Nuclear Medicine and Molecular Imaging • Original Research Rakheja et al. PET/MRI of Neoplasms
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Nuclear Medicine and Molecular Imaging Original Research
Correlation Between Standardized Uptake Value and Apparent Diffusion Coefficient of Neoplastic Lesions Evaluated With Whole-Body Simultaneous Hybrid PET/MRI Rajan Rakheja1 Hersh Chandarana2 Linda DeMello1 Kimberly Jackson 3 Christian Geppert 3 David Faul 3 Christopher Glielmi 3 Kent P. Friedman1 Rakheja R, Chandarana H, DeMello L, et al.
Keywords: apparent diffusion coefficient, MRI, PET/CT, PET/MRI, standardized uptake value DOI:10.2214/AJR.13.11304 Received May 22, 2013; accepted without revision May 29, 2013. 1 Department of Radiology, Division of Nuclear Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016. Address correspondence to K. P. Friedman ([email protected]). 2 Department of Radiology, Abdominal Imaging Section, NYU Langone Medical Center, New York, NY. 3
MR R&D Collaborations, Siemens Healthcare, New York, NY.
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OBJECTIVE. The purpose of this study was to assess the correlation between standardized uptake value (SUV) and apparent diffusion coefficient (ADC) of neoplastic lesions in the use of a simultaneous PET/MRI hybrid system. SUBJECTS AND METHODS. Twenty-four patients with known primary malignancies underwent FDG PET/CT. They then underwent whole-body PET/MRI. Diffusion-weighted imaging was performed with free breathing and a single-shot spin-echo echo-planar imaging sequence with b values of 0, 350, and 750 s/mm2. Regions of interest were manually drawn along the contours of neoplastic lesions larger than 1 cm, which were clearly identified on PET and diffusion-weighted images. Maximum SUV (SUVmax) on PET/MRI and PET/CT images, mean SUV (SUVmean), minimum ADC (ADCmin), and mean ADC (ADCmean) were recorded on PET/ MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient. Pearson correlation coefficient was used to asses the following relations: SUVmax versus ADCmin on PET/MR and PET/CT images, SUVmean versus ADCmean, and ratio of SUVmax to mean liver SUV (SUV ratio) versus ADCmin. A subanalysis of patients with progressive disease versus partial treatment response was performed with the ratio of SUVmax to ADCmin for the most metabolically active lesion. RESULTS. Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. A significant inverse Pearson correlation coefficient was found between PET/MRI SUVmax and ADCmin (r = –0.21, p = 0.04), between SUVmean and ADCmean (r = –0.18, p = 0.07), and between SUV ratio and ADCmin (r = –0.27, p = 0.01). A similar inverse Pearson correlation coefficient was found between the PET/CT SUVmax and ADCmin. Twenty of 24 patients had previously undergone PET/CT; five patients had a partial treatment response, and six had progressive disease according to Response Evaluation Criteria in Solid Tumors 1.1. The ratio between SUVmax and ADCmin was higher among patients with progressive disease than those with a partial treatment response. CONCLUSION. Simultaneous PET/MRI is a promising technology for the detection of neoplastic disease. There are inverse correlations between SUVmax and ADCmin and between SUV ratio and ADCmin. Correlation coefficients between SUVmax and ADCmin from PET/ MRI were similar to values obtained with SUVmax from the same-day PET/CT. Given that both SUV and ADC are related to malignancy and that the correlation between the two biomarkers is relatively weak, SUV and ADC values may offer complementary information to aid in determination of prognosis and treatment response. The combined tumoral biomarker, ratio between SUVmax and ADCmin, may be useful for assessing progressive disease versus partial treatment response.
P
ET/CT is used routinely to diagnose and stage disease and evaluate response to therapy for many cancers [1–3]. Maximum standardized uptake value (SUVmax) from PET/CT is a measure of tumoral glucose metabolism and has been found to correlate with tumor grade [4] and other histopatho-
logic features, such as mitotic count and the presence of necrosis [5]. Diffusion-weighted MRI (DWI) is also increasingly used in the evaluation of neoplastic diseases. Restriction of diffusion can be quantified by the apparent diffusion coefficient (ADC), which has been found to correlate with cellularity [6, 7]. Like the SUV from PET/CT, ADC has
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Rakheja et al. been used clinically to differentiate benign from malignant tumors [8–10] and to assess tumor grade, delineate tumor extent, and predict survival [6, 11, 12]. Results of several studies have suggested an inverse correlation between SUVmax and ADC across varying malignancies [13–17]. Although these two biomarkers of tumoral cellularity have been suggested to correlate, to our knowledge all of the previously published research was performed on separate PET and MRI systems and on different imaging days, sometimes weeks apart. We aimed to assess the correlation between the SUV and ADC of neoplastic lesions using a simultaneous PET/MRI hybrid imaging system to more accurately assess the relation between these values by eliminating limitations such as patient motion between separate PET/CT and MRI examinations and by minimizing potential physiologic and treatment changes in the tumor due to the time interval between the PET and MRI examinations. Subjects and Methods Patient Studies This HIPAA-compliant study received local institutional review board approval. Patients undergoing clinically indicated PET/CT were recruited for a research PET/MRI examination from August 2012 through December 2012. All patients provided written informed consent for the PET/MRI examination. Twenty-four consecutively enrolled patients (six men, 18 women; average age, 65.4 years) with known metastatic cancer underwent FDG PET/CT immediately followed by a wholebody PET/MRI examination performed with residual FDG from the initial injection for PET/CT.
