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Experimental Studies |
1 From the Advanced Technology Ctr (Y.R., A.O., G.K., Y.M.) and Oncology Inst (T.T.), Chaim Sheba Medical Ctr, Tel-Hashomer 52621, Israel; Dept of Radiology, Universidad Complutense, Madrid, Spain (J.R.C.); Dept of Radiology, Brigham and Women’s Hosp, Harvard Medical School, Boston, Mass (S.E.M.); and Dept of Pharmacology, Faculty of Medicine, Hebrew Univ, Jerusalem, Israel (J.S.C.). Supported by Israel Science Foundation, Israel Cancer Research Fund, Adams Super Ctr for Brain Studies at Tel-Aviv Univ, Izmel program of Israel Ministry of Industry and Commerce, and NIH ROI NS 39335. Received May 18, 2003; revision requested Jul 15; final revision received Nov 18; accepted Jan 13, 2004. Address correspondence to Y.M. (e-mail: yael@tauphy.tau.ac.il).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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MATERIALS AND METHODS: Mice bearing C26 colon carcinoma tumors were treated with doxorubicin (n = 25) and with aminolevulinic acid–based photodynamic therapy (n = 23). Fourteen mice served as controls. Conventional T2-weighted fast spin-echo and diffusion-weighted MR images were acquired once before therapy and at 6, 24, and 48 hours after treatment. Pretreatment and early (1–2 days) posttreatment water diffusion parameters were calculated and compared with later changes in tumor volumes measured on conventional MR images by using the Pearson correlation test.
RESULTS: In chemotherapy-treated tumors, a significant correlation (P < .002, r = 0.6) was observed between diffusion parameters that reflected tumor viability, measured prior to treatment, and changes in tumor volumes after therapy. This correlation implies that tumors with high pretreatment viability will respond better to chemotherapy than more necrotic tumors. In tumors treated with photodynamic therapy, no such correlation was found. Changes observed in water diffusion 1–2 days after treatment significantly correlated with later tumor growth rate for both therapies (P < .002, r = 0.54 for photodynamic therapy; P < .0003, r = 0.61 for chemotherapy).
CONCLUSION: High-b-value diffusion-weighted MR imaging has potential use for the early detection of response to therapy and for predicting treatment outcome prior to initiation of chemotherapy.
© RSNA, 2004
Index terms: Colon, MR, 75.12141, 75.12144 • Colon neoplasms, 75.321 • Experimental study • Magnetic resonance (MR), diffusion study, 75.12144 • Magnetic resonance (MR), treatment planning, 75.12144
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Previous investigators of tumors in animal models (5–7) and in the human brain (8,9) have demonstrated the ability of diffusion-weighted MR imaging to distinguish solid and viable tumor from cystic and necrotic regions and have shown that tumor water diffusion is correlated with tumor cellularity (10–12). Bright regions on diffusion-weighted MR images are associated with viable tumor regions, whereas necrotic regions appear dark on diffusion-weighted MR images.
In several diffusion-weighted MR imaging studies (12–19), an increase in apparent diffusion coefficients for water in tumors has been found after various therapies. This finding correlated significantly with later tumor regression or decelerated growth and, thus, enabled early detection of tumor response. In most of these studies, standard diffusion-weighted MR imaging was used with b values less than or equal to 1,000 sec/mm2. Investigators in one recent clinical study (20) demonstrated enhanced sensitivity with the use of high-b-value (b of approximately 4,000 sec/mm2) diffusion-weighted MR imaging for early detection of response to radiation therapy.
Furthermore, it has been suggested that various MR methods have potential use for predicting tumor response to treatment (21,22). The results of several studies of diffusion-weighted MR imaging have suggested that the initial apparent diffusion coefficient can serve as a predictive parameter for response to chemotherapy in primary mammary tumors in rats (7) and for response to chemotherapy and/or radiation therapy in human rectal cancers (23,24).
