Kidney stone identification system

1 . A system comprising:

a medical target ablation instrument for ablating a target located at an anatomic site within a patient, the medical target ablation instrument defining therewithin an evacuation path for transporting the ablated target away from the anatomic site;

a measurement chamber located along the evacuation path;

a turbulator configured to generate turbulence within the measurement chamber; and

a target composition characterization system, operatively coupled to the measurement chamber, the target composition characterization system configured to determine a composition characteristic of the ablated target during agitation within the measurement chamber.

2 . The system of claim 1 , wherein the evacuation path further comprises:

a receptacle located downstream of the measurement chamber for storing the ablated target.

3 . The system of claim 2 , wherein the measurement chamber comprises:

an inlet valve to direct the ablated target into the measurement chamber; and

an outlet valve to direct the ablated target out of the measurement chamber.

4 . The system of claim 3 , wherein the evacuation path comprises:

a bypass valve to direct the ablated target around the measurement chamber and directly into the receptacle.

5 . The system of claim 4 , wherein the system includes controller circuitry that is configured to operate in a plurality of modes, the plurality of modes including a sample measurement mode and a sample trap mode.

6 . The system of claim 5 , wherein in the sample measurement mode, the controller circuitry actuates the inlet valve to be open, the outlet valve to be closed, and the bypass valve to be closed, and wherein in the sample trap mode, the controller circuitry actuates the inlet valve to be closed, the outlet valve to be open, and the bypass valve to be open.

7 . The system of claim 1 , further comprising:

controller circuitry for adjusting a parameter associated with the medical target ablation instrument based at least in part on the determined composition characteristic of at least a portion of the ablated target.

8 . The system of claim 7 , wherein the controller circuitry is coupled to memory circuitry including stored instructions that, when performed by the controller circuitry, cause the controller circuitry to:

receive an inflow rate indicative of a fluid flow going into the measurement chamber;

receive an outflow rate indicative of a fluid flow leaving the measurement chamber; and

establish or adjust the inflow rate or the outflow rate to at least one of establish, adjust, or maintain a target turbulence level using the turbulator.

9 . The system of claim 7 , wherein the target composition characterization system comprises:

a light source for illuminating the ablated target within the measurement chamber; and

a spectrometer for detecting a response signal from the at least a portion of the ablated target in response to the illumination;

wherein the controller circuitry determines the composition characteristic of the at least a portion of the ablated target based on at least in part on the detected response signal.

10 . The system of claim 9 , wherein the controller circuitry is coupled to memory circuitry including instructions that, when performed by the controller circuitry, cause the controller circuitry to:

receive the response signal from the spectrometer;

analyze the response signal to determine the composition characteristic of the at least a portion of the ablated target;

compare the composition characteristic of the at least a portion of the ablated target to at least one criterion; and

generate an output based on the comparison.

11 . The system of claim 10 , comprising:

a convolutional neural network connected to the controller circuitry, wherein the controller circuitry is configured to:

transmit a signal from the spectrometer to the convolutional neural network;

transmit the output indicative of the target composition characteristic to the convolutional neural network; and

receive one or more updated instructions, based on an output of the convolutional neural network.

12 . The system of claim 7 , wherein the target composition characterization system comprises:

an acoustic wave generator to produce an acoustic wave that propagates to the measurement location along the evacuation path;

an impedance sensor to generate an impedance-indicating signal from a change in amplitude and phase of the acoustic wave after the acoustic wave has traveled through the measurement location; and

the controller circuitry is configured for determining the target composition characteristic of the at least a portion of the ablated target based at least in part on the impedance-indicating signal.

13 . The system of claim 12 , wherein the controller circuitry is coupled to memory circuitry including instructions that, when performed by the controller circuitry, cause the controller circuitry to:

receive the impedance-indicating signal from the impedance sensor;

analyze the impedance-indicating signal to determine the target composition characteristic of the at least a portion of the ablated target;

compare the target composition characteristic of the at least a portion of the ablated target to at least one reference characteristic; and

generate an output indicative of an identity of the target based on the comparison.

14 . The system of claim 13 , comprising:

a convolutional neural network connected to the controller circuitry, the controller circuitry configured to:

transmit the impedance-indicating signal to the convolutional neural network;

transmit the output indicative of the target composition characteristic to the convolutional neural network; and

receive one or more updated acoustic impedance algorithms.

15 . The system of claim 7 , wherein the target composition characteristic system further comprises:

an imaging device for imaging the ablated target along the evacuation path; and

an object-detection system for detecting the ablated target in an image of the ablated target acquired by the imaging device, wherein the controller circuitry determines the target composition characteristic of the ablated target based at least in part on the image of the ablated target acquired by the imaging device.

16 . The system of claim 15 , wherein the target composition characterization system is trained to recognize a plurality of ablated target characteristics.

17 . The system of claim 15 , wherein the controller circuitry is coupled to memory circuitry including instructions that, when performed by the controller circuitry, cause the controller circuitry to:

receive an output from the object-detection system;

analyze the output to determine the target composition characteristic of the at least a portion of the ablated target;

compare the target composition characteristic of the at least a portion of the ablated target to at least one criterion; and

generate an output indicative of an identity of the target based on the comparison.

18 . The system of claim 17 , comprising:

a convolutional neural network connected to the controller circuitry, the controller circuitry configured to:

transmit the output from the object-detection system to the convolutional neural network;

transmit the output indicative of the target composition characteristic to the convolutional neural network; and

receive one or more updated object-detection instructions based on an output of the convolutional neural network in response to the output from the object-detection system and in response to the output indicative of an identity of the target.

19 . The system of claim 1 , comprising:

a particle sensor, arranged for measuring a quantity of particles within at least a portion of the evacuation path; and

controller circuitry, coupled to the particle sensor, to calculate an ablation rate of the target based at least in part on the measured quantity of the particles.

20 . The system of claim 1 , wherein the turbulator is located at least partially within the measurement chamber.

21 . The system of claim 1 , wherein the measurement chamber includes a first cross-sectional area and the evacuation path defines a second cross-sectional area, and wherein the first cross-sectional area is greater than the second cross-sectional area.