Figure - available from: Cancer Informatics
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Diagram illustrating user bias (user 1) and inconsistency of bias compared with other users (users 2 and 3).
Source publication
User measurement bias during subcutaneous tumor measurement is a source of variation in preclinical in vivo studies. We investigated whether this user variability could impact efficacy study outcomes, in the form of the false negative result rate when comparing treated and control groups. Two tumor measurement methods were compared; calipers which...
Citations
... 13 In comparison to callipers, 3D-TI reduces user bias by using machine learning and computational algorithms to calculate length, width, and height measurements automatically. The variability in calliper tumour measurement methods is predicted to affect the rate of false negative results in efficacy studies, 14 and the tumour growth inhibition (TGI) drug efficacy metric 15 in comparison to 3D-TI. Height measurement allows 3D-TI to calculate tumour volume using the LWH (Volume formula using length, width and height) formula which has been shown to give more consistently accurate volumes in comparison to the LWW formula and 18 other tumour volume formulae. ...
Tumour volume is typically calculated using only length and width measurements, using width as a proxy for height in a 1:1 ratio. When tracking tumour growth over time, important morphological information and measurement accuracy is lost by ignoring height, which we show is a unique variable. Lengths, widths, and heights of 9522 subcutaneous tumours in mice were measured using 3D and thermal imaging. The average height:width ratio was found to be 1:3 proving that using width as a proxy for height overestimates tumour volume. Comparing volumes calculated with and without tumour height to the true volumes of excised tumours indeed showed that using the volume formula including height produced volumes 36X more accurate (based off of percentage difference). Monitoring the height:width relationship (prominence) across tumour growth curves indicated that prominence varied, and that height could change independent of width. Twelve cell lines were investigated individually; the scale of tumour prominence was cell line-dependent with relatively less prominent tumours (MC38, BL2, LL/2) and more prominent tumours (RENCA, HCT116) detected. Prominence trends across the growth cycle were also dependent on cell line; prominence was correlated with tumour growth in some cell lines (4T1, CT26, LNCaP), but not others (MC38, TC-1, LL/2). When pooled, invasive cell lines produced tumours that were significantly less prominent at volumes >1200 mm³ compared to non-invasive cell lines (P < .001). Modelling was used to show the impact of the increased accuracy gained by including height in volume calculations on several efficacy study outcomes. Variations in measurement accuracy contribute to experimental variation and irreproducibility of data, therefore we strongly advise researchers to measure height to improve accuracy in tumour studies.
Animal experiments are often used in cancer research as an alternative to clinical trials to determine the effect of various drugs and other biological conditions on tumor behavior. The tumor volume measurement is necessary in these experiments. The operation of imaging devices is expensive, and it is necessary to anesthetize the animals during the measurement. Anesthesiology induces stress and deviation from homeostatic functioning, which greatly affects the results of the experiment. To address these problems, the digital caliper method, which is safe and cost-effective, is applied to measure tumor volume during in vitro studies. However, it is only rarely possible to accurately measure the volume of the tumor with a digital caliper. It is, therefore, important to examine how we can estimate the three-dimensional volume of the tumor from measurements carried out with a digital caliper. This study summarizes the approximation formulas used in the literature and their scope of use and analyzes the advantages and disadvantages of digital caliper measurements. We aim to highlight the importance of creating a noise model in cancer research that generally describes the difference between real tumor volumes and those measured with calipers.