The purpose of our study was to evaluate the use of diffusion-weighted MR imaging with standard and high b values for pretreatment prediction and early detection of tumor response to various antineoplastic therapies in an animal model.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Animal and Tumor Model
Sixty-two male BALB/C mice (Bagg Albino, inbred research mouse strain), 10 weeks old and with an average weight of 25 g, were inoculated with C26 colon carcinoma cells by the laboratory technician. The C26 colon carcinoma cell line was maintained at 37°C in Dulbecco modified Eagle medium enriched with 10% fetal calf serum and penicillin-streptomycin 1%, and was subcultured twice a week. Tumors were implanted with one subcutaneous injection of 106 cells (200 µL of a solution containing 5 x 106 cells per milliliter, counted by using trypan blue stain) into the right thigh of BALB/C mice.
Antitumor Treatments
Mice in the treatment group were treated aggressively with 5-aminolevulinic acid–based photodynamic therapy (PDT) or were given intravenous doxorubicin chemotherapy. PDT and chemotherapy differ in the mechanism of their action: PDT is a regional therapy that induces early destruction of tissue, whereas the effect of chemotherapy is systemic and seen much later. Chemotherapy or PDT was carried out 10–14 days after tumor induction. The delay was designed to allow most of the tumors to achieve a volume of 0.5–1.0 cm3 prior to treatment. For chemotherapy, 25 mice were injected intravenously with doxorubicin at a dose of 10 mg per kilogram of body weight by the laboratory technician. For PDT, which was administered by one of the authors (Y.R.), 23 mice were given an intraperitoneal injection of 5-aminolevulinic acid (ALA; FineTech, Haifa, Israel) at a dose of 200 mg per kilogram of body weight 2–3 hours before exposure to filtered light. Intraperitoneal injection was used to achieve systemic administration and to comply with accepted clinical protocol. A light-delivery system (VersaLight; ESC Medical Systems, Yokneam, Israel) was used for focused surface irradiation of the tumors with red-filtered light (580–720 nm, fluence 360 J/cm2). Fourteen mice served as controls and received no treatment.
Diffusion-weighted MR Method
Diffusion-weighted MR imaging was performed by using a conventional T2-weighted pulse sequence with diffusion-weighting gradients to filter out the signal from high-mobility water molecules and enhance the sensitivity of the method for depicting molecular diffusion and mobility (25). At low diffusion-weighting gradient levels, most of the signal from the tissue is recorded on the images. At high diffusion-weighting gradient levels, most of the signal is filtered out, and the signal remaining originates mostly from low-mobility molecules.
With this method, the normalized intensity of the water signal is given as
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To quantify the diffusion characteristics of the tissue as reflected in the diffusion curve, we defined a diffusion index, RD (no units), which is the normalized summation over the curve
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The change in the diffusion curve after therapy is quantified by the index 
RD, calculated as
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RD should reflect changes in tumor viability, intracellular water fraction, and integrity of cell membranes that may affect permeability.
Data Acquisition
Data were acquired at the Chaim Sheba Medical Center by using a 0.5-T interventional MR imaging unit (Signa SP/i; GE Medical Systems, Milwaukee, Wis) with a Genesis operating system (Stockport, England), gradient intensity less than or equal to 1 x 10–4 T/cm (1 G/cm), and a line-scan diffusion-weighted pulse sequence (26). A specially designed animal volume coil with a diameter of 5 cm was used for data acquisition.
T2-weighted and diffusion-weighted MR images were acquired 1 day prior to treatment and 6, 24, and 48 hours after treatment. In addition, T2-weighted images were acquired 14 days after treatment.
T2-weighted fast spin-echo images were acquired with the following parameters: repetition time msec/echo time msec, 3,000/40; matrix, 256 x 128; field of view, 8 x 6 cm; echo train length, 16; section thickness, 3 mm; acquisition time for 15 sections, 5 minutes. With this section thickness, tumors could be clearly discerned in three to five sections. Line-scan diffusion-weighted MR images were acquired with the following parameters: 5,440/142; matrix, 64 x 64; field of view, 8 x 6 cm; section thickness, 4 mm. A section thickness of 4 mm was used to increase the signal-to-noise ratio. Since the tumor appeared in at least three 3-mm sections, a section of 4 mm could be acquired in the tumor center as observed on the T2-weighted images without partial volume effects. The diffusion gradient duration was 68 msec, and separation between gradients was 78.7 msec. Twenty different values of the diffusion factor b (range, 15–4,000 sec/mm2), obtained by incrementally increasing the diffusion gradient intensity from 0.055 to 0.9 G/cm, were used. The image acquisition time was 5 minutes 56 seconds per section.
