Shlomi Laufer

Rescuing the Clinical Breast Examination: Advances in Classifying Technique and Assessing Physician Competency.

Objective: Develop new performance evaluation standards for the clinical breast examination (CBE). Summary Background Data: There are several, technical aspects of a proper CBE. Our recent work discovered a significant, linear relationship between palpation force and CBE accuracy. This article investigates the relationship between other technical aspects of the CBE and accuracy. Methods: This performance assessment study involved data collection from physicians (n = 553) attending 3 different clinical meetings between 2013 and 2014: American Society of Breast Surgeons, American Academy of Family Physicians, and American College of Obstetricians and Gynecologists. Four, previously validated, sensor-enabled breast models were used for clinical skills assessment. Models A and B had solitary, superficial, 2 cm and 1 cm soft masses, respectively. Models C and D had solitary, deep, 2 cm hard and moderately firm masses, respectively. Finger movements (search technique) from 1137 CBE video recordings were independently classified by 2 observers. Final classifications were compared with CBE accuracy. Results: Accuracy rates were model A = 99.6%, model B = 89.7%, model C = 75%, and model D = 60%. Final classification categories for search technique included rubbing movement, vertical movement, piano fingers, and other. Interrater reliability was (k = 0.79). Rubbing movement was 4 times more likely to yield an accurate assessment (odds ratio 3.81, P < 0.001) compared with vertical movement and piano fingers. Piano fingers had the highest failure rate (36.5%). Regression analysis of search pattern, search technique, palpation force, examination time, and 6 demographic variables, revealed that search technique independently and significantly affected CBE accuracy (P < 0.001). Conclusions: Our results support measurement and classification of CBE techniques and provide the foundation for a new paradigm in teaching and assessing hands-on clinical skills. The newly described piano fingers palpation technique was noted to have unusually high failure rates. Medical educators should be aware of the potential differences in effectiveness for various CBE techniques.

Evaluation of Simulated Clinical Breast Exam Motion Patterns Using Marker-Less Video Tracking.

Objective: This study investigates using marker-less video tracking to evaluate hands-on clinical skills during simulated clinical breast examinations (CBEs). Background: There are currently no standardized and widely accepted CBE screening techniques. Methods: Experienced physicians attending a national conference conducted simulated CBEs presenting different pathologies with distinct tumorous lesions. Single hand exam motion was recorded and analyzed using marker-less video tracking. Four kinematic measures were developed to describe temporal (time pressing and time searching) and spatial (area covered and distance explored) patterns. Results: Mean differences between time pressing, area covered, and distance explored varied across the simulated lesions. Exams were objectively categorized as either sporadic, localized, thorough, or efficient for both temporal and spatial categories based on spatiotemporal characteristics. The majority of trials were temporally or spatially thorough (78% and 91%), exhibiting proportionally greater time pressing and time searching (temporally thorough) and greater area probed with greater distance explored (spatially thorough). More efficient exams exhibited proportionally more time pressing with less time searching (temporally efficient) and greater area probed with less distance explored (spatially efficient). Just two (5.9 %) of the trials exhibited both high temporal and spatial efficiency. Conclusions: Marker-less video tracking was used to discriminate different examination techniques and measure when an exam changes from general searching to specific probing. The majority of participants exhibited more thorough than efficient patterns. Application: Marker-less video kinematic tracking may be useful for quantifying clinical skills for training and assessment.

Modeling Touch and Palpation Using Autoregressive Models

Objective: The human haptic system uses a set of reproducible and subconscious hand maneuvers to identify objects. Similar subconscious maneuvers are used during medical palpation for screening and diagnosis. The goal of this work was to develop a mathematical model that can be used to describe medical palpation techniques. Methods: Palpation data were measured using a two-dimensional array of force sensors. A novel algorithm for estimating the hand position from force data was developed. The hand position data were then modeled using multivariate autoregressive models. Analysis of these models provided palpation direction and frequency as well as palpation type. The models were tested and validated using three different data sets: simulated data, a simplified experiment in which participant followed a known pattern, and breast simulator palpation data. Results: Simulated data showed that the minimal error in estimating palpation direction and frequency is achieved when the sampling frequency is five to ten times the palpation frequency. The classification accuracy was

Use of simulators to explore specialty recommendation for a palpable breast mass

99\%

Characterizing Touch Using Pressure Data and Auto Regressive Models

for the simplified experiment and

Evaluation of hands-on clinical exam performance using marker-less video tracking

73\%

Use of decision-based simulations to assess resident readiness for operative independence

for the breast simulator data. Conclusion: Proper palpation is one of the vital components of many hands-on clinical examinations. In this study, an algorithm for characterizing medical palpation was developed. The algorithm measured palpation frequency and direction for the first time and provided classification of palpation type. Significance: These newly developed models can be used for quantifying and assessing clinical technique, and consequently, lead to improved performance in palpation-based exams. Furthermore, they provide a general tool for the study of human haptics.

Idle time: an underdeveloped performance metric for assessing surgical skill

BACKGROUND The aim of this study was to evaluate recommendation patterns of different specialties for the work-up of a palpable breast mass using simulated scenarios and clinical breast examination models. METHODS Study participants were a convenience sample of physicians (n = 318) attending annual surgical, family practice, and obstetrics and gynecology (OB/GYN) conferences. Two different silicone-based breast models (superficial mass vs chest wall mass) were used to test clinical breast examination skills and recommendation patterns (imaging, tissue sampling, and follow-up). RESULTS Participants were more likely to recommend mammography (P < .001) and core biopsy (P < .0001) and less likely to recommend needle aspiration (P < .043) and 1-month follow-up (P < .001) for the chest wall mass compared with the superficial mass. Family practitioners were less likely to recommend ultrasound (P < .001) and obstetrics and gynecologists were less likely to recommend mammogram (P < .006) across models. Surgeons were more likely to recommend core biopsy and less likely to recommend needle aspiration across models (P < .001). CONCLUSIONS Recommendation patterns differed across the 2 models in line with existing practice guidelines. Additionally, differences in practice patterns between primary care and specialty providers may represent varying clinician capabilities, healthcare resources, and individual preferences. Our work shows that simulation may be used to track adherence to practice guidelines for breast masses.

Working volume: validity evidence for a motion-based metric of surgical efficiency.

Palpation plays a critical role in medical physical exams. Despite the wide range of exams, there are several reproducible and subconscious sets of maneuvers that are common to examination by palpation. Previous studies by our group demonstrated the use of manikins and pressure sensors for measuring and quantifying how physicians palpate during different physical exams. In this study we develop mathematical models that describe some of these common maneuvers. Dynamic pressure data was measured using a simplified testbed and different autoregressive models were used to describe the motion of interest. The frequency, direction and type of motion used were identified from the models. We believe these models can a provide better understanding of how humans explore objects in general and more specifically give insights to understand medical physical exams.

Multimodality approach to classifying hand utilization for the clinical breast examination.

This study investigates the potential of using marker-less video tracking for evaluating hands-on clinical skills. Experienced family practitioners attending a national conference were recruited and asked to conduct a breast examination on a simulator that presents different clinical pathologies. Videos were taken of the clinician’s hands during the exam. Video processing software for tracking and quantifying hand motion kinematics was used. Videos were divided into two segments: a general search segment and a mass exploration segment. The general exploration segments exhibited motion patterns which included 72% faster movement and 73% higher acceleration across clinical pathologies. The most complex pathology exhibited 14% greater displacement for pressing/rubbing than for general exploration. Marker-less video kinematic tracking shows promise in discriminating between different examination procedures, clinicians, and pathologies.