PET/CT All patients fasted for 4 hours before imaging. Insulin was withheld 6 hours before imaging. Blood glucose concentration was verified to be less than 200 mg/dL. All patients were adults who received a fixed 15-mCi IV dose of FDG. Patients were instructed to sit quietly in a dimly lit room for 45 minutes after the injection. Acquisitions were performed from the base of the skull to the mid thighs. Board-certified nuclear physicians read the PET/CT images and provided clinical interpretation; this examination was considered the reference standard for our study. PET/CT was performed with a Biograph mCT system (Siemens Healthcare). The CT parameters were as follows: 120 kVp, 95 mA, 5.0-mm slice width, 50-cm transaxial FOV, 512 × 512 transaxial image matrix. The PET parameters were as follows: 15 mCi FDG injected, 2 minutes per bed position, 814-mm transaxial FOV, 200 × 200 transaxial matrix, 3-mm gaussian postreconstruction image filter. PET images were reconstructed with
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CT for attenuation correction with the attenuationweighting ordered subsets expectation-maximization 3D algorithm at two iterations and 24 subsets. With these parameters the transaxial voxel size was 4.07 × 4.07 mm and the axial voxel size 2.03 mm.
of-stars trajectory with parameters as follows: TR/ TE 4.5/2; slice thickness, 2.5 mm; flip angle, 12°; number of axial slices, 80; bandwidth, 400 Hz/pixel; voxel size, 1.4 × 1.4 × 2.5 mm; quick fat-saturation mode. T2-weighted images were acquired in the coronal plane with the following parameters: STIR; TR/TE, 6250/56; inversion time, 220 ms; number of slices 36; nominal voxel size, 1.75 × 1.75 × 5 mm; bandwidth, 300 Hz/pixel; GRAPPA factor, 3. The PET acquisition time was 6 minutes and the MRI acquisition time approximately 10 minutes for each bed position. All patients had one bed position each for the pelvis, abdomen, thorax, and head and neck. Total imaging time for these bed positions ranged from 45 to 60 minutes. The PET data were reconstructed with an iterative 3D ordinary Poisson ordered subsets expectation-maximization algorithm at three iterations and 21 subsets and with a 4-mm gaussian postreconstruction image filter. The transaxial image matrix size was 172 × 172 mm with a transaxial FOV of 717.2 mm and an axial FOV of 258 mm. The transaxial voxel size for the PET/MRI PET images was 4.17 × 4.17 mm and the axial voxel size 2.03 mm.
PET/MRI Immediately after PET/CT, patients were imaged with the PET/MRI system (Biograph mMR, Siemens Healthcare). Because patients had to be transported to another building for PET/MRI, imaging was begun a total of 120–150 minutes after the initial injection of FDG. PET and MRI data were acquired simultaneously. For each bed position, an approximately 20-second breath-hold MRI attenuation correction map was acquired with a T1-weighted Dixon-based segmentation model. Thereafter, diagnostic MRI sequences (coronal T1-weighted turbo spin echo [TSE], T1-weighted gradient-echo imaging with radial stack-of-stars trajectory volumetric interpolated breath-hold examination [VIBE], T2weighted, and transverse DWI) were performed simultaneously with PET data acquisition during free breathing. T1-weighted TSE images were acquired with the following parameters: TR/TE, 500/9.5; slice thickness, 5 mm; refocusing flip angle, 140°; number of coronal slices, 35; bandwidth, 266 Hz/ pixel; voxel size, 1.6 × 1.2 × 5 mm; and parallel imaging generalized autocalibrating partial parallel acquisition (GRAPPA) factor, 2. DWI was performed with a single-shot spin-echo echo-planar imaging sequence with parameters as follows: TR/ TE, 5900/54; slice thickness, 6 mm; number of axial slices, 30; bandwidth, 1628 Hz/pixel; voxel size, 2.6 × 2.1 × 6 mm; parallel imaging GRAPPA factor, 2; fat-saturation mode; b values, 0, 350 and 750 s/ mm2. Radial VIBE images were acquired as a stack-
Image Analysis Nuclear physicians trained in PET/CT interpreted the PET/CT images independently. The PET/ MRI images were jointly read by a nuclear physician with experience in PET/CT and a radiologist with experience in MRI. Regions of interest (ROIs) were manually drawn along the contours of the neoplastic lesions that were clearly identified on PET images by the same experienced PET/CT nuclear physician (a single reader). The ROI was then copied to the DW images with fusion software (MIM 5.4, MIM Software), and ADC contours were
TABLE 1: Correlations Between Standardized Uptake Value (SUV) and Apparent Diffusion Coefficient (ADC) for All Lesions Comparison
R
p
−0.21
0.04
PET/MRI SUVmean vs ADCmean
−0.18
0.07
PET/MRI SUV ratio vs ADCmin
−0.27
0.01
PET/CT SUVmax vs ADCmin
−0.29
0.008
PET/CT SUV ratio vs ADCmin
−0.25
0.02
PET/MRI SUVmax vs ADCmin
Note— max = maximum, min = minimum. SUV ratio = ratio of SUVmax to mean liver SUV.
TABLE 2: Correlations of PET/MRI Standardized Uptake Value (SUV) and Apparent Diffusion Coefficient (ADC) of Osseous Metastatic Lesions (n = 17) Comparison SUVmax vs ADCmin
R
p
−0.12
0.24
SUVmean vs ADCmean
−0.05
0.14
SUV ratio vs ADCmin
−0.46
0.04
Note—max = maximum, min = minimum. SUV ratio = ratio of SUVmax to mean liver SUV.
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PET/MRI of Neoplasms slightly modified because of the subtle misregistration between ADC maps and PET data. The main contributing factors to misalignment in echo-planar imaging sequences are eddy current–induced image distortion and the nonlinearities of the gradient coils. Automated threshold-based ROIs could not be used because the software could not draw accurate ROIs on ADC maps, although our method is similar to that previously described [18]. Mean ADC (ADCmean) was defined as the average ADC value for all voxels in each lesion, and minimum ADC (ADCmin) as the lowest ADC value among all voxels in each lesion. SUVmax (on PET/ MRI and PET/CT images), mean SUV (SUVmean), ADCmin, and ADCmean were recorded on PET/MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient (if there were more than three lesions, the most intensely FDG-avid lesions were chosen). Relations between SUVmax and ADCmin, SUVmean and ADCmean and between the ratio of SUVmax to mean liver SUV (SUV ratio) and ADCmin were assessed with the Pearson correlation coefficient. A ratio of SUVmax to ADCmin was calculated for a subset of patients with partial treatment response versus progressive disease according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 [19].