Because of the long acquisition times at 0.5 T, diffusion was measured in a single direction with all three gradient pulses applied simultaneously in each acquisition. Because the C26 tumors were naturally isotropic and mouse orientation was reasonably reproducible, the effect of anisotropy on measured diffusion indices was negligible.
Assessment of Tumor Response
Tumor volumes were calculated by using fast spin-echo T2-weighted images, on which the tumors appeared to have high signal intensity relative to that of neighboring muscle. An ROI was defined over the entire apparent tumor in each section, and the number of pixels was counted by one of the authors (Y.R.). Tumor volumes were calculated in cubic centimeters prior to treatment and 14 days after treatment. Response to treatment was determined by the change in tumor volume, defined as
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The treatment effect, as reflected in change in the diffusion index (RD), was correlated with the degree of response determined by V; hence, data were not stratified according to whether tumors were responsive or nonresponsive.
Analysis of Diffusion-weighted MR Imaging Data
Image analysis was performed by using special software (Interactive Data Language, version 3.6.1, Research Systems, Crowthorne, England; and Physics Analysis Workstation, version 2.09.18, CERN, Geneva, Switzerland).
Diffusion curves were obtained by plotting the logarithmic signal intensity of an ROI in the tumor (I), normalized to the signal intensity with no diffusion gradients (I0), as a function of b (Eq [1]). Changes in the diffusion curves acquired 1–2 days after treatment (RD) were calculated from diffusion indices (RD) obtained by summing over b values of 2,000–4,000 sec/mm2 or less (depending on the noise level in the specific tumor). For each tumor, both RDi and RDf were calculated by using the same number of b values, and RD was then calculated by using Equation (4) and normalized to 14 b values to enable analysis of all tumors according to the same scale. For all tumors, the same range of b values was used in the calculation of diffusion indices for pretreatment prediction of response to therapy. To ensure a level far above that of noise, we calculated the diffusion index, RD (Eq [2]), by summing over 14 b values ranging from 15 to 2,741 sec/mm2. The diffusion parameters were then correlated with changes in tumor volumes 2 weeks after treatment, compared with pretreatment tumor volumes.
The early changes in the diffusion curves after treatment (RD) and the pretreatment diffusion index (RD) were calculated for two methods of ROI definition: ROIs chosen in the tumor areas that appeared bright on the diffusion-weighted MR images acquired at b of 1,000 sec/mm2, as well as ROIs chosen over the entire tumor (selected from the T2-weighted images). ROIs were defined by one of the authors (Y.R.) on T2-weighted images that depicted the central 4-mm section of the tumor, to avoid partial volume effects. The position and orientation of the mouse were accurately depicted on consecutive T2-weighted images. Images were acquired in sections parallel to the head-to-tail axis of the mouse, and the center of the tumor was located in the center of the magnet, as defined by the cross-mark of laser beams. Posttreatment ROIs were defined in accordance with pretreatment ROIs, so that ROI mismatch was negligible. In all cases, ROIs were 0.3–2.0 cm2.
Statistical Analysis
The statistical analysis was performed by using software (InStat, version 3.05; GraphPad Software, San Diego, Calif). A two-sample one-tailed Student t test was used to compare changes in volume (V) and diffusion index (RD) between chemotherapy-treated, PDT-treated, and control groups. Analysis of correlation between MR image–derived V, initial tumor volume Vb, and diffusion parameters (RD and RD) for chemotherapy-treated and PDT-treated tumors was performed by using a two-sided parametric Pearson correlation test. In each case, the test for correlation between volume and diffusion parameters was performed for the two methods of ROI definition (described in the previous section). In addition, the correlation between V and diffusion parameters measured with standard diffusion-weighted imaging (with b less than or equal to 1,000 sec/mm2) was analyzed. P of less than .01 was considered to indicate a statistically significant difference.
