Clinical decision support (cds) for radiotherapy in prostate cancer

Patent metadata

Field	Value
Publication number	US-2016008629-A1
Application number	US-201414770482-A
Country	US
Kind code	A1
Filing date	Mar 7, 2014
Priority date	Mar 20, 2013
Publication date	Jan 14, 2016
Grant date	—

Abstract

A system ( 30 ) and method for detecting or predicting toxicity induced by radiation therapy. A device ( 34 ) is configured for determining polypeptide biomarkers present in a urine sample. At least one processor ( 36 ) is programmed to detect or predict radiation toxicity based on one or more polypeptide biomarkers determined to be in the urine sample.

First claim

1 . A method for detecting or predicting toxicity induced by radiation therapy, said method comprising:
receiving a urine sample from a human subject; and, detecting or predicting radiation toxicity using one or more biomarkers within the urine sample, wherein each biomarker corresponds to a polypeptide, wherein the detecting or predicting includes: analyzing the urine sample for one or more biomarkers, each including a different mass from the group consisting of 4478±9 Da, 6716±13 Da, 8293±17 Da, 8840±18 Da, 10571±21 Da, 2863±6 Da and 6732≅13 Da, to detect or predict toxicity induced by radiation therapy of prostate, bladder, bowel, rectum, endometrial, cervix, ovarial or vaginal cancer.

2 . The method according to claim 1 , wherein the detecting or predicting includes:
analyzing the urine sample for one or more biomarkers having a mass from the group consisting of 2863±6 Da and 6732±13 Da, to detect bowel toxicity caused by radiation therapy.

3 . The method according to claim 1 , wherein the detecting or predicting includes:
analyzing the urine sample for a biomarker with a mass of 6732±13 Da to predict bowel toxicity in radiation therapy of prostate cancer.

4 . The method according to claim 1 , wherein the detecting or predicing includes:
analyzing the urine sample for one or more biomarkers having a mass of at least one of 4478±9 Da, 6716±13 Da, 8293±17 Da, 8840±18 Da and 10571±21 Da, to detect urinary toxicity caused by radiation therapy.

5 . The method according to claim 1 , wherein the detecting or predicing includes:
analyzing the urine sample for one or more biomarkers with a mass of at least one of 8293±17 Da and 10571±2.1 Da, to predict urinary toxicity in radiation therapy of prostate cancer.

6 . (canceled)

7 . The method according to claim 1 , wherein the detecting or predicting includes performing a mass spectrometry (MS) analysis of the urine.

8 . The method according to claim 1 , wherein the detecting or predicing is performed using enzyme-linked immunosorbent assay (ELISA) antibody assays.

9 . The method according to claim 1 , wherein the detecting or predicting further uses data from one or more of genetic tests, tumor grading, scaling, histology, concurrent patient medication, patient file data, medical imaging, and in vitro diagnostics.

10 . The method according to claim 1 , further including:
based on the detecting or predicting, at least one of:
displaying an indication of the radiation toxicity induced or an indication of susceptibility to the radiation toxicity; and,
generating or updating a radiation treatment plan, wherein doses are reduced in response to toxicity or in response to susceptibility to toxicity.

11 . A system for detecting or predicting toxicity induced by radiation therapy, said system comprising:
a device configured for determining polypeptide biomarkers present in a urine sample from a human subject; at least one processor programmed to:
detect or predict radiation toxicity based on one or more polypeptide biomarkers determined to be in the urine sample wherein the at least one processor is programmed to:
analyze the polypeptide biomarkers for polypeptides with a mass of at least one of 4478±9 Da, 6716±13 Da, 8293±17 Da, 8840±18 Da, 10571±21 Da, 2863±6 Da and 6732±13 Da to detect or predict toxicity induced by radiation therapy of prostate, bladder, bowel, rectum, endometrial, cervix, ovarial or vaginal cancer.

12 . (canceled)

13 . (canceled)

14 . The system according to claim 11 , wherein the device determines whether peptides with a mass of at least one of 4478±9 Da, 6716±13 Da, 8293±17 Da, 8840±18 Da and 10571±21 is present in the urine sample.

15 . (canceled)

16 . The system according to claim 11 , wherein the device includes:
a mass spectrometer used to perform the detecting or predicting; wherein the at least one processor is programmed to:
extract features from mass spectrometry (MS) peaks of the urine sample, the features being one or more of p-value, receiver operating characteristic limits, and intensity; and,
input the extracted features into a classifier trained on a training set of urine samples.

17 . The system according to claim 11 , wherein the detecting or predicing is performed using enzyme-linked immunosorbent assay (ELISA) antibody assays.

18 . The system according to claim 11 , wherein the at least one processor is programmed to:
use data from one or more of genetic tests, tumor grading, scaling, histology, concurrent patient medication, patient tile data, medical imaging, and in vitro diagnostics to detect or predict the radiation toxicity.

19 . The system according to claim 11 , wherein the at least one processor is further programmed to:
control a display device to display an indication of the radiation toxicity or susceptibility; and, generate or update a radiation treatment plan, wherein doses are reduced in response to toxicity or in response to susceptibility to toxicity.

20 . (canceled)

Assignees

• Koninkl Philips Nv

Inventors

• Ribbing Carolina
• Bitter Katrin

Classifications

• G01N35/00584

  Control arrangements for automatic analysers · CPC title

• G01N2800/52

  Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis · CPC title

• G01N33/6848

  Methods of protein analysis involving mass spectrometry · CPC title

• A61N5/103 Primary

  Treatment planning systems · CPC title

• H01J49/0027

  Methods for using particle spectrometers · CPC title