1 Department of Mechanical Engineering, 2 Department of Biomedical Engineering, 3 Department of Urologic Surgery, and 4 Department of Obstetrics and Gynecology, University of Minnesota, Minneapolis, MN 55455, USA
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Abstract |
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Key words: cryosurgery/leiomyoma/oestradiol/thermal history/tumour
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Introduction |
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The current applications of cryosurgery have been reviewed recently (Gage and Baust, 1998). For visceral deep-seated soft tissue tumours, cryotherapy can be used through laparoscopy or percutaneously by ultrasound guidance. This approach has been used in liver (Onik et al., 1993a
; Korpan, 1997
), prostate (Onik et al., 1993b
, 1995
), and in initial clinical trials in kidney (Uchida et al., 1995
; Delworth et al., 1996
). Cryotherapy has also been used on uterine tissue in the past (Cahan, 1964
; Boonstra et al., 1990
), and is currently being re-evaluated for the treatment of both endometrial disorders and leiomyomata (Rutherford et al., 1998
; Zreik et al., 1998
). A recent pilot clinical study suggests that cryomyolysis, or cryosurgery of uterine leiomyomata, may be able to reduce uterine fibroids, thus making it a potential treatment or management option for this disease (Zreik et al., 1998
). However, knowledge of the precise conditions (and mechanisms) whereby freezing destroys tumour cells and tissues remains an area of active research.
Based on available empirical survival results, it is clear that the thermal dose necessary to destroy tumour cells varies tremendously from cell type to cell type (Gage and Baust, 1998; Smith et al., 1999
). At the cellular level, mechanisms which are known to affect cell viability are dependent on the thermal history a cell experiences, i.e. the cooling rate (CR), minimum or end temperature (ET), time held at the end temperature (HT), and thawing rate (TR) (Mazur, 1984
; Gage and Baust, 1998
). Each of these parameters varies with distance from the cryoprobe in an iceball during cryosurgery. CR-dependent biophysical events in frozen cells [intracellular ice formation (IIF) and severe cell dehydration] have been correlated with cell injury in a variety of cell types (Mazur, 1984
), and an ET-dependent injury effect has been observed in Walker carcinoma cells (Jacob et al., 1985
), human prostate cancer cells (Tatsutani et al., 1996
) and in a rat prostate cancer line (Bischof et al., 1997
; Smith et al., 1999
). Furthermore, HT and TR were found to be correlated with cell death in cryopreserved cell systems, due at least in part to recrystallization (Mazur, 1984
). The following study was designed to establish the thermal conditions required to reproducibly destroy uterine leiomyomata cells.
In this study, a two-level, four-parameter (24) set of experiments (Box et al., 1978) was performed to explore the connection between thermal history and post-thaw viability in cultured uterine leiomyoma cells from the ELT-3 cell line. The ELT-3 and several other leiomyoma cell lines were established and characterized in the laboratory of Dr Cheryl Walker from spontaneously growing leiomyoma tumours in an Eker rat line (Everitt et al., 1995
). The four parameters of this study were: CR, ET, HT and TR; together these four parameters define the subzero portion of a freezethaw process. The thermal parameters which most significantly affect survival outcome were determined through calculation of individual parameter effect values (E), according to the experimental design guidelines (Box et al., 1978
). In addition, any synergy between two parameters in determining survival outcome was revealed by calculation of the interaction value for those parameters (I), and the degree of non-linearity in the dependence of survival on parameter variations was assessed based on calculation of the survival curvature (C) in the parameter ranges studied. The E, I and C values were used to establish thermal dose thresholds and, where possible, to assist in uncovering cellular injury mechanisms which potentially could contribute to tissue destruction after cryosurgery of a leiomyoma tumour. Additional studies outside the parameter range of the factorial design were performed to assess the broader effects of cooling rate at 150°C/min, as well as the presence of the hormone oestradiol on cryoinjury.
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Theoretical background |
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Materials and methods |
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A supplemental study to assess whether cryoinjury is enhanced or depressed in the presence of a mitogenic hormone was also performed. ELT-3 cells were cultured in the presence of 108 mol/l water soluble oestradiol-17ß (Sigma). This concentration of oestradiol was selected on the basis of a previous study assessing the impact of the drug Tamoxifen on ELT-3 cell growth in the presence and absence of oestradiol (Howe et al., 1995). It should be noted that the selected concentration of hormone is several hundred times the peak circulating values found during pro-oestrus in SpragueDawley rats (Butcher et al., 1975
). Cells were cultured in the presence of hormone for at least 1 week and split continuously every other day in order to ensure dense, log-phase populations.