Results Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. There was weak to moderate correlation between SUV and ADC for nonosseous soft-tissue lesions (Table 1). There was no correlation between SUV and ADC for osseous lesions. However, there was a significant negative correlation between lesion SUV ratio and ADCmin (Table 2). There was a strong correlation between SUVmax values from PET/CT and PET/MRI (r = 0.725, p < 0.001). There was no difference in correlation between ADC and SUV from PET data obtained from PET/CT and PET/MRI. Twenty of 24 patients had previously undergone PET/CT. Five patients had a partial treatment response and six had progressive disease according to RECIST 1.1 [19]. The others had stable disease. All patients underwent interval chemotherapy (we include monoclonal antibody treatments in chemotherapy). The ratio of SUVmax to ADCmin based on PET/MRI of the most metabolical-
TABLE 3: PET/MRI Ratios Between Standardized Uptake Value (SUV) and Apparent Diffusion Coefficient (ADC) for the Most Active Tumors in Patients With Partial Treatment Response Lesion Location
Primary Malignancy MRI SUVmax MRI SUVmean
ADCmin
ADCmean
SUVmax / ADCmin
1.32
7.06
Left lower lobe nodule
Breast
8.80
7.20
1.02
Paraaortic node
Breast
15.40
10.70
0.97
1.11
11.03
Lung
5.20
4.30
1.41
2.62
3.04
Left lower lobe nodule Right upper lobe nodule
Lung
1.70
1.40
1.40
1.80
1
Right apical mass
Lung
6.30
3.90
0.94
1.30
4.15
7.48
5.50
1.15
1.63
5.26
Mean value for all locations
Note—Partial treatment response according to Response Evaluation Criteria in Solid Tumors version 1.1. max = maximum, min = minimum.
TABLE 4: PET/MRI Ratios Between Maximum Standardized Uptake Value (SUV) and Minimum Apparent Diffusion Coefficient (ADC) for the Most Active Tumors in Patients With Progressive Disease Lesion Location
Primary Malignancy MRI SUVmax MRI SUVmean ADCmin
ADCmean
SUVmax / ADCmin 10.18
Peritoneum
Ovarian
10.00
5.70
0.56
0.97
Right hilar node
Ovarian
8.10
7.10
1.19
1.31
5.97
Subcarina
Lymphoma
14.60
11.80
0.73
1.03
16.16
Pancreas
Lung
9.70
8.10
1.08
1.39
7.50
Right upper lobe mass
Lung
12.90
10.40
0.86
1.62
12.09
Left upper lobe mass
Lung
14.40
11.90
0.47
0.94
25.32
11.62
9.17
0.82
1.21
12.87
Mean value for all locations
Note—Progressive disease according to Response Evaluation Criteria in Solid Tumors version 1.1. max = maximum, min = minimum.
ly active lesion in each patient was calculated. The average lesion size in this subanalysis was 2.1 cm. The ratio of SUVmax to ADCmin was higher for patients with progressive disease than for those with a partial response (Tables 3 and 4 and Figs. 1 and 2). Discussion PET entails the use of FDG to depict differences in glucose metabolism between physiologic and malignant cells to diagnose neoplastic processes. FDG, a glucose analogue, is trapped within cells, which are unable to further metabolize the radiotracer after phosphorylation. The SUV from PET/CT is commonly used to quantify tumor glucose metabolism and is an indirect biomarker of tumor cellularity [20, 21]. SUVmax is used in most clinical studies because it is independent of tumor size and shape and thus highly reproducible. SUVmean, however, is based on the estimation of tumor boundaries (either with a threshold technique or by subjective visual analysis) and is thus more variable [13]. DWI provides information on the brownian motion of water molecules in tissues. ADC is a calculated parameter derived from DWI. ADC values depend on the presence of barriers to diffusion within the water microenvironment, and the physical boundaries of cell membranes restrict water diffusion in both normal and neoplastic tissues [13]. ADC has been found to inversely correlate with tumor cellularity [6, 7, 22]. ADC has also been applied clinically to differentiate benign from malignant tumors [8–10, 23], to differentiate tumor types, to assess tumor grade, to delineate tumor extent, and to predict survival [6, 11, 12]. Studies have shown that DWI is a valuable imaging modality for detecting metastasis and cancer relapse; it has also been used to assess treatment response in various malignancies [24–26]. PET/CT and DWI share applications in the field of clinical oncology. Whereas both SUV and ADC correlate with cellularity, SUV also correlates with several other pathologic markers, such as mitotic count, presence or absence of necrosis [5], MIB proliferation marker expression, and p53 tumor suppressor gene function [4]. It remains a question for research to further define how these two parameters may be combined to improve the diagnosis and management of cancer. The published results of preliminary work investigating a link between SUV and ADC have been mixed. In a study by Ho et al. [13], patients with documented primary cervical cancer underwent abdominopelvic DWI and
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Fig. 1—65-year-old woman with metastatic ovarian cancer and FDG-avid left upper abdominal peritoneal implant. A and B, PET image (A) and apparent diffusion coefficient map (B) show maximum standardized uptake value in region of interest (arrow) is 10.1 and minimum apparent diffusion coefficient is 0.56.
A
B
FDG PET/CT within 2 weeks of each other. Although SUVmax and ADCmin were not correlated, relative ADCmin, defined as the ratio between ADCmin and ADCmean, inversely correlated with relative SUVmax. In a study by Wu et al. [14], 15 patients with histologically proven diffuse large B-cell lymphoma underwent pretherapy FDG PET/CT and DWI within 2 days of each other. The analysis showed no correlation between the ADCmean and the SUVmax or SUVmean of the lesions. In a study by Nakajo et al. [15], 44 patients with breast cancer underwent preoperative PET/CT and DWI within an average of 17 days between examinations, and both SUVmax and ADC were significantly associated (p < 0.05) with histologic grade (independently), nodal status, and vascular invasion. This finding suggests that SUVmax and ADC correlate with several of the pathologic prognostic factors and that both values may have the same potential for being predictive of the prognosis of breast cancer. In a study by Gu et al. [16], 33 patients with pathologically confirmed rectal adenocarcinoma underwent DWI and PET/CT within 1 week of each other, and significant negative correlations were found between ADCmin and SUVmax and between ADCmean and SUVmean. In a study by Mori et al. [17], 104 patients with pulmonary nodules or masses underwent PET/CT and DWI within a 2-week period, and the ADCmin and SUV contrast ratio values had a significant inverse correlation. The observed correlations between ADC and SUV (from FDG PET) suggest that these
parameters are not completely independent of each other, and thus there remains a question whether hybrid imaging modalities of the future must include both methods of imaging. However, the mixed and negative correlations observed in some of the studies cited suggest that the two parameters may yield related but possibly complementary information. Further studies of larger and better defined patient populations combined with improvements in quantitative accuracy will allow the medical community to better understand these two parameters and more definitively answer whether both methods of imaging are required. Our study differed from previous work in that PET, SUV, and ADC data were obtained at the same time with an integrated PET/MRI system, and thus biologic changes and misregistration artifacts were minimized. We are therefore able to confirm that the observed weak correlation between SUV and ADC in previous studies is not due to temporal or spatial bias but instead likely represents a true biologic relation. Moreover, showing that there was no difference in correlation between ADC and SUV from PET data obtained at PET/CT and same-day PET/MRI validates the results of previous studies, in which correlations were performed with PET/CT data and ADC data from separate MRI examinations. Furthermore, given that both biomarkers represent different cellular processes and that each is independently correlated with treatment response [12], it is possible that a ratio
4.0 3.5
4.0 3.5
3.0 2.5
3.0 2.5
2.0 1.5 1.0 0.5 0.0 0.0
ADCmin
ADCmin
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Rakheja et al.
