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EP-4142624-B1 - PREDICTION OF TISSUE IRREGULARITIES BASED ON BIOMARKER MONITORING

EP4142624B1EP 4142624 B1EP4142624 B1EP 4142624B1EP-4142624-B1

Inventors

  • SHELTON, IV, FREDERICK E.
  • HARRIS, JASON L.
  • ECKERT, Chad E.

Dates

Publication Date
20260506
Application Date
20220121

Claims (14)

  1. A computing system comprising a processor (20236) configured to at least: obtain, via at least one sensing system, measurement data associated with at least one patient biomarker; predict a tissue irregularity complication based on the measurement data associated with the at least one patient biomarker, wherein the tissue irregularity complication comprises at least one of: a tissue thickness irregularity, a tissue density irregularity, a tissue compressibility irregularity, or a tissue stiffness irregularity; and generate an output based on the predicted tissue irregularity complication.
  2. The computing system of claim 1, wherein the processor is further configured to: determine, based on the predicted tissue irregularity complication, a control signal configured to alter an operational parameter associated with a surgical device, wherein the output comprises the control signal.
  3. The computing system of claim 1 or claim 2, wherein the output comprises a control signal configured to control a surgical cutting and stapling device to perform at least one of: prolonging a tissue creep wait time prior to stapling; reducing a clamping speed; reducing a stapler firing speed; increasing a closure compression force; or shifting upward a viable staple height range.
  4. The computing system of any preceding claim, wherein the output comprises a control signal configured to control a surgical energy device to perform at least one of: increasing an energy level; increasing an energy application duration; or increasing a threshold for an energy generation associated with a subsequent energy application.
  5. The computing system of any preceding claim, wherein the processor is further configured to: determine a probability of a chronic inflammation response based on the measurement data associated with the at least one patient biomarker, wherein the tissue irregularity complication is predicted based on the probability of a chronic inflammation response crossing a threshold and the at least one patient biomarker includes at least one of: tissue perfusion pressure, lactate, oxygen saturation, maximal oxygen consumption (VO2 max), respiration rate, autonomic tone, sweat rate, heart rate variability, skin conductance, or gastrointestinal (GI) motility.
  6. The computing system of any preceding claim, wherein the processor is further configured to: determine a probability of an irregular water retention level based on the measurement data associated with the at least one patient biomarker, wherein the tissue irregularity complication is predicted based on the probability of a water retention level crossing a threshold and the at least one patient biomarker includes at least one of: edema or hydration state.
  7. The computing system of any preceding claim, wherein at least one patient biomarker comprises local edema, a weight change and albumin level, and the processor is further configured to: determine an edema severity based on the local edema, a weight change and an albumin level change, wherein the tissue irregularity complication is predicted when the determined edema severity exceeds a threshold.
  8. The computing system of any preceding claim, wherein the tissue irregularity complication is associated with a pulmonary procedure, and the measurement data is associated with at least one of forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), or FEV1 to FVC ratio, wherein the processor is further configured to: determine a pulmonary function metric based on at least one of FEV1, FVC, or FEV1 to FVC ratio, wherein the tissue irregularity complication is predicted based on the pulmonary function metric crossing a threshold.
  9. The computing system of any preceding claim, wherein the output comprises a control signal configured to indicate an adjustment to a surgical procedure plan, optionally the adjustment comprising at least one of: an adjustment to a surgical instrument's reload; adding an adjunct; highlighting an affected area associated with the predicted tissue irregularity complication; enlarging a mobilization planned area; or displaying an improved access option.
  10. The computing system of any preceding claim, wherein the output comprises a control signal configured to indicate a probability of a tissue irregularity complication via at least one of: displaying on a pre-surgery imaging; displaying via an augmented reality device; or displaying in a surgical procedure plan along with an indication of an adjustment to the surgical procedure plan.
  11. A sensing system comprising: at least one sensor (20235) for measuring at least one biomarker; and the computing system of claim 1.
  12. The sensing system of claim 11, wherein the measurement data comprises at least one of: pre-surgical measurement data or in-surgical measurement data associated with the at least one biomarker, and the at least one patient biomarker comprises at least one of: tissue perfusion pressure, lactate, oxygen saturation, VO2Max, respiration rate, autonomic tone, sweat rate, heart rate variability, skin conductance, GI motility, edema or hydration state.
  13. The sensing system of claim 11 or claim 12, further comprising a transceiver (20240) configured to: receive a threshold associated with the at least one patient biomarker from a computing system, and wherein the processor is further configured to: calculate a probability of tissue irregularity complication based on the measurement data and received threshold, wherein the tissue irregularity complication is predicted based on the calculated probability.
  14. A computer-implemented method, performed by a computing system, comprising: receiving at the computing system, from at least one sensing system, pre-surgical measurement data associated with at least one patient biomarker; predicting a tissue irregularity complication based on the measurement data associated with the at least one patient biomarker, wherein the tissue irregularity complication comprises at least one of: a tissue thickness irregularity, a tissue density irregularity, a tissue compressibility irregularity, or a tissue stiffness irregularity; and generating a pre-surgical output, such as a control signal, based on the predicted tissue irregularity complication.