Prior to initiation of the study, we estimated a linear correlation coefficient r of about 0.5. To obtain P < .005, our study population had to include approximately 30 mice in each treatment group (based on the linear-correlation coefficient table). The actual number of mice included in this study (25 chemotherapy-treated and 23 PDT-treated mice) was lower as a result of experimental conditions. The treatment effect turned out to be greater than expected; therefore, the r and P values actually obtained were better than our initial estimates.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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V) obtained prior to treatment and 14 days after treatment. RD was plotted as a function of V (Fig 2).
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V when using standard diffusion weighting with b values of 1,000 sec/mm2 or less (P = .1). A significant positive correlation was found between pretreatment volume and posttreatment changes in volume for both chemotherapy-treated and PDT-treated tumors (P < .0001, r = 0.70 for both groups). On the other hand, no significant correlation was found between pretreatment RD and pretreatment tumor volume (P = .3).
Early Posttreatment Response
The effect of therapy on diffusion soon after treatment was manifested by a substantial increase in signal decay rate calculated as a function of b. Typical diffusion curves for responsive and nonresponsive chemotherapy-treated tumors are shown in Figure 3. In chemotherapy-treated tumors, substantial changes in diffusion were observed 24–48 hours after treatment. In the PDT-treated tumors, substantial changes in diffusion were observed 6–24 hours after treatment. No substantial changes in diffusion were observed in control tumors. Average changes in tumor volumes (V, Eq [5]) and diffusion curves (RD, Eq [4]) were calculated for treatment and control groups (Fig 4). The observed treatment effect on tumor growth rates and on tumor diffusion properties was highly significant for both treatment groups. For chemotherapy- and PDT-treated tumors, average volume changes (± standard deviations) were 0.79 cm3 ± 0.13 and 1.41 cm3 ± 0.12, respectively, compared with 2.76 cm3 ± 0.33 for tumors in control mice. Results of a comparison of volume changes between treated tumors and tumors in control mice with use of a two-sample one-tailed t test indicated a statistically significant difference (P < .0001 and P < .0007 for chemotherapy-treated and PDT-treated tumors, respectively). An average negative change in the tumor diffusion index after treatment was observed for both treatment groups (RD = –3.1 ± 0.5 and RD = –4.4 ± 1.0, for chemotherapy-treated and PDT-treated tumors, respectively). The effect was greater in the PDT-treated tumors. In contrast, a small positive change in the diffusion index was observed in tumors in control mice (RD = 0.68 ± 0.45; P < .0001 for comparison of chemotherapy-treated and PDT-treated tumors with controls).
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RD with V. A positive correlation was found between changes in the diffusion index 1–2 days after treatment (calculated from ROIs chosen in tumor regions that appeared bright on diffusion-weighted MR images acquired with b of 1,000 sec/mm2) and changes in tumor volume 14 days after treatment, for both treatment groups (Fig 5). An early increase in the absolute value of RD, which reflected decreased tissue viability, was correlated with a later reduction in tumor growth rate. These results demonstrate the potential of high-b-value diffusion-weighted MR imaging for early detection of response to therapy (P < .002, r = 0.54 for PDT-treated tumors, and P < .0003, r = 0.61 for chemotherapy-treated tumors; Pearson correlation). When RD was calculated from ROIs defined over the entire tumor, however, the P values were higher (P = .012 for chemotherapy-treated tumors and P = .016 for PDT-treated tumors).
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RD and V was also studied by using standard diffusion-weighted MR imaging with b less than or equal to 1,000 sec/mm2. For PDT-treated tumors, the correlation was similar to that found by using high-b-value diffusion-weighted MR imaging (P < .002, r = 0.54). For chemotherapy-treated tumors, the correlation was even stronger than that found with high-b-value diffusion-weighted MR imaging (P < .004, r = 0.42). |
DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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In this study, we found that the correlation between RD and tumor volume increment was better when RD was calculated for ROIs chosen in tumor areas that appeared bright on diffusion-weighted MR images. Hence, we conclude that diffusion-weighted MR imaging is more sensitive to posttreatment diffusion changes in bright (viable) tumor regions than in dark (necrotic) regions. It is reasonable to assume that necrotic tissue will not respond to therapy; hence, including necrotic tissue in the ROI will decrease the sensitivity of the method for detection of early treatment response. Nevertheless, for accurate pretreatment prediction of treatment outcome, the degree of viability of the entire tumor must be determined. The best indication of tumor viability and cellularity, and, hence, predicted sensitivity to chemotherapy, is obtained from ROIs defined over the entire tumor. This hypothesis is consistent with the higher correlation found between prechemotherapy RD and posttreatment changes in tumor volumes in ROIs defined over the entire tumor relative to ROIs chosen from viable regions in the tumor.
