systems played a larger role in decision-making such that surgeons were blamed less. However, there was a limit to this shift with human surgeons still being ascribed blame in scenarios of autonomous robotic systems where humans had no role in decision-making. Importantly, there was no clear consensus among respondents where to allocate blame in the case of harm occurring from a fully autonomous system.ConclusionsThe iRobotSurgeon Survey demonstrated a dilemma among respondents on who to blame when harm is caused by a fully autonomous surgical robotic system. Importantly, it also showed that the surgeon is ascribed blame even when they have had no role in decision-making which adds weight to concerns that human operators could act as “moral crumple zones” and bear the brunt of legal responsibility when a complex autonomous system causes harm.</p