Description

Background Tissue irregularity may lead to complications in a surgical procedure. For example, a failure to account for a thicker-than-normal tissue may lead to complications in a transection step of a surgical procedure. For example, a surgical stapler may compress a thicker-than-normal tissue ineffectively by applying a normal compression force during tissue compression. A sub-optimal compression on the thicker-than-normal tissue may be reached if the surgical stapler waits a normal tissue creep time before firing. A staple line may be poorly formed on the thicker-than-normal tissue if the surgical stapler uses staples with a normal staple height during firing. The complications may include staple-line air leaks in a thoracic surgery or staple-line leaks in a colorectal surgery. For example, a failure to account for stiffer-than-normal tissue or a highly-variable-in-thickness tissue in a dissection, a transection, and/or an anastomosis step of a surgical procedure may lead to similar complications. US2020/268472A1 describes systems and methods for analysis of fluid leakage. A system may include at least one processor configured to receive in real time, intracavitary video of a surgical procedure; analyze frames of the intracavitary video to determine an abnormal fluid leakage situation in the intracavitary video; and institute a remedial action when the abnormal fluid leakage situation is determined. US2011/152759A1 describes that biomarkers are collected and used to determine biological propensities of a patient, to determine the efficacy of medical devices, to select and administer therapeutic agents, to select medical devices, to make adjustments to medical devices, and/or to adjust surgical techniques. WO2017/098503A1 describes a computer-implemented system for providing database management for laparoscopic surgery comprising: a. at least two records, each one of said records is of at least one procedure, each record is characterized by at least one attribute; b. at least one processor configured to compare each of said at least two records and to determine if there exists at least one attribute common to both of said at least two records; wherein, if there exists at least one said attribute common to both of said at least two records, an outcome of at least one said procedure is predictable. Summary The invention is as defined in the independent claims. Further embodiments of the invention are defined in the dependent claims. A computing system comprises a processor. The processor is configured to obtain, via at least one sensing system, measurement data associated with at least one patient biomarker. The processor is configured to predict a tissue irregularity complication based on the measurement data associated with the at least one patient biomarker. The processor is configured to generate an output based on the predicted tissue irregularity complication. Advantageously, predicting a tissue irregularity complication and generating an output based on this enables identification of a physiological issue (tissue irregularity complication) that may lead to complications in a surgical procedure. Predicting physiological issues and reacting to them (by generating an output) are important steps in minimizing the possibility of negative surgical outcomes occurring before they arise. The processor may be further configured to determine, based on the predicted tissue irregularity complication, a control signal configured to alter an operational parameter associated with a surgical device. The output may comprise the control signal. Advantageously, adjusting parameters, such as an operational parameter of a surgical device, to mitigate complications reduces the risk of the impending surgery to the patient. The output may comprise a control signal configured to control a surgical cutting and stapling device to perform at least one of: prolonging a tissue creep wait time prior to stapling; reducing a clamping speed; reducing a stapler firing speed; increasing a closure compression force; or shifting upward a viable staple height range. The output may comprise a control signal configured to control a surgical energy device to perform at least one of: increasing an energy level; increasing an energy application duration; or increasing a threshold for an energy generation associated with a subsequent energy application. The processor may be further configured to determine a probability of a chronic inflammation response based on the measurement data associated with the at least one patient biomarker. The tissue irregularity complication may be predicted based on the probability of a chronic inflammation response crossing a threshold. The at least one patient biomarker may include at least one of: tissue perfusion pressure, lactate, oxygen saturation, maximal oxygen consumption (VO2 max), respiration rate, autonomic tone, sweat rate, heart rate variability, skin conductance, or gastrointestinal (GI) motility. The