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. 2013 Oct 8;20(2):105–109. doi: 10.5152/dir.2013.13275

Correlation of minimum apparent diffusion coefficient with maximum standardized uptake on fluorodeoxyglucose PET-CT in patients with rectal adenocarcinoma

Hale Çolakoğlu Er 1, Ayşe Erden 1, N Özlem Küçük 1, Ethem Geçim 1
PMCID: PMC4463301  PMID: 24100063

Abstract

PURPOSE

The aim of this study was to retrospectively assess the correlation between minimum apparent diffusion coefficient (ADCmin) values obtained from diffusion-weighted magnetic resonance imaging (MRI) and maximum standardized uptake values (SUVmax) obtained from positron emission tomography-computed tomography (PET-CT) in rectal cancer.

MATERIALS AND METHODS

Forty-one patients with pathologically confirmed rectal adenocarcinoma were included in this study. For preoperative staging, PET-CT and pelvic MRI with diffusion-weighted imaging were performed within one week (mean time interval, 3±1 day). For ADC measurements, the region of interest (ROI) was manually drawn along the border of each hyperintense tumor on b=1000 s/mm2 images. After repeating this procedure on each consecutive tumor-containing slice to cover the entire tumoral area, ROIs were copied to ADC maps. ADCmin was determined as the lowest ADC value among all ROIs in each tumor. For SUVmax measurements, whole-body images were assessed visually on transaxial, sagittal, and coronal images. ROIs were determined from the lesions observed on each slice, and SUVmax values were calculated automatically. The mean values of ADCmin and SUVmax were compared using Spearman’s test.

RESULTS

The mean ADCmin was 0.62±0.19×10−3 mm2/s (range, 0.368–1.227×10−3 mm2/s), the mean SUVmax was 20.07±9.3 (range, 4.3–49.5). A significant negative correlation was found between ADCmin and SUVmax (r=−0.347; P = 0.026).

CONCLUSION

There was a significant negative correlation between the ADCmin and SUVmax values in rectal adenocarcinomas.

Diffusion-weighted imaging (DWI) is a widely used technique for disease evaluation in oncology (1, 2). In rectal cancer, the applications of DWI include tumor detection, tumor characterization, distinguishing tumor tissue from nontumor tissue, and monitoring and predicting treatment response (3–8). For local staging of rectal cancer, adding DWI to conventional magnetic resonance imaging (MRI) yields better identification of tumor borders and locoregional lymph nodes than conventional MRI alone (9, 10).

The apparent diffusion coefficient (ADC) map obtained from DWI shows the freedom of water diffusion, and values calculated on the map are useful parameters in tissue characterization. By performing diffusion-weighted (DW) MRI with at least two diffusion weightings, or b values, the differential signal attenuation at different b values can be used to calculate the ADC (2). Regardless of the tumor type and location, the ADC values reflect tumor morphology, including the cellular density, integrity of cell membrane, and nuclear-to-cytoplasm ratio (11, 12).

Positron emission tomography/computed tomography (PET-CT) has become a crucial method in cancer imaging, both for diagnosis and staging, as well as for offering prognostic information based on tumor response. In PET-CT, the standardized uptake value (SUV) is a measure of fluorodeoxyglucose (FDG) uptake, which has been shown to be helpful in establishing the metabolic activity level of a tumor (13–15).

Both ADC and SUV have been used as important imaging parameters to supplement visual interpretation. To our knowledge, few studies have evaluated the relationship between ADC and SUV in cancer patients (16–18). The aim of the present study was to retrospectively assess the correlation between the minimum ADC (ADCmin) on DWI and maximum SUV (SUVmax) values from FDG PET-CT in rectal cancer.