Experimental design
The experimental matrix for determining how cell survival is dependent on thermal history was designed according to the principles of two-level parametric experimental design (see above). The theory of experimental factorial design is explained in more detail elsewhere (Box et al., 1978). The adaptation of this design for the study of cryoinjury on single cells used here was first described in 1999 (Smith et al., 1999
). The four parameters used in the study to describe a freezethaw included: CR, ET, HT and TR. High and low values of each parameter were chosen to be within the range of each parameter typically experienced by cryotreated tissue in cryosurgery (Table I
). Survival tests were performed for every combination of parameter values; this results in 24 = 16 experimental protocols, each of which is one point in the matrix as shown in Figure 1
. To assess non-linearity in the survival dependence on thermal history, an additional protocol (the centre point protocol) defined by the midpoint of each of the four parameter ranges was included, for a total of 17 freezethaw protocols in the parametric experimental design. Additional protocols were used to assess CR dependence over a broader CR range than that defined in Table I
for the minimally injurious values of the other parameters (i.e. high ET, low HT and high TR). The additional CR tested were 1, 10, 20 and 50°C/min to 20°C. Each protocol was performed three times on separate cell suspensions, so that an average survival value and SD could be calculated for each protocol in the matrix (Figure 1
). By measuring cell survival in cells exposed to each of the 17 protocols in the parametric experiment design, survival dependence on each thermal parameter can be assessed.
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After the freezethaw process, the viability of cell suspensions was measured using calcein AM and propidium iodide as previously described (Smith et al., 1999). A 10 µl sample of cell suspension was removed from the microslide and incubated with 2 µmol/l calcein AM and 3 µmol/l propidium iodide for 1530 min at 37°C. After incubation, cells were scored as either live or dead under a fluorescent microscope. Three separate freezethaw experiments were performed for each experimental protocol. Viability measurements on cells taken directly from the stock suspension without freezing were determined before and after every three freezethaw experiments as a control; all experimental viability values were normalized to the average control viability. Control viabilities were all >95%. The viability of cell suspensions frozen in vitro and assessed immediately post-thaw likely underpredict the true cryosurgical injury for the same thermal history experienced in vivo (Bischof et al., 1997
), but these short-term viability measurements do serve as conservative estimates of possible in-vivo cryodestruction.
Statistical analysis
Once the survival data were collected, the parameter effects, interactions and curvature were calculated using the formulation originally described by Box (Box et al., 1978) and recently applied to cryoinjury in AT-1 cell suspensions (Smith et al., 1999
). Each parameter effect was calculated from the survival results as the average difference in survival percentage caused by change in that parameter. This difference was calculated by averaging the survival values (0100%) for the eight protocols in which the high value of the parameter was used, and subtracting the average survival for the eight protocols in which the low parameter value was used. Calculation of the ET effect is shown in equation 1
as an example (using the nomenclature of Figure 1
) and shown pictorially in Figure 2A
.
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EET is the ET effect value, and each four-letter combination of c, e, h and t represents one of the 16 average survival measurements in the experimental matrix. The capital or lowercase letters represent the high or low value for a parameter respectively. For example, cEHt represents the average survival for cells exposed to the low CR, high ET, high HT and low TR, according to the parameter values in Table I.
The magnitude of the minimum significant parameter effect can be calculated using the Student's t-distribution and the pooled SD for the 17 protocols used as part of the matrix for the two-level experiment (Moffat, 1985). This minimum value represents the average difference in survival between two protocols caused solely by experimental uncertainty in the survival measurements. The magnitude of any parameter effect must be greater than this minimum value to be considered significant, and the relative magnitudes of parameter effects indicated which effects most significantly affect survival in the parameter ranges studied (Table I
). The minimum significant parameter effect was calculated using the following formula (Moffat, 1985
):
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The parameter t is the t statistic for the chosen confidence interval from the Student's t-distribution. For the present set of experiments, the number of degrees of freedom for the parametric design is the total number of data points collected minus the total number of combinations of parameters. The total number of data points was 17 protocols, at three trials per protocol, or 51. The total number of parameter combinations for which survival was measured was 17; 16 combinations of extreme parameter values plus the additional survival measurement for the centre point protocol. The number of degrees of freedom was thus 51 17 = 34. For a 99% confidence level with 34 degrees of freedom, t = 2.72 (Moore and McCabe, 1993). The parameter s is the pooled SD in all 17 protocols. The parameter m is the number of parameter levels (two) raised to the power of the number of parameters minus 1, or m = 23 = 8. The parameter k is the number of separate trials for each protocol in the matrix; in this experimental design, k = 3. The value of µE computed from the survival results for this study was 3.45%.
