Estimation of tumour volume at therapy initiation by back-extrapolating the post-therapy regression curve of tumour volume

Background: Tumour volume at therapy initiation, Vi, is rarely available in cancer patients, and the last pre-treatment tumour volume available is from previous diagnostic imaging (Vd). Therapeutic efficacy is thus evaluated by comparing tumour volume after treatment with Vd, instead of Vi, which results in underestimation of treatment efficacy. Vi, together with Vd, can also be used for estimation of the natural growth rate of tumour valuable for, e.g., screening programs, prognostication and individualised treatment planning such as chemotherapy scheduling. The aim of this work was to study the feasibility of estimating Vi by back-extrapolating the post-therapy regression of tumour volume, based on data from animal model. Methods: Nude mice bearing human neuroendocrine GOT1 tumour cell line were treated with 177Lu-DOTA-TATE. Tumour volumes were measured regularly after therapy and Vi was estimated by back-extrapolation of (a) linear and (b) exponential regression lines of the two earliest post-therapy tumour volumes and (c) the long-term exponential regression of tumour volume. The estimated Vi values (Vest) were compared with the measured volume of tumour at therapy initiation. Results: The linear regression of the two earliest post-therapy tumour volumes gave the best estimate for Vi (Vest = 0.91 Vi, p < 0.00001), compared with the exponential regression models either on short-term (Vest = 2.30 Vi, p < 0.01), or long-term (Vest = 0.93 Vi, non-significant) follow up of tumour volume after therapy. Conclusion: Back-extrapolation of the early linear regression of tumour volume after therapy gave the best estimate for tumour volume at time of therapy initiation. This estimate can be used as baseline for treatment efficacy evaluation or for estimation of the natural growth rate of tumour (together with the measured tumour volume at pre-treatment diagnostic imaging)

Objective assessment of tumour response to therapy based on tumour growth kinetics.

BACKGROUND: Current standards for assessment of tumour response to therapy (a) categorise therapeutic efficacy values, inappropriate for patient-specific and deterministic studies, (b) neglect the natural growth characteristics of tumours, (c) are based on tumour shrinkage, inappropriate for cytostatic therapies, and (d) do not accommodate integration of functional/biological means of therapeutic efficacy assessed with, for example, positron emission tomography or magnetic resonance imaging, with data from anatomical changes in tumour. METHODS: A quantity for tumour response was formulated assuming that an effective treatment may decrease the cell proliferation rate (cytostatic) and/or increase the cell loss rate (cytotoxic) of the tumour. Tumour response values were analysed for 11 non-Hodgkin's lymphoma patients treated with (131)I-labelled anti-B1 antibody and 12 prostate cancer patients treated with a nutritional supplement. RESULTS: Tumour response was found to be equal to the logarithm of the ratio of post-treatment tumour volume to the volume of corresponding untreated tumour. Neglecting the natural growth characteristics of tumours results in underestimation of treatment effectiveness based on currently used methods. The model also facilitates the integration of data from tumour volume changes, with data from functional imaging. CONCLUSION: Tumour response to therapy can be assessed with a continuous dimensionless quantity for both cytotoxic and cytostatic treatments.