Materials and methods

Patients

Between March 2010 and November 2012, 53 consecutive patients underwent pelvic MRI using a 3.0 Tesla system for baseline local staging of rectal tumors. Inclusion criteria for the present study consisted of histopathologically (biopsy) proven rectal adenocarcinoma and the presence of correlative PET-CT. Exclusion criteria were histologic subtypes other than adenocarcinoma (including mucinous adenocarcinoma) according to the current World Health Organization classification of colorectal cancer (19) and insufficient magnetic resonance (MR) image quality (e.g., owing to metal implants or movement artifacts). Twelve patients were excluded for the following reasons: severe motion artifacts on DW images (n=1), histopathologic diagnosis of mucinous adenocarcinoma (n=2), and absence of correlative PET-CT (n=9). Forty-one consecutive patients (24 males, 17 females; age range, 41–79 years [mean age, 59 years]) who met the inclusion criteria were enrolled in the current study. All patients provided written informed consent. Our Institutional Ethics Committee approved this retrospective study.

MR techniques

All patients were fasted from food for periods of 5–6 hours before examination to prevent stimulation of bowel peristaltism. No intravenous antiperistaltic agent was administered. Rectal cleansing was not performed. Air insufflation or a water enema was not carried out for rectal distension.

The patients underwent MRI using 3.0 Tesla whole-body system (MAGNETOM Verio, Siemens, Erlangen, Germany) and a phased-array body coil. The imager operates with a maximum gradient strength of 45 mT/m and a slew rate of 200 mT/m/s in all three directions. Conventional MR images and DW images were acquired during the same procedure. The MR imaging examination consisted of standard sagittal and axial T2-weighted turbo spin-echo images, high-resolution oblique axial and oblique coronal T2-weighted images, axial DW images, and contrast-enhanced fat suppressed T1-weighted axial images. All pulse sequence parameters other than those of DWI used in this study are listed in detail in Table. DW images with three different b values (50, 400, and 1000 s/mm2) were obtained in the axial plane using a single-shot multi-slice echoplanar imaging (EPI) sequence with spectral adiabatic inversion recovery fat suppression and the following parameters: repetition time/echo time, 6800/75 ms; EPI factor, 78; field of view, 360×271 mm; matrix size, 130×104; slice thickness, 5 mm; distance factor, 20%; averages, 4; reduction factor, 2; and receiver bandwidth, 2402 Hz/Px. The acquisition time for the DWI was 4 min and 25 s.

Table.

Pulse sequence parameters

Parameter Sagittal T2-weighted TSE Axial T2-weighted TSE Oblique axial T2-weighted TSE (High resolution) Oblique coronal T2-weighted TSE (High resolution) T1-weighted fat suppressed contrast-enhanced
Matrix size 384×307 320×240 320×240 320×240 320×240
Slice thickness (mm) 3.5 5.0 3.5 3.5 3.5
Distance factor 15% 20% 14% 14% 14%
Repetititon time (ms) 4500 5450 5460 5180 495
Echo time (ms) 104 93 85 85 12
Echo trains per slice 13 8 12 15 39
Flip angle (°) 120 150 149 130 140
Reduction factor 2 2 2 2 2
Averages 2 3 3 3 2
FoV (mm) 220×220 220×220 200×200 200×200 200×200
Orientation Sagittal Axial Oblique axial Oblique coronal Oblique axial
Bandwidth (Hz/Px) 250 260 260 260 260
Acquisiton time (min and s) 4 min, 5 s 2 min, 18 s 3 min, 24 s 4 min 3 min, 17 s
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FoV, field of view; TSE, turbo spin echo.

The PET-CT scanner used in this study was a Discovery ST PET/CT scanner (General Electric, Milwaukee, Wisconsin, USA). The CT device had eight rows of detectors. The CT data were used for attenuation correction. To maintain a normal “fasting glucose level”, the patients were instructed not to eat food for six hours before the PET-CT imaging. Patients with diabetes mellitus were required to fast for four hours before the examination and allowed to continue to take their antidiabetic medication or to administer insulin. In patients whose preparation was adequate, the blood glucose level was checked at the imaging center to ensure that the patients’ glucose level was not too low or high. If the level was still greater than 150 mg/dL, crystallized insulin was administered to the patient intramuscularly to lower the blood glucose level under 150 mg/dL. Next, 1000 cc of low-density oral contrast agent were administered to the patients to aid in the evaluation of gastrointestinal FDG uptake and facilitate confident exclusion or diagnosis of luminal and mural disease. In all patients, 0.15 mCi/kg of the intravenous tracer (radiopharmaceutic) fluorine-18 FDG (18F-FDG) was administered. After the injection of 18F-FDG, the patients were requested to rest in a semirecumbent arm chair as calmly as they can for 50–60 min. At the end of the resting period, the patients were asked to empty their bladder because intense bladder activity can impair the interpretation of lesions in the pelvis. All the patients were scanned from the vertex to the midfemur. After routine imaging, additional views of the suspicious uptake area were obtained whenever necessary. All participants underwent pelvic DWI and FDG PET-CT within one week (mean time interval, 3±1 days).

