METHOD FOR ANALYSING MEDICAL DATA

• US 20110275908A1
• Filed: 05/06/2011
• Published: 11/10/2011
• Est. Priority Date: 05/07/2010
• Status: Abandoned Application

• Current Assignee: TomTec Imaging Systems GmbH (Koninklijke Philips N.V.)
• Original Assignee: TomTec Imaging Systems GmbH (Koninklijke Philips N.V.)
• Inventors: BAUMANN, Rolf
• Application Number:
  US13/102,661
• Publication Number:
  US 20110275908A1
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A method for analysing medical data in view of a specific clinical question, the method including the steps of a) providing one or several medical datasets having data acquired by means of one or several diagnostic modalities from one patient; b) providing a clinical question to be answered by the medical dataset(s); c) selecting one or several evaluation methods which are generally suitable for returning relevant information with regard to the clinical question; and d) automatically analysing the medical dataset(s) with regard to their suitability to be used for the one or several evaluation methods and calculating corresponding quality factors for each pair of medical dataset and evaluation method.

Claims

1. A method for analysing medical data in view of a specific clinical question, the method comprising the following steps:

e) providing one or several medical datasets comprising data acquired by means of one or several diagnostic modalities from one patient;

f) providing a clinical question to be answered by the medical dataset(s);

g) selecting one or several evaluation methods which are generally suitable for returning relevant information with regard to the clinical question;

h) automatically analysing the medical dataset(s) with regard to their suitability to be used for the one or several evaluation methods and calculating corresponding quality factors for each pair of medical dataset and evaluation method.

2. The method according to claim 1, further comprising the step of

e) outputting the calculated quality factors.

3. The method according to claim 2, further comprising the step of

f) selecting at least one medical dataset as suitable to be evaluated by at least one evaluation method, the selection comprising:

on the basis of the calculated quality factors, selecting one evaluation method for at least one of the medical dataset(s); and

/or

on the basis of the calculated quality factors, selecting one of several medical datasets to be evaluated by one preferred pre-selected evaluation method.

4. The method according to claim 3, further comprising the steps of:

g) evaluating the selected at least one medical dataset by the selected or the preferred evaluation method;

h) outputting the result of the evaluation method; and

i) outputting the quality factor associated with the outputted result.

5. The method of claim 3, further comprising the steps of:

g) evaluating the selected at least one medical dataset by the preferred evaluation method and, in addition, by one or more of the other generally suitable evaluation methods;

h) outputting the results of each evaluation method; and

i) outputting the quality factor associated with each outputted result.

6. The method according to claim 1, wherein the one or several medical datasets are selected from the group comprising:

image datasets, such as two-dimensional, three-dimensional or four-dimensional image datasets acquired by means of Ultrasound, Computed Tomography, Magnetic Resonance Imaging (MRI), Infrared or X-Ray;

electromedical datasets such as ECG-datasets or EEG-datasets;

hemodynamic datasets, and

blood pressure datasets.

7. The method according to claim 1, wherein the one or several evaluation methods may comprise:

2D evaluation methods for image datasets;

3D evaluation methods for image datasets;

4D evaluation methods for image datasets;

measurement of the synchrony of the movement of a heart chamber;

measurement of the cross section of a blood vessel;

measurement of the intima-media thickness (IMT) of a blood-vessel;

measurement of the degree of stenosis of a blood vessel;

measurement of muscle deformation such as strain, displacement velocity, thickening;

determination of a ventricular ejection fraction by means of single plane Simpson'"'"'s method to measure the ventricular volume;

determination of a ventricular ejection fraction by means of biplane Simpson'"'"'s method to measure the ventricular volume;

determination of a ventricular ejection fraction by means of 3D volume measurements of the ventricular volume.

8. The method according to claim 1, wherein the clinical question is related to the cardiovascular system and in particular is selected from the group comprising:

determining the risk for a vascular disease;

determining the risk for a heart disease;

determining whether the patient has a coronary heart disease;

determining the ventricular function, e.g. the ejection fraction;

determining whether an intraventricular dissynchrony is present;

determining the valvular function.

9. The method according to claim 1, wherein the analysis step d) comprises one or several of the following steps related to the analysis of the provided medical dataset(s):

the readout of data included in the file header(s) of the one or several medical datasets;

OCR of text data on a digital image;

extracting one or more of the imaging modality, the acquisition mode, the dimension of the dataset (2D, 3D;

3D), the time resolution, the spatial resolution and/or the field-of-view of an image dataset, preferably by readout of data contained in the file header(s) of the one or several image datasets or by OCR;

determination of the content of a medical image dataset;

determination of the quality of a medical image dataset in terms of the content of the image in view of the medical question;

determination of the contrast profile of a medical image dataset;

determination of the quality of an image dataset in terms of noise level;

determination of the quality of an image dataset in terms of spatial resolution and/or field-of-view;

determining the type of a medical image dataset in terms of imaging modality, 2D, 3D, 4D.

10. The method according to claim 1, wherein the analysis step d) comprises accessing a list of pre-determined merit factors for the available evaluation methods.

11. The method according to claim 1, wherein the quality factor for each pair of medical dataset and evaluation method is calculated on the basis of one or both of the following:

a component related to the medical dataset, in particular as determined by the analysis step of claim 12;

a pre-determined merit factor of the evaluation method.

12. The method according to claim 1, wherein the quality factor for each pair of medical dataset and evaluation method is calculated by accessing and taking into account of one or several of the following further information:

already available measurement values (46b) for the patient;

the skill of the user (46c);

clinical a priori knowledge (46a) concerning the clinical question;

the age of the patient;

the type of device on which the evaluation is to be carried out.

13. The method according to claim 1, wherein the analysis step d) comprises one or several of the following steps:

d1) optionally preselecting those medical datasets which are generally suitable for returning relevant information with regard to the clinical question;

d2) loading the provided or preselected medical datasets into a working memory;

d3) performing an analysis on the medical datasets in the working memory to calculate a quality factor for each available or pre-selected evaluation method.

14. The method according to claim 1, wherein the analysis step d) or the evaluation step f) comprises a step of modifying the at least one medical dataset to make it suitable for the available or preferred evaluation method(s), in particular a step of extracting partial datasets from at least one medical dataset.

15. A computer program adapted for performing the method according to claim 1, when the computer program is executed on a computer.

16. A device for performing the method according to claim 1, comprising

a storage device for storing the one or several medical datasets;

a computing device for performing the analysis steps d).