5.0
10.0
15.0
20.0 SUVmax
1118
25.0
30.0
35.0
40.0
2.0 1.5 1.0 0.5 0.0 0.0
10.0
20.0 SUVmax
between the two could be used to jointly assess treatment response as a composite biomarker. We therefore calculated a ratio of SUVmax to ADCmin of the most metabolically active lesions and found this ratio was higher among patients with progressive disease than those with a partial treatment response. These preliminary results are of interest and suggest that combined PET and DWI measurements obtained with an integrated PET/MRI system may be more useful for assessment of treatment response than either parameter alone. This possibility needs to be further investigated as a more accurate early marker of response to treatment, a finding that is of great interest. Although PET/CT and MRI are sensitive modalities for the assessment of osseous metastasis, PET/MRI may be an excellent modality for this purpose, given the capability of simultaneous imaging of the metabolic activity of bone lesions in conjunction with the exceptional bone marrow resolution of MRI. Moreover, because of the limited methods of assessing response to treatment of osseous metastasis, the utility of DWI for the diagnosis of osseous metastasis and evaluation of treatment response is of interest in the imaging community. Although interval SUV values have been found to correlate with treatment response in patients with bone metastasis [27, 28], we hypothesize that ADC can be another biomarker of osseous metastasis. We therefore aimed to ascertain whether there is a correlation between the two quantitative markers because we
30.0
40.0
50.0
Fig. 2—Graphs show PET/MRI-derived (left) and PET/CT-derived (right) maximum standardized uptake value (SUVmax) compared with minimum apparent diffusion coefficient (ADCmin).
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PET/MRI of Neoplasms were unaware of previous studies of this correlation. Although SUVmax and ADCmin had no significant correlation, the SUV ratio and ADC had a significant inverse correlation (Table 2). The lack of correlation may have been related to current limitations in metabolic quantification of osseous values at PET/MRI. The Dixonbased PET/MRI attenuation correction methods used do not incorporate bone attenuation correction values. This issue originates from the lack of cortical bone signal intensity in conventional MRI sequences and results in suboptimal bone segmentation on attenuation maps derived from such sequences. Samarin et al. [29] studied methods of attenuation correction of bone at MRI and found that current methods result in underestimation of radiotracer uptake in osseous lesions. Further research is required to evaluate the clinical utility of ADC for evaluation of osseous metastasis. Conclusion Simultaneous PET/MRI is a promising technology for the detection of neoplastic disease. There is an inverse correlation between SUVmax and ADCmin, and between SUV ratio and ADCmin. Correlation coefficients between SUVmax and ADCmin from PET/MRI were similar to values obtained from same-day PET/CT. Given that both SUV and ADC are related to malignancy and that the correlation between the two biomarkers is relatively weak, SUV and ADC values may yield complementary information about tumoral metabolism, prognosis, and response to treatment. The ratio between the two biomarkers (SUVmax to ADCmin) was on average higher among patients with progressive disease than patients with a partial treatment response. A composite biomarker based on SUV and ADC measured accurately at simultaneous PET/MRI may have potential in improving characterization of cancer and monitoring response to therapy. References 1. Gambhir SS, Czernin J, Schwimmer J, Silverman DH, Coleman RE, Phelps ME. A tabulated summary of the FDG PET literature. J Nucl Med 2001; 42(5 suppl):1S–93S 2. Czernin J, Allen-Auerbach M, Schelbert HR. Improvements in cancer staging with PET/CT: literature-based evidence as of September 2006. J Nucl Med 2007; 48(suppl 1):78S–88S 3. Beyer T, Townsend DW, Brun T, et al. A combined PET/CT scanner for clinical oncology. J Nucl Med 2000; 41:1369–1379 4. Folpe AL, Lyles RH, Sprouse JT, et al. (F-18) flu-
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Nuclear Medicine and Molecular Imaging Original Research
Correlation Between Standardized Uptake Value and Apparent Diffusion Coefficient of Neoplastic Lesions Evaluated With Whole-Body Simultaneous Hybrid PET/MRI Rajan Rakheja1 Hersh Chandarana2 Linda DeMello1 Kimberly Jackson 3 Christian Geppert 3 David Faul 3 Christopher Glielmi 3 Kent P. Friedman1 Rakheja R, Chandarana H, DeMello L, et al.
Keywords: apparent diffusion coefficient, MRI, PET/CT, PET/MRI, standardized uptake value DOI:10.2214/AJR.13.11304 Received May 22, 2013; accepted without revision May 29, 2013. 1 Department of Radiology, Division of Nuclear Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016. Address correspondence to K. P. Friedman ([email protected]). 2 Department of Radiology, Abdominal Imaging Section, NYU Langone Medical Center, New York, NY. 3
MR R&D Collaborations, Siemens Healthcare, New York, NY.