Image interpretation

The ADC maps were automatically generated using a monoexponential decay model, including all three b-values at Siemens Software Version syngo MR B17. Regions of interest (ROIs) covering the tumor were drawn manually on DW images with b=1000 s/mm2. On each slice, the high signal intensity of tumor boundaries was traced, and ROIs were copied to the corresponding ADC map to measure ADC values. ADCmin was the lowest value of the ADC obtained from the tumor-containing slices.

For SUVmax measurements, whole-body images from FDG PET-CT in axial, sagittal, and coronal planes were evaluated visually. The ROI for the SUV measurements was drawn manually around each tumor on all consecutive slices that contained the lesion, and SUVmax values were calculated automatically.

Statistical analysis

Because the data shown were not in a normal distribution, Spearman’s correlation (nonparametric test) was employed to analyze the relationship between the ADCmin and SUVmax values. Statistical analysis was performed using using a commercially available software (Statistical Package for Social Sciences, version 15.0, SPSS Inc., Chicago, Illinois, USA). P values less than 0.05 were deemed to indicate a statistically significant difference.

Results

Tumor thickness ranged between 1.3 and 2.5 cm (mean size, 1.7 cm). The mean ADCmin of tumors was 0.62±0.19×10−3 mm2/s (range, 0.368–1.227×10−3 mm2/s). The mean SUVmax of tumors was 20.07±9.3 (range, 4.3–49.5). There was a negative correlation between ADCmin and SUVmax (r=−0.347, P = 0.026). The graph shows the negative correlation between values of ADCmin and SUVmax (Fig. 1). An example of our cases is presented in Fig. 2.

Figure 1.

Figure 1.

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Negative correlation between ADCmin and SUVmax. The ADC is expressed in units of 10−3 mm2/s.

Figure 2. a–e.

Figure 2. a–e.

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A 50-year-old male with rectal adenocarcinoma. High-resolution T2-weighted turbo spin echo oblique axial image (a) shows eccentric bowel-wall thickening in the distal rectum. Manual tracing of free-hand ROI for calculation of the sectional area of the tumor on DW image (b) with b=1000 s/mm2, and ROIs are copied from the DW images with b=1000 s/mm2 to the ADC map (c) to calculate minimum tumor ADC values. FDG PET-CT image of the same patient shows increased uptake of FDG at axial PET (d). A fusion image (e) at the same level as in a–c is seen.

Discussion

Advancing technology allows the acquisition of physiological and metabolic information that complements the anatomic information provided by conventional imaging methods. Quantification of the level of signal attenuation and uptake values is used mainly for making comparisons between tissues. In the present study, DWI of rectal cancer allows quantitative evaluation of the ADC. We found a negative correlation between ADCmin and SUVmax values. In our study, we included only the minimum ADC value measurements. The present definition of minimum ADC is the lowest value selected from multiple ROIs drawn manually along the border of the lesion on each consecutive tumor-containing slices, including the whole tumor volume, not the lowest value corresponding to a pixel in one ROI surrounding the mass. The regions with minimum ADCs have been suggested to reflect the highest tumor cell density or the most proliferative portion of the tumor (20).

Malignant lesions are characterized by high signal intensity on DW images with high b value and exhibit lower ADC values. Diffusion of water within malignant tissue from the extracellular to the intracellular compartment is relatively restricted. Several investigators have found an inverse correlation between the ADC and tumor cellularity (21). Recently, it has been reported that lower ADC values were associated with a more aggressive tumor profile in rectal cancer (22). Although MRI provides high-resolution anatomic information, PET adds information concerning the metabolic activity of lesions. Tumoral uptake is estimated by SUV, reflecting metabolically active tissue volume. Glucose is a critical nutrient for proliferating cells. Thus, it may not be surprising that tumor cells, to meet the increased requirements of proliferation, often display fundamental changes in pathways of energy metabolism and glucose uptake (23).