In this study, we treated mice bearing C26 colon carcinoma tumors by using either aggressive aminolevulinic acid–based PDT or intravenous doxorubicin chemotherapy and assessed the potential of high-b-value diffusion-weighted MR imaging for pretreatment prediction and early detection of tumor response to these two treatment types.
A possible explanation for the significant correlation found between the prechemotherapy diffusion parameters and treatment outcome may be related to the fact that cancer cells near necrotic regions may experience hypoxic conditions and have slower metabolisms and, therefore, may be less sensitive to chemotherapy (27). Furthermore, the distribution of chemotherapeutic agents in necrotic tumors may be less efficient because of insufficient vascularity. The significant correlation between pretreatment diffusion and posttreatment response in chemotherapy-treated tumors indicates that for some types of treatment, high-b-value diffusion-weighted MR imaging may be useful for predicting outcome prior to initiation of treatment.
The fact that we observed no correlation between pretreatment RD and posttreatment response in the PDT-treated tumors might be due to the more global effect of thrombosis and damage to blood vessels caused by PDT (28), which may lead to coagulative necrosis in addition to (possible) apoptotic cell death. The aggressive quality of PDT may result in a similar treatment effect both in viable tumors and in more necrotic tumors, so that treatment outcome might be less dependent on tumor viability and tumor cell metabolism.
The results of our comparison between high-b-value diffusion-weighted MR imaging and standard-b-value diffusion-weighted MR imaging demonstrate the advantage of using high-b-value diffusion weighting. In this study, a significant correlation between pretreatment diffusion parameters and tumor response to chemotherapy was found only by using the high-b-value images. There are at least three previously published reports (7,23,24) of a similar correlation found between pretreatment diffusion properties and later tumor response by using standard diffusion-weighted imaging. Lemaire et al (7) showed that primary rat mammary tumors with relatively low pretreatment apparent diffusion coefficients (n = 3) responded to chemotherapy better than tumors with much higher pretreatment apparent diffusion coefficients (n = 7). The authors monitored large tumors (approximately 5 cm3) in which a wide range of apparent diffusion coefficients ([0.7–1.8] x 10–3 mm2/sec) was found. In the presence of more moderate variability in apparent diffusion coefficients among tumors (eg, [0.4–0.8] x 10–3 mm2/sec, the range in our study), the enhanced sensitivity of higher b values is necessary for pretreatment prediction of response to therapy. Dzik-Jurasz et al (23) and Hein et al (24) showed a negative correlation between pretreatment apparent diffusion coefficients and response of rectal tumors to combined chemotherapy and radiation therapy, such that tumors with lower apparent diffusion coefficients and higher signal intensity at diffusion-weighted MR imaging responded better to therapy. Both studies were performed with standard b values.
A significant correlation between early posttreatment changes in diffusion characteristics and later tumor response was found by using standard diffusion-weighted MR imaging. Still, high-b-value diffusion-weighted MR imaging demonstrated a higher correlation for chemotherapy-treated tumors. This trend accords with previous findings regarding the response to radiation therapy in human brain tumors (20).
The considerable decrease in the value of RD (–RD) observed soon after treatment in both chemotherapy-treated and PDT-treated tumors probably reflects the evolution of early necrosis after treatment, which leads to decreased cell density and more free water diffusion. On the other hand, the small positive change in the diffusion index observed in control tumors may reflect a natural increase in tumor viability and cell density.
