Advice
Clinical and technical evidence
Clinical and technical evidence
A literature search was carried out for this briefing in accordance with the interim process and methods statement. This briefing includes the most relevant or best available published evidence relating to the clinical effectiveness of the technology. Further information about how the evidence for this briefing was selected is available on request by contacting mibs@nice.org.uk.
Published evidence
Three studies are summarised in this briefing, including a total of 57 kidney stones from 50 patients plus additional 607 cases of shockwave lithotripsy.
The evidence for StoneChecker includes 3 observational studies (2 full publications and 1 conference abstract).
Table 1 summarises the clinical evidence, and its strengths and limitations.
Overall assessment of the evidence
The studies included in table 1 examine the accuracy of CT texture analysis (CTTA) software for distinguishing uric acid (UA) and non-UA stones and predicting shockwave lithotripsy outcomes. Studies report that CTTA in vivo and ex vivo using unenhanced CT images can accurately differentiate UA stones from non-UA stones, and can also help to predict number of shocks needed when using shock wave lithotripsy to treat kidney stones. Two studies were funded by the company.
Table 1 Summary of selected studies
|
Study size, design and location |
A cross-sectional study of 5 patients with 7 kidney stones varying in size from 3 mm to 6 mmm done in the UK. |
|
Intervention and comparator |
CTTA on CT scan images using CTTA software. No comparator. |
|
Key outcomes |
CTTA metrics showed a mean HU density was statistically significantly positively corrected to number of shocks needed to fragment the stone (correlation co-efficient: 0.806, p=0.028). CTTA metrics of entropy and kurtosis predicted 92% of the outcome of number of shocks to fragment the stone. This was better than using stone volume or density. |
|
Strengths and limitations |
This was an experimental study, and CTTA was based on passed kidney stones that were provided by 5 volunteers. It examined imaging-related factors that were associated with number of shocks needed to fragment the stone. But other clinical-related factors, such renal morphology, congenital anomalies and stone nature (de novo or recurrent), were not included in the analysis when predicting the outcome. Funding of the study was not reported, and 1 study author is a director and shareholder of Feedback Plc. This is the company that developed and markets the TexRAD texture analysis algorithm used in the study. |
|
Study size, design and location |
A cross-sectional study of 14 patients with 18 UA stones and 31 patients with 32 non-UA stones, done in the UK. |
|
Intervention and comparator(s) |
CTTA on CT scan images using CTTA software. No comparator (fourier transform infrared spectroscopy as reference standard). |
|
Key outcomes |
CTTA showed that the accuracy of texture features for differentiating UA from non-UA stones ranged from 88% to 92%. CTTA incorporated metrics including skewness and kurtosis had a sensitivity of 94.4% and specificity of 93.7% for differentiating UA stones from non-UA stones. |
|
Strengths and limitations |
Small sample size. The retrospective design may have introduced selection bias and overestimated diagnostic accuracy. |
|
Study size, design and location |
A cross-sectional study of 607 cases of SWL done in the UK and China. |
|
Intervention and comparator(s) |
CTTA on CT scan images using CTTA software. No comparator. |
|
Key outcomes |
UK data showed a 46% of success rate (completely stone free) with SWL. Variables associated with a significantly lower SWL success rates were: increasing age, female, larger stone sizes, higher mean and standard deviation of the HU, 2 or more stones in the same location, vesico-urteric junction location and higher CTTA calculated entropy and total. The predicted probability of success rates was 84% using CTTA. The data from China produced a model of similar predictive ability. |
|
Strengths and limitations |
A cross-sectional study. The study was funded by StoneChecker Software Limited. |
|
Abbreviations: CTTA, CT texture analysis; HU, Hounsfield unit; SWL, shockwave lithotripsy; UA, uric acid. |
|