AJR 2013; 201:1115–1119 0361–803X/13/2015–1115 © American Roentgen Ray Society
OBJECTIVE. The purpose of this study was to assess the correlation between standardized uptake value (SUV) and apparent diffusion coefficient (ADC) of neoplastic lesions in the use of a simultaneous PET/MRI hybrid system. SUBJECTS AND METHODS. Twenty-four patients with known primary malignancies underwent FDG PET/CT. They then underwent whole-body PET/MRI. Diffusion-weighted imaging was performed with free breathing and a single-shot spin-echo echo-planar imaging sequence with b values of 0, 350, and 750 s/mm2. Regions of interest were manually drawn along the contours of neoplastic lesions larger than 1 cm, which were clearly identified on PET and diffusion-weighted images. Maximum SUV (SUVmax) on PET/MRI and PET/CT images, mean SUV (SUVmean), minimum ADC (ADCmin), and mean ADC (ADCmean) were recorded on PET/ MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient. Pearson correlation coefficient was used to asses the following relations: SUVmax versus ADCmin on PET/MR and PET/CT images, SUVmean versus ADCmean, and ratio of SUVmax to mean liver SUV (SUV ratio) versus ADCmin. A subanalysis of patients with progressive disease versus partial treatment response was performed with the ratio of SUVmax to ADCmin for the most metabolically active lesion. RESULTS. Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. A significant inverse Pearson correlation coefficient was found between PET/MRI SUVmax and ADCmin (r = –0.21, p = 0.04), between SUVmean and ADCmean (r = –0.18, p = 0.07), and between SUV ratio and ADCmin (r = –0.27, p = 0.01). A similar inverse Pearson correlation coefficient was found between the PET/CT SUVmax and ADCmin. Twenty of 24 patients had previously undergone PET/CT; five patients had a partial treatment response, and six had progressive disease according to Response Evaluation Criteria in Solid Tumors 1.1. The ratio between SUVmax and ADCmin was higher among patients with progressive disease than those with a partial treatment response. CONCLUSION. Simultaneous PET/MRI is a promising technology for the detection of neoplastic disease. There are inverse correlations between SUVmax and ADCmin and between SUV ratio and ADCmin. Correlation coefficients between SUVmax and ADCmin from PET/ MRI were similar to values obtained with SUVmax from the same-day PET/CT. Given that both SUV and ADC are related to malignancy and that the correlation between the two biomarkers is relatively weak, SUV and ADC values may offer complementary information to aid in determination of prognosis and treatment response. The combined tumoral biomarker, ratio between SUVmax and ADCmin, may be useful for assessing progressive disease versus partial treatment response.
P
ET/CT is used routinely to diagnose and stage disease and evaluate response to therapy for many cancers [1–3]. Maximum standardized uptake value (SUVmax) from PET/CT is a measure of tumoral glucose metabolism and has been found to correlate with tumor grade [4] and other histopatho-
logic features, such as mitotic count and the presence of necrosis [5]. Diffusion-weighted MRI (DWI) is also increasingly used in the evaluation of neoplastic diseases. Restriction of diffusion can be quantified by the apparent diffusion coefficient (ADC), which has been found to correlate with cellularity [6, 7]. Like the SUV from PET/CT, ADC has
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Rakheja et al. been used clinically to differentiate benign from malignant tumors [8–10] and to assess tumor grade, delineate tumor extent, and predict survival [6, 11, 12]. Results of several studies have suggested an inverse correlation between SUVmax and ADC across varying malignancies [13–17]. Although these two biomarkers of tumoral cellularity have been suggested to correlate, to our knowledge all of the previously published research was performed on separate PET and MRI systems and on different imaging days, sometimes weeks apart. We aimed to assess the correlation between the SUV and ADC of neoplastic lesions using a simultaneous PET/MRI hybrid imaging system to more accurately assess the relation between these values by eliminating limitations such as patient motion between separate PET/CT and MRI examinations and by minimizing potential physiologic and treatment changes in the tumor due to the time interval between the PET and MRI examinations. Subjects and Methods Patient Studies This HIPAA-compliant study received local institutional review board approval. Patients undergoing clinically indicated PET/CT were recruited for a research PET/MRI examination from August 2012 through December 2012. All patients provided written informed consent for the PET/MRI examination. Twenty-four consecutively enrolled patients (six men, 18 women; average age, 65.4 years) with known metastatic cancer underwent FDG PET/CT immediately followed by a wholebody PET/MRI examination performed with residual FDG from the initial injection for PET/CT.
PET/CT All patients fasted for 4 hours before imaging. Insulin was withheld 6 hours before imaging. Blood glucose concentration was verified to be less than 200 mg/dL. All patients were adults who received a fixed 15-mCi IV dose of FDG. Patients were instructed to sit quietly in a dimly lit room for 45 minutes after the injection. Acquisitions were performed from the base of the skull to the mid thighs. Board-certified nuclear physicians read the PET/CT images and provided clinical interpretation; this examination was considered the reference standard for our study. PET/CT was performed with a Biograph mCT system (Siemens Healthcare). The CT parameters were as follows: 120 kVp, 95 mA, 5.0-mm slice width, 50-cm transaxial FOV, 512 × 512 transaxial image matrix. The PET parameters were as follows: 15 mCi FDG injected, 2 minutes per bed position, 814-mm transaxial FOV, 200 × 200 transaxial matrix, 3-mm gaussian postreconstruction image filter. PET images were reconstructed with
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CT for attenuation correction with the attenuationweighting ordered subsets expectation-maximization 3D algorithm at two iterations and 24 subsets. With these parameters the transaxial voxel size was 4.07 × 4.07 mm and the axial voxel size 2.03 mm.
of-stars trajectory with parameters as follows: TR/ TE 4.5/2; slice thickness, 2.5 mm; flip angle, 12°; number of axial slices, 80; bandwidth, 400 Hz/pixel; voxel size, 1.4 × 1.4 × 2.5 mm; quick fat-saturation mode. T2-weighted images were acquired in the coronal plane with the following parameters: STIR; TR/TE, 6250/56; inversion time, 220 ms; number of slices 36; nominal voxel size, 1.75 × 1.75 × 5 mm; bandwidth, 300 Hz/pixel; GRAPPA factor, 3. The PET acquisition time was 6 minutes and the MRI acquisition time approximately 10 minutes for each bed position. All patients had one bed position each for the pelvis, abdomen, thorax, and head and neck. Total imaging time for these bed positions ranged from 45 to 60 minutes. The PET data were reconstructed with an iterative 3D ordinary Poisson ordered subsets expectation-maximization algorithm at three iterations and 21 subsets and with a 4-mm gaussian postreconstruction image filter. The transaxial image matrix size was 172 × 172 mm with a transaxial FOV of 717.2 mm and an axial FOV of 258 mm. The transaxial voxel size for the PET/MRI PET images was 4.17 × 4.17 mm and the axial voxel size 2.03 mm.
