Thermoluminescence dosimetry (TLD) in a 3 T magnetic resonance imaging (MRI) environment: implications for personnel exposure monitoring.

Thermoluminescent dosimeters (TLDs) serve as compact and user-friendly tools for various applications, including personal radiation dosimetry and radiation therapy. This study explores the potential of utilizing TLD-100 personal dosimetry, conventionally applied in PET/CT (positron emission tomography/computed tomography) settings, in the PET/MRI (magnetic resonance imaging) environment. The integration of MRI into conventional radiotherapy and PET systems necessitates ionizing radiation dosimetry in the presence of static magnetic fields. In this study, TLD-100 dosimeters were exposed on the surface of a water-filled cylindrical phantom containing PET-radioisotope and positioned on the patient table of a 3 T PET/MRI, where the magnetic field strength is around 0.2 T, aiming to replicate real-world scenarios experienced by personnel in PET/MRI environments. Results indicate that the modified MR-safe TLD-100 personal dosimeters exhibit no significant impact from the static magnetic field of the 3 T PET/MRI, supporting their suitability for personal dosimetry in PET/MRI settings. This study addresses a notable gap in existing literature on the effect of MRI static magnetic field on TLDs.

Analysis of inter-patient variations in tumour growth rate.

PURPOSE: Inter-patient variations in tumour growth rate are usually interpreted as biological heterogeneity among patients due to, e.g., genetic variability. However, these variations might be a result of non-exponential, e.g. the Gompertzian, tumour growth kinetics. The aim was to study if the natural tumour growth deceleration, i.e. non-exponential growth, is a dominant factor in such variations. MATERIALS AND METHODS: The correlation between specific growth rate (SGR) and the logarithm of tumour volume, Ln(V), was calculated for tumours in patients with meningioma, hepatocellular carcinoma, pancreatic carcinoma, primary lung cancer, post-chemotherapy regrowth of non-small cell lung cancer (NSCLC), and in nude mice transplanted with human midgut carcinoid GOT1, a tumour group which is biologically more homogeneous than patient groups. RESULTS: The correlation between SGR and Ln(V) was statistically significant for meningioma, post-chemotherapy regrowth of NSCLC, and the mouse model, but not for any other patient groups or subgroups, based on differentiation and clinical stage. CONCLUSION: This method can be used to evaluate the homogeneity of tumour growth kinetics among patients. Homogeneity of post-chemotherapy regrowth pattern of NSCLC suggests that, in contrast to untreated tumours, the remaining resistant cells or stem cells (if exist) might have similar biological characteristics among these patients.

A new method to estimate parameters of the growth model for metastatic tumours.

PURPOSE: Knowledge of natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal scheduling of chemotherapy, and assessing tumour spread. However, mathematical modelling in individuals is hampered by the limited data available. We aimed to develop a method to estimate parameters of the growth model and formation rate of metastases in individual patients. MATERIALS AND METHODS: Data from one patient with liver metastases from a primary ileum carcinoid and one patient with lung metastases from a primary renal cell carcinoma were used to demonstrate this new method. Metastatic growth models were estimated by direct curve fitting, as well as with the new proposed method based on the relationship between tumour growth rate and tumour volume. The new model was derived from the Gompertzian growth model by eliminating the time factor (age of metastases), which made it possible to perform the calculations using data from all metastases in each patient. Finally, the formation time of each metastasis and, consecutively, the formation rate of metastases in each patient were estimated. RESULTS: With limited measurements in clinical studies, fitting different growth curves was insufficient to estimate true tumour growth, even if patients were followed for several years. Growth of liver metastases was well described with a general growth model for all metastases. However, the lung metastases from renal cell carcinoma were better described by heterogeneous exponential growth with various growth rates. CONCLUSION: Analysis of the regression of tumour growth rate with the logarithm of tumour volume can be used to estimate parameters of the tumour growth model and metastasis formation rates, and therefore the number and size distribution of metastases in individuals.

Quantitative analysis of tumor growth rate and changes in tumor marker level: specific growth rate versus doubling time.

BACKGROUND: Doubling time (DT) of tumor volume has been widely used to estimate the growth rate of tumors. However, DT gives incorrect estimates of the average growth rate of tumors when the uncertainty of growth rate is considerable. Specific growth rate (SGR) is less affected by uncertainties and is a more relevant parameter. Optimized imaging techniques and prolonged interval between observations can reduce the uncertainty of growth rate estimation. DT is also used for defining changes in tumor marker level. The aim of this study was to compare DT and SGR as measures of growth rate when the uncertainty is negligible. METHODS: Mathematical analysis and computer simulations were carried out assuming no uncertainty of growth rate estimation. Data from two previously published clinical studies were assessed by both variables. RESULTS: Due to the non-linear relationship between DT and SGR, using these variables does not give similar results. The variation of DT is not uniformly indicating variations of the growth rate. DT largely overestimates the difference in growth rate of slowly growing tumors and underestimates the difference in growth rate of rapidly growing tumors. On the other hand, SGR uniformly indicates the difference between growth rates throughout all ranges. Quantitative analysis of clinical observations can lead to contradictory results depending on the variable used for growth rate. CONCLUSION: The growth rate of tumor volume should be expressed by SGR, or percentage increase per unit time, regardless of the level of the uncertainty of growth rate estimation. This conclusion is also valid for changes in tumor marker level, whether it is correlated with the growth rate of tumor volume or not.

Specific growth rate versus doubling time for quantitative characterization of tumor growth rate.

Doubling time (DT) is widely used for quantification of tumor growth rate. DT is usually determined from two volume estimations with measurement time intervals comparable with or shorter than DT. Clinical data show that the frequency distribution of DT in patients is positively skewed, with some very long DT values compared with the average DT. Growth rate can also be quantified using specific growth rate (SGR; %/d), equal to ln2/DT. The aim of this work was to compare DT and SGR as growth rate variables. Growth rate calculations were computer simulated for a tumor with DT of 100 days, measurement time interval of 1 to 200 days, and volume estimation uncertainty of 5% to 20%. Growth rate variables were determined and compared for previously published clinical data. The study showed that DT is not a suitable variable for tumor growth rate because (a) for short measurement time intervals, or high volume uncertainties, mean DT can either overestimate or underestimate the average growth rate; (b) DT is not defined if the consecutively estimated volumes are equal; and (c) the asymmetrical frequency distribution of DT makes it unsuitable for common statistical testing. In contrast, mean SGR and its equivalent DT give the correct values for average growth rate, SGR is defined for all tumor volume changes, and it has a symmetrical frequency distribution. SGR is also more accurate to use when discussing, for example, growth fraction, cell loss rate, and growth rate heterogeneities within the tumor. SGR should thus be used, instead of DT, to quantify tumor growth rate.