Studies of the correlation between ADCmin and SUVmax are few. Cafagna et al. (16) measured SUV and ADC values of lesions to determine the possible correlation between PET-CT and DWI in 38 patients with malignancy. However, they did not find a significant correlation between these two parameters. This result may be the consequence of including different types of malignant processes in the study or may be due to the method used to calculate ADC values. Ho et al. (17) found no significant correlation between ADCmin and SUVmax in patients with primary cervical tumor. In that study, however, a significantly inverse correlation between the relative ADCmin (defined as ADCmin/ADC mean ratio) and relative SUVmax was observed in patients with adenocarcinoma/adenosquamous carcinoma (r=−0.685; P = 0.0012). The authors suggest that DWI and FDG PET-CT might play a complementary role for the clinical assessment of this cancer type (17). Gu et al. (18) assessed correlations between parameters on DWI and FDG PET-CT in rectal cancer. Significant negative correlations were found between ADCmin and SUVmax (r=−0.450, P = 0.009), and between ADC mean and SUV mean (r=−0.402, P = 0.020). A significant positive correlation was found between the total diffusivity index (TDI) obtained from DWI and total lesion glycolysis (TLG) obtained from FDG PET-CT (r=0.634; P < 0.001). The authors concluded that the significant negative correlation between ADC and SUV suggests an association between tumor cellularity and metabolic activity in primary rectal adenocarcinoma (18).

Neoadjuvant chemoradiotherapy has become a standard treatment for locally advanced rectal cancer. However, this application is not beneficial for all patients. The patients who do not respond to preoperative chemoradiotherapy are exposed to unnecessary toxicities of the neoadjuvant therapy, and resection of their primary tumor is delayed (24). Ippolito et al. (25) evaluated the correlation between the changes in SUVmax and ADC before and after neoadjuvant therapy in patients with locally advanced rectal cancer. The best predicted cutoff values for response are an SUVmax of 4.4 and an ADC of 1.28×10−3 mm2/s with sensitivity, specificity, accuracy, negative predictive value, and positive predictive values of 77.3%, 88.9%, 80.7%, 61.5%, and 94.4%, respectively. They concluded that the absolute values of SUVmax and ADC of rectal lesions after chemoradiotherapy were the best parameters to define the response to treatment (25).

Our study had some limitations. We assessed only minimum ADC values and maximum SUV in our study. Combining multiple parameters such as the mean ADC, tumor volume, total diffusivity index, mean SUV, and total lesion glycolysis as imaging biomarkers might provide more comprehensive information regarding the tumoral process.

Several factors affect the values measured as ADC and SUV (26, 27). ADC measurements are subject to institutional differences and intraobserver variability. The ROI is an important consideration because small variations in ROI size or placement may result in non-negligible variations in ADC that may substantially influence the results. Size and location influence tumor ADC measurements in rectal cancer (28). It has been shown that ADC measurements of the “whole tumor volume” provide the most reproducible and dependable results for clinical applications (28). In our study, we used this method for consecutive tumor-containing slices. The histologic subtype of rectal carcinoma may also affect ADC values. Mucinous tumors are known to have a low cellular density and high extracellular mucin component. It has been established that mucinous adenocarcinoma of the rectum shows higher ADC values than well-differentiated adenocarcinoma due to its low cellularity (29). There are also diverse factors influencing SUV determination, such as ROI shape, partial-volume effects, reconstruction method and parameters for the scanner type, tissue state factors (type and extent of disease, vascularity, organ usage, urine management policy), time of SUV evaluation, body size, and competing transport effects (serum glucose and protein levels) (27). Understanding these factors and knowledge of potential interpretive pitfalls will help to avoid mistakes.

In conclusion, ADCmin and SUVmax are inversely correlated parameters in patients with rectal cancer. They reflect the most cellular and metabolically active portions of the tumoral lesions and provide physiopathological information as quantifiable data.

Footnotes

Conflict of interest disclosure

The authors declared no conflicts of interest.

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