The parameter interactions were also calculated using the formulation of Box et al. (1978) which has recently been applied to cryoinjury in cell systems (Smith et al., 1999). The interaction between two parameters was calculated from the survival results as the average change in the parameter effect for one of the parameters caused by increase of the other parameter. This calculation was carried out by averaging the survival values for the eight protocols in which the same level of each parameter was used (i.e. both high values or both low values) and subtracting the average survival for the eight protocols in which the high value of one parameter and the low value of the other parameter was used. The ETHT interaction calculation is shown in equation 3
as an example (using the nomenclature of Figure 1
) and shown pictorially in Figure 2B
.
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IETHT is the ETHT interaction value, and the other symbols are described above for equation 1. The relative magnitudes of parameter interactions indicate which ones most significantly affect survival in the parameter ranges studied (Table I
). The magnitude of the minimum significant parameter interaction µI is equal to µE, because in both cases the calculated quantity is computed from the same 16 survival values (Moffat, 1985
). The magnitude of any parameter interaction must be greater than this minimum value to be considered significant.
The non-linearity of survival dependence on thermal history was assessed by calculation of the curvature in the results. The curvature (C) is the extent to which cell survival variation departs from linear dependence on the parameters (Moffat, 1985). It was calculated from the survival results as the difference in survival percentage between a linear interpolation of the experimental data and actual survival measurement at a point in the parameter space midway between the high and low levels of each parameter. The linear interpolation of the experimental data at the centre point in the parameter space was simply the average survival for all 16 protocols in the experimental matrix. The curvature was calculated by taking the average survival for the 1 protocols and subtracting the survival measured for the centre point protocol:
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C is the value of the curvature, and the other symbols are described above for equation 1. The survival value
is the measured survival for the centre point protocol. The magnitude of the minimum significant curvature can be calculated using the Student's t-distribution. The minimum significant curvature µC was calculated using the following formula (Moffat, 1985
):
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The parameters t, s, m and k are defined above. The parameter c is the number of separate trials performed for the centre point protocol; in this experiment, c = 3. µC is not equal to µE or µI because the curvature calculation includes an additional survival value, the centre point survival. The value of µC computed from the survival results for this study was 7.3%.
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Results |
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Tissues during cryosurgery will often experience cooling rates which vary from 50100°C/min at the probe to as low as 15°C/min, or even less, at the advancing ice front boundary. Thus, additional CR studies beyond the 525°C/min selected in the factorial design were also performed and are shown in Figure 4. In order to isolate the specific effects of CR, studies were conducted between 1 and 50°C/min for mild values of the other three parameters (i.e. high ET, low HT and high TR). The survival values ± SD for cells cooled at 1, 5, 10, 20, 25 and 50°C/min to 20°C were 14.6 ± 6.6%, 82.3 ± 5.1, 84.4 ± 6.6, 70.6 ± 5.9, 71.8 ± 3.4 and 18.33 ± 2.3% respectively. The results at 5 and 25°C/min were taken directly from Figure 3
. These results suggest an `inverted U' survival curve for ELT-3 cells as typically seen in mammalian cells (Mazur, 1970
, 1984
). Preliminary observations of intracellular ice formation (IIF) in ELT-3 cells (n = 20) cooled to 20°C, showed that IIF began to form only at CR
25°C/min (data not shown). This IIF measurement was taken using standard cryomicroscopy techniques, described in detail in other work (Toner et al., 1992
; Bischof et al., 1997
).