PET/MRI Immediately after PET/CT, patients were imaged with the PET/MRI system (Biograph mMR, Siemens Healthcare). Because patients had to be transported to another building for PET/MRI, imaging was begun a total of 120–150 minutes after the initial injection of FDG. PET and MRI data were acquired simultaneously. For each bed position, an approximately 20-second breath-hold MRI attenuation correction map was acquired with a T1-weighted Dixon-based segmentation model. Thereafter, diagnostic MRI sequences (coronal T1-weighted turbo spin echo [TSE], T1-weighted gradient-echo imaging with radial stack-of-stars trajectory volumetric interpolated breath-hold examination [VIBE], T2weighted, and transverse DWI) were performed simultaneously with PET data acquisition during free breathing. T1-weighted TSE images were acquired with the following parameters: TR/TE, 500/9.5; slice thickness, 5 mm; refocusing flip angle, 140°; number of coronal slices, 35; bandwidth, 266 Hz/ pixel; voxel size, 1.6 × 1.2 × 5 mm; and parallel imaging generalized autocalibrating partial parallel acquisition (GRAPPA) factor, 2. DWI was performed with a single-shot spin-echo echo-planar imaging sequence with parameters as follows: TR/ TE, 5900/54; slice thickness, 6 mm; number of axial slices, 30; bandwidth, 1628 Hz/pixel; voxel size, 2.6 × 2.1 × 6 mm; parallel imaging GRAPPA factor, 2; fat-saturation mode; b values, 0, 350 and 750 s/ mm2. Radial VIBE images were acquired as a stack-
Image Analysis Nuclear physicians trained in PET/CT interpreted the PET/CT images independently. The PET/ MRI images were jointly read by a nuclear physician with experience in PET/CT and a radiologist with experience in MRI. Regions of interest (ROIs) were manually drawn along the contours of the neoplastic lesions that were clearly identified on PET images by the same experienced PET/CT nuclear physician (a single reader). The ROI was then copied to the DW images with fusion software (MIM 5.4, MIM Software), and ADC contours were
TABLE 1: Correlations Between Standardized Uptake Value (SUV) and Apparent Diffusion Coefficient (ADC) for All Lesions Comparison
R
p
−0.21
0.04
PET/MRI SUVmean vs ADCmean
−0.18
0.07
PET/MRI SUV ratio vs ADCmin
−0.27
0.01
PET/CT SUVmax vs ADCmin
−0.29
0.008
PET/CT SUV ratio vs ADCmin
−0.25
0.02
PET/MRI SUVmax vs ADCmin
Note— max = maximum, min = minimum. SUV ratio = ratio of SUVmax to mean liver SUV.
TABLE 2: Correlations of PET/MRI Standardized Uptake Value (SUV) and Apparent Diffusion Coefficient (ADC) of Osseous Metastatic Lesions (n = 17) Comparison SUVmax vs ADCmin
R
p
−0.12
0.24
SUVmean vs ADCmean
−0.05
0.14
SUV ratio vs ADCmin
−0.46
0.04
Note—max = maximum, min = minimum. SUV ratio = ratio of SUVmax to mean liver SUV.
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PET/MRI of Neoplasms slightly modified because of the subtle misregistration between ADC maps and PET data. The main contributing factors to misalignment in echo-planar imaging sequences are eddy current–induced image distortion and the nonlinearities of the gradient coils. Automated threshold-based ROIs could not be used because the software could not draw accurate ROIs on ADC maps, although our method is similar to that previously described [18]. Mean ADC (ADCmean) was defined as the average ADC value for all voxels in each lesion, and minimum ADC (ADCmin) as the lowest ADC value among all voxels in each lesion. SUVmax (on PET/ MRI and PET/CT images), mean SUV (SUVmean), ADCmin, and ADCmean were recorded on PET/MR images for each FDG-avid neoplastic soft-tissue lesion with a maximum of three lesions per patient (if there were more than three lesions, the most intensely FDG-avid lesions were chosen). Relations between SUVmax and ADCmin, SUVmean and ADCmean and between the ratio of SUVmax to mean liver SUV (SUV ratio) and ADCmin were assessed with the Pearson correlation coefficient. A ratio of SUVmax to ADCmin was calculated for a subset of patients with partial treatment response versus progressive disease according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 [19].
Results Sixty-nine neoplastic lesions (52 nonosseous lesions, 17 bone metastatic lesions) were evaluated. The mean SUVmax from PET/MRI was 7.0 ± 6.0; SUVmean, 5.6 ± 4.6; mean ADCmin, 1.10 ± 0.58; and mean ADCmean, 1.48 ± 0.72. There was weak to moderate correlation between SUV and ADC for nonosseous soft-tissue lesions (Table 1). There was no correlation between SUV and ADC for osseous lesions. However, there was a significant negative correlation between lesion SUV ratio and ADCmin (Table 2). There was a strong correlation between SUVmax values from PET/CT and PET/MRI (r = 0.725, p < 0.001). There was no difference in correlation between ADC and SUV from PET data obtained from PET/CT and PET/MRI. Twenty of 24 patients had previously undergone PET/CT. Five patients had a partial treatment response and six had progressive disease according to RECIST 1.1 [19]. The others had stable disease. All patients underwent interval chemotherapy (we include monoclonal antibody treatments in chemotherapy). The ratio of SUVmax to ADCmin based on PET/MRI of the most metabolical-
TABLE 3: PET/MRI Ratios Between Standardized Uptake Value (SUV) and Apparent Diffusion Coefficient (ADC) for the Most Active Tumors in Patients With Partial Treatment Response Lesion Location
Primary Malignancy MRI SUVmax MRI SUVmean
ADCmin
ADCmean
SUVmax / ADCmin
1.32
7.06
Left lower lobe nodule
Breast
8.80
7.20
1.02
Paraaortic node
Breast
15.40
10.70
0.97
1.11
11.03
Lung
5.20
4.30
1.41
2.62
3.04
Left lower lobe nodule Right upper lobe nodule
Lung
1.70
1.40
1.40
1.80
1
Right apical mass
Lung
6.30
3.90
0.94
1.30
4.15
7.48
5.50
1.15
1.63
5.26
Mean value for all locations
Note—Partial treatment response according to Response Evaluation Criteria in Solid Tumors version 1.1. max = maximum, min = minimum.