The effect of treatment as reflected in the diffusion curves was greater for PDT-treated tumors than for chemotherapy-treated tumors. The changes in PDT-treated tumors could be observed also on diffusion-weighted images acquired by using standard b values; thus, the correlation between early changes in routine diffusion characteristics after PDT and later tumor response was similar to changes calculated on the basis of high-b-value images. These data might indicate a more rapid response to treatment in the PDT-treated group (6–24 hours) compared with the chemotherapy-treated group, in which prominent diffusion-weighted MR imaging changes were detected no sooner than 24 hours (in most cases, 48 hours) after treatment. Hence, for the tumors treated in this study, it was found that the optimal timing of diffusion-weighted imaging for detection of postchemotherapy changes was 48 hours or more after treatment. The effect of treatment on V was more pronounced in chemotherapy-treated tumors than in the PDT-treated group. Therefore, the results of this study suggest that the diffusion-weighted MR imaging response pattern should be studied separately for different types of clinical therapies.
This study is limited in that it was performed with a relatively low magnetic field of 0.5 T and relatively weak diffusion gradient of 1 x 10–4 T/cm (1 G/cm). The data were acquired by using line-scan diffusion-weighted MR imaging, which is less sensitive to motion and susceptibility artifacts but yields relatively low signal-to-noise data per unit of acquisition time and requires longer acquisition times. To compensate for the low signal-to-noise ratio, we performed imaging with a wide range (n = 20) of b factor values (15–4,000 sec/mm2), which resulted in relatively long acquisition times (5 minutes 56 seconds per section). In addition, we used normalized signal intensities for quantification of diffusion curves instead of fitting the data to a biexponential function and calculating apparent diffusion coefficients and volume fractions. With single-shot diffusion-weighted echo-planar imaging (29), which is available on most new MR machines, several sections may be imaged without increasing acquisition times. This type of sequence, given its availability and short acquisition times, would be more appropriate for routine clinical use than the method presented here, although some susceptibility artifacts may occur in boundary areas. A combination of short acquisition times and reduced vulnerability to susceptibility artifacts is offered by novel diffusion imaging techniques such as slab-scan diffusion imaging (30), or single-shot sensitivity-encoded echo-planar imaging (31). High-field-strength (3-T) MR imaging systems suitable for clinical use are rapidly evolving, and we are currently widening our investigations to include clinical studies with a 3-T MR system.
The control mice did not receive any sham treatment, since the purpose of our study was to determine whether a correlation existed between the magnitude of the treatment effect as reflected in diffusion-weighted MR imaging and the change in tumor volume. The factors that influenced therapy outcome therefore were not considered relevant.
Practical application: In this study, we assessed high-b-value diffusion-weighted MR imaging for early detection of response to therapy and compared the diffusion-weighted MR imaging response patterns of two different therapy modalities. Our results clearly suggest that diffusion-weighted MR imaging may be used to predict treatment outcome prior to initiation of chemotherapy. Moreover, our results demonstrate the potential usefulness of high-b-value diffusion-weighted MR imaging for noninvasive pretreatment prediction and early posttreatment evaluation of response and suggest that this method may help in the near future to optimize the management of malignancy.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Abbreviations: PDT = photodynamic therapy, ROI = region of interest
Author contributions: Guarantor of integrity of entire study, Y.M.; study concepts and design, Y.M., Y.R., A.O., J.S.C., G.K.; literature research, Y.M., Y.R.; experimental studies, Y.M., Y.R.; data acquisition, Y.M., Y.R., J.R.C.; data analysis/interpretation, Y.M., Y.R., J.S.C., G.K., T.T., S.E.M.; statistical analysis, Y.M., Y.R.; manuscript preparation and editing, Y.R., Y.M.; manuscript definition of intellectual content and final version approval, all authors; manuscript revision/review, A.O., G.K., J.R.C., T.T., S.E.M., J.S.C.
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1,000 sec/mm2) 14 days after chemotherapy, for ROIs defined over the entire tumor. D, Plot of pretreatment RD values as a function of 
) and 1 (
) and 2 (
) days after treatment for ROIs in areas that appeared bright on diffusion-weighted MR images acquired with b of 1,000 sec/mm2. Measurement in the same ROIs was repeated on consecutive days. x = noise level.