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Discussion |
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Results of the factorial design approach for thermal sensitivity in Dunning rat AT-1 prostate tumour cells show similar survival trends over a much broader parameter range than in the present uterine leiomyoma study (Smith et al., 1999). Due to the lack of thermal sensitivity of the AT-1 line, the parameter space of interest was much larger: CR, 550°C/min; ET, 20 to 80°C; HT, 015 min; TR 20200°C/min. Clearly the thresholds of injury in the AT-1 prostate cancer model were very different. In particular, AT-1 cells survived freezing to 80°C under various conditions, whereas the ELT-3 cells only survive to roughly 30°C. In addition, AT-1 cell survival began dropping after 15 min of HT at 20°C whereas similar survival drops occurred within ELT-3 cells after only 5 min. When the specific parameter effects and interactions were investigated, the AT-1 study showed that the most important thermal parameter was ET, followed closely by HT and to a lesser extent TR. The interactions between any of these three effects were significant, as they are for ELT-3 cells as well. Again, in the AT-1 study as here, CR was found to play a statistically small to negligible role within the parameter space tested. It should be noted that expanded cooling rates were investigated in both the AT-1 (0.690°C/min) and ELT-3 (150°C/min) studies. The expanded CR range led to a drop from 7585% to 40% in survival for the AT-1 cells at 0.6°C/min, while the survival drop in ELT-3 cells was from between 7080% to 1520% at both 1 and 50°C/min when all other parameters were held at mild values. A comparison between the AT-1 and ELT-3 studies suggests that the trends in thermal parameter sensitivity between two cell types were similar, however the parameter thresholds necessary to induce significant survival reduction were dramatically different. It should also be noted that in addition to sharing similarities with single-cell studies, the general trends in ELT-3 cell survival are similar to those found in an experimental study of in-vivo skin cryosurgery in dogs (Gage et al., 1985
).
Finally, since the growth of many tumours including leiomyomata are hormonally dependent, and cryosurgical patients may be in varying stages of the menstrual cycle, it is important to investigate the relative effects of hormonal presence on cryosensitivity. It is perhaps not surprising that when oestradiol is present, under all conditions tested, the cryosensitivity of the cell line is increased as shown in Figure 5. This is perhaps an indication that a proliferating cell is more sensitive to thermal insult. It is well known that heat shock is tolerated poorly by cells in mid- to late S phase when the cell is fully committed to mitosis (Walsh et al., 1991
). Perhaps the same or a similar phenomenon is acting in the oestradiol-treated ELT-3 cells, which are reproducing more actively than cultures in the absence of hormone.
Cryosurgical implications
By far the most widely used approach in cryosurgery consists of an attempt to reach a lethal ET within the entire tumour by allowing the ice volume to grow beyond the tumour boundary (Gage, 1992). This critical isotherm approach is based on the clinical and experimental evidence reviewed above and elsewhere which supports the importance of ET in determining survival outcome at the cellular level. The ELT-3 cell-survival results support the importance of ET. The results also indicate that this destruction will occur in cells cooled to below 30°C, a temperature above the criteria usually used in designing cryosurgical protocols (40 to 60°C) (Gage, 1992
). In addition to the end-temperature effect, increased HT and slow thaw rate also have a positive effect in lowering cell survival in the ELT-3 system. This approach is generally recommended for any tumour in reviews on the subject of cryosurgery, however not all tumour cells show the same cryosenstivity (Gage, 1992
; Gage and Baust, 1998
). Our recent report on cryosensitivity in AT-1 prostate tumour cells using the same technique showed that these cells can significantly withstand cooling protocols to 60°C and below (Smith et al., 1999
). It is thus very important to verify the cryosensitivity of the specific tumour type one hopes to treat with cryosurgery.
In vivo, additional injury mechanisms may assist in defining the injury event. First, the cells are embedded in an extracellular matrix and may have a different response to freezing than when cultured and trypsinized prior to experimentation in suspension. Secondly, the microvasculature of the tissue usually contributes to injury by occluding after a freezethaw cycle (Gage and Baust, 1998; Hoffmann et al., 1999
). And finally, there is the possibility that an immunological reaction to the tissue is activated by the freezethaw process which accentuates its further destruction post-freeze. Unfortunately, these in-vivo effects have not been quantified in most tissues. Further understanding of these additional injury mechanisms in both animal and human tissue is currently being pursued in several laboratories (including ours). This information, combined with a knowledge of cellular injury due to the thermal parameters as reported here, will help to insure a good clinical outcome if uterine leiomyomata are treated with cryosurgery.
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Acknowledgments |
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Notes |
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References |
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Submitted on January 12, 2000; accepted on October 18, 2000.