TABLE 4: PET/MRI Ratios Between Maximum Standardized Uptake Value (SUV) and Minimum Apparent Diffusion Coefficient (ADC) for the Most Active Tumors in Patients With Progressive Disease Lesion Location
Primary Malignancy MRI SUVmax MRI SUVmean ADCmin
ADCmean
SUVmax / ADCmin 10.18
Peritoneum
Ovarian
10.00
5.70
0.56
0.97
Right hilar node
Ovarian
8.10
7.10
1.19
1.31
5.97
Subcarina
Lymphoma
14.60
11.80
0.73
1.03
16.16
Pancreas
Lung
9.70
8.10
1.08
1.39
7.50
Right upper lobe mass
Lung
12.90
10.40
0.86
1.62
12.09
Left upper lobe mass
Lung
14.40
11.90
0.47
0.94
25.32
11.62
9.17
0.82
1.21
12.87
Mean value for all locations
Note—Progressive disease according to Response Evaluation Criteria in Solid Tumors version 1.1. max = maximum, min = minimum.
ly active lesion in each patient was calculated. The average lesion size in this subanalysis was 2.1 cm. The ratio of SUVmax to ADCmin was higher for patients with progressive disease than for those with a partial response (Tables 3 and 4 and Figs. 1 and 2). Discussion PET entails the use of FDG to depict differences in glucose metabolism between physiologic and malignant cells to diagnose neoplastic processes. FDG, a glucose analogue, is trapped within cells, which are unable to further metabolize the radiotracer after phosphorylation. The SUV from PET/CT is commonly used to quantify tumor glucose metabolism and is an indirect biomarker of tumor cellularity [20, 21]. SUVmax is used in most clinical studies because it is independent of tumor size and shape and thus highly reproducible. SUVmean, however, is based on the estimation of tumor boundaries (either with a threshold technique or by subjective visual analysis) and is thus more variable [13]. DWI provides information on the brownian motion of water molecules in tissues. ADC is a calculated parameter derived from DWI. ADC values depend on the presence of barriers to diffusion within the water microenvironment, and the physical boundaries of cell membranes restrict water diffusion in both normal and neoplastic tissues [13]. ADC has been found to inversely correlate with tumor cellularity [6, 7, 22]. ADC has also been applied clinically to differentiate benign from malignant tumors [8–10, 23], to differentiate tumor types, to assess tumor grade, to delineate tumor extent, and to predict survival [6, 11, 12]. Studies have shown that DWI is a valuable imaging modality for detecting metastasis and cancer relapse; it has also been used to assess treatment response in various malignancies [24–26]. PET/CT and DWI share applications in the field of clinical oncology. Whereas both SUV and ADC correlate with cellularity, SUV also correlates with several other pathologic markers, such as mitotic count, presence or absence of necrosis [5], MIB proliferation marker expression, and p53 tumor suppressor gene function [4]. It remains a question for research to further define how these two parameters may be combined to improve the diagnosis and management of cancer. The published results of preliminary work investigating a link between SUV and ADC have been mixed. In a study by Ho et al. [13], patients with documented primary cervical cancer underwent abdominopelvic DWI and
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Fig. 1—65-year-old woman with metastatic ovarian cancer and FDG-avid left upper abdominal peritoneal implant. A and B, PET image (A) and apparent diffusion coefficient map (B) show maximum standardized uptake value in region of interest (arrow) is 10.1 and minimum apparent diffusion coefficient is 0.56.
A
B
FDG PET/CT within 2 weeks of each other. Although SUVmax and ADCmin were not correlated, relative ADCmin, defined as the ratio between ADCmin and ADCmean, inversely correlated with relative SUVmax. In a study by Wu et al. [14], 15 patients with histologically proven diffuse large B-cell lymphoma underwent pretherapy FDG PET/CT and DWI within 2 days of each other. The analysis showed no correlation between the ADCmean and the SUVmax or SUVmean of the lesions. In a study by Nakajo et al. [15], 44 patients with breast cancer underwent preoperative PET/CT and DWI within an average of 17 days between examinations, and both SUVmax and ADC were significantly associated (p < 0.05) with histologic grade (independently), nodal status, and vascular invasion. This finding suggests that SUVmax and ADC correlate with several of the pathologic prognostic factors and that both values may have the same potential for being predictive of the prognosis of breast cancer. In a study by Gu et al. [16], 33 patients with pathologically confirmed rectal adenocarcinoma underwent DWI and PET/CT within 1 week of each other, and significant negative correlations were found between ADCmin and SUVmax and between ADCmean and SUVmean. In a study by Mori et al. [17], 104 patients with pulmonary nodules or masses underwent PET/CT and DWI within a 2-week period, and the ADCmin and SUV contrast ratio values had a significant inverse correlation. The observed correlations between ADC and SUV (from FDG PET) suggest that these
parameters are not completely independent of each other, and thus there remains a question whether hybrid imaging modalities of the future must include both methods of imaging. However, the mixed and negative correlations observed in some of the studies cited suggest that the two parameters may yield related but possibly complementary information. Further studies of larger and better defined patient populations combined with improvements in quantitative accuracy will allow the medical community to better understand these two parameters and more definitively answer whether both methods of imaging are required. Our study differed from previous work in that PET, SUV, and ADC data were obtained at the same time with an integrated PET/MRI system, and thus biologic changes and misregistration artifacts were minimized. We are therefore able to confirm that the observed weak correlation between SUV and ADC in previous studies is not due to temporal or spatial bias but instead likely represents a true biologic relation. Moreover, showing that there was no difference in correlation between ADC and SUV from PET data obtained at PET/CT and same-day PET/MRI validates the results of previous studies, in which correlations were performed with PET/CT data and ADC data from separate MRI examinations. Furthermore, given that both biomarkers represent different cellular processes and that each is independently correlated with treatment response [12], it is possible that a ratio
4.0 3.5
4.0 3.5
3.0 2.5
3.0 2.5
2.0 1.5 1.0 0.5 0.0 0.0
ADCmin
ADCmin
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Rakheja et al.
5.0
10.0
15.0
20.0 SUVmax
1118
25.0
30.0
35.0
40.0
2.0 1.5 1.0 0.5 0.0 0.0
10.0
20.0 SUVmax
between the two could be used to jointly assess treatment response as a composite biomarker. We therefore calculated a ratio of SUVmax to ADCmin of the most metabolically active lesions and found this ratio was higher among patients with progressive disease than those with a partial treatment response. These preliminary results are of interest and suggest that combined PET and DWI measurements obtained with an integrated PET/MRI system may be more useful for assessment of treatment response than either parameter alone. This possibility needs to be further investigated as a more accurate early marker of response to treatment, a finding that is of great interest. Although PET/CT and MRI are sensitive modalities for the assessment of osseous metastasis, PET/MRI may be an excellent modality for this purpose, given the capability of simultaneous imaging of the metabolic activity of bone lesions in conjunction with the exceptional bone marrow resolution of MRI. Moreover, because of the limited methods of assessing response to treatment of osseous metastasis, the utility of DWI for the diagnosis of osseous metastasis and evaluation of treatment response is of interest in the imaging community. Although interval SUV values have been found to correlate with treatment response in patients with bone metastasis [27, 28], we hypothesize that ADC can be another biomarker of osseous metastasis. We therefore aimed to ascertain whether there is a correlation between the two quantitative markers because we
30.0
40.0
50.0
Fig. 2—Graphs show PET/MRI-derived (left) and PET/CT-derived (right) maximum standardized uptake value (SUVmax) compared with minimum apparent diffusion coefficient (ADCmin).
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PET/MRI of Neoplasms were unaware of previous studies of this correlation. Although SUVmax and ADCmin had no significant correlation, the SUV ratio and ADC had a significant inverse correlation (Table 2). The lack of correlation may have been related to current limitations in metabolic quantification of osseous values at PET/MRI. The Dixonbased PET/MRI attenuation correction methods used do not incorporate bone attenuation correction values. This issue originates from the lack of cortical bone signal intensity in conventional MRI sequences and results in suboptimal bone segmentation on attenuation maps derived from such sequences. Samarin et al. [29] studied methods of attenuation correction of bone at MRI and found that current methods result in underestimation of radiotracer uptake in osseous lesions. Further research is required to evaluate the clinical utility of ADC for evaluation of osseous metastasis. Conclusion Simultaneous PET/MRI is a promising technology for the detection of neoplastic disease. There is an inverse correlation between SUVmax and ADCmin, and between SUV ratio and ADCmin. Correlation coefficients between SUVmax and ADCmin from PET/MRI were similar to values obtained from same-day PET/CT. Given that both SUV and ADC are related to malignancy and that the correlation between the two biomarkers is relatively weak, SUV and ADC values may yield complementary information about tumoral metabolism, prognosis, and response to treatment. The ratio between the two biomarkers (SUVmax to ADCmin) was on average higher among patients with progressive disease than patients with a partial treatment response. A composite biomarker based on SUV and ADC measured accurately at simultaneous PET/MRI may have potential in improving characterization of cancer and monitoring response to therapy. References 1. Gambhir SS, Czernin J, Schwimmer J, Silverman DH, Coleman RE, Phelps ME. A tabulated summary of the FDG PET literature. J Nucl Med 2001; 42(5 suppl):1S–93S 2. Czernin J, Allen-Auerbach M, Schelbert HR. Improvements in cancer staging with PET/CT: literature-based evidence as of September 2006. J Nucl Med 2007; 48(suppl 1):78S–88S 3. Beyer T, Townsend DW, Brun T, et al. A combined PET/CT scanner for clinical oncology. J Nucl Med 2000; 41:1369–1379 4. Folpe AL, Lyles RH, Sprouse JT, et al. (F-18) flu-
orodeoxyglucose positron emission tomography as a predictor of pathologic grade and other prognostic variables in bone and soft tissue sarcoma. Clin Cancer Res 2000; 6:1279–1287 5. Rakheja R, Makis W, Skamene S, et al. Correlating metabolic activity on 18F-FDG PET/CT with histopathologic characteristics of osseous and soft-tissue sarcomas: a retrospective review of 136 patients. AJR 2012; 198:1409–1416 6. Hayashida Y, Hirai T, Morishita S, et al. Diffusion-weighted imaging of metastatic brain tumors: comparison with histologic type and tumor cellularity. AJNR 2006; 27:1419–1425 7. Guo AC, Cummings TJ, Dash RC, et al. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224:177–183 8. Rubesova E, Grell AS, De Maertelaer V, et al. Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging 2006; 24:319–324 9. Pickles MD, Gibbs P, Sreenivas M, et al. Diffusion-weighted imaging of normal and malignant prostate tissue at 3.0T. J Magn Reson Imaging 2006; 23:130–134 10. Naganawa S, Sato C, Kumada H, et al. Apparent diffusion coefficient in cervical cancer of the uterus: comparison with the normal uterine cervix. Eur Radiol 2005; 15:71–78 11. Di Costanzo A, Scarabino T, Trojsi F, et al. Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy. Neuroradiology 2006; 48:622–631 12. Hamstra DA, Chenevert TL, Moffat BA, et al. Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overall survival in high-grade glioma. Proc Natl Acad Sci USA 2005; 102:16759–16764 13. Ho KC, Lin G, Wang JJ, Lai CH, Chang CJ, Yen TC. Correlation of apparent diffusion coefficients measured by 3T diffusion-weighted MRI and SUV from FDG PET/CT in primary cervical cancer. Eur J Nucl Med Mol Imaging 2009; 36:200–208 14. Wu X, Korkola P, Pertovaara H, et al. No correlation between glucose metabolism and apparent diffusion coefficient in diffuse large B-cell lymphoma: a PET/CT and DW-MRI study. Eur J Radiol 2011; 79:e117–e121 15. Nakajo M, Kajiya Y, Kaneko T, et al. FDG PET/ CT and diffusion-weighted imaging for breast cancer: prognostic value of maximum standardized uptake values and apparent diffusion coefficient values of the primary lesion. Eur J Nucl Med Mol Imaging 2010; 37:2011–2020 16. Gu J, Khong P, Wang S, et al. Quantitative assessment of diffusion-weighted MR imaging in patients with primary rectal cancer: correlation with FDG-
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