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Predicting biochemical recurrence in patients with high-risk prostate cancer using the apparent diffusion coefficient of magnetic resonance imaging

Purpose We aimed to investigate whether the apparent diffusion coefficient (ADC) value in diffusion-weighted magnetic resonance imaging predicts the prognoses of patients with high-risk prostate cancer. Materials and Methods A total of 157 patients with high-risk prostate cancer (based on D'Amico's criteria) were included in the analysis. Patients underwent preoperative 3.0 Tesla magnetic resonance imaging within 2 months before radical prostatectomy. Those who received neoadjuvant hormone therapy (33 persons) or radiation therapy (18 persons) were excluded. The ADC of the tumor calculated from 2 b-values (0 and 1,000 s/mm2) was measured. Areas under receiver operating characteristics curves were calculated to maximize the accuracy of the ADC value. Based on the obtained cutoff value, the patients were stratified into 2 groups: Group A consisted of patients with ADC values <746×10−6 mm2/s and group B comprised those with ADC values ≥746×10−6 mm2/s. Results Group A showed higher rate of lymph positive and biochemical recurrence (BCR) rates than group B. Kaplan-Meier analysis showed that the BCR-free survival rate of group A was much lower than that of group B (p<0.001). On Cox proportional regression analyses, ADC group A (hazard ratio [HR], 3.238, p=0.002) and pathologic lymph node positive (HR, 2.242; p=0.009) were independent predictors of BCR. Conclusions In patients with high-risk prostate cancer, ADC value is significantly associated with BCR-free survival. Therefore, the ADC value is a useful tool for predicting the prognoses of these high-risk patients.


INTRODUCTION
The incidence of prostate cancer is increasing in Korea as well as globally. In 2013, the incidence rate of this disease in Korea was 37.6 per 100,000 persons, which represented an almost 5-fold increase over the rate reported in 2000 (7.2 per ADC in patients with high-risk prostate cancer diffusion-weighted MRI (DW-MRI), which is based on the mobility of hydrogen protons in water, has gained attention owing to its ability to differentiate aggressive tumor types with higher Gleason scores from indolent lesions [4][5][6][7][8][9][10]. The apparent diffusion coefficient (ADC) is a measure of the average rate of a hydrogen proton's movement (mm/s 2 ). Therefore, the ADC decreases as tissue cells become denser. A tumor typically demonstrates denser cell distribution and sparser extracellular space; therefore, the ADC value is lower in prostate cancer tissue [3].
It has been reported that patients who meet the same high-risk prostate cancer criteria still exhibit a broad range of outcomes. Meanwhile, several recent studies have shown an inverse association between ADC values and Gleason scores, as well as other adverse prostate cancer pathologic features [5,[9][10][11][12][13]. However, to the best of our knowledge, no study has examined the relationship between ADC values and the prognosis of high-risk prostate cancer in particular. In this study, we investigated the relationship between ADC values and the prognoses of patients who met the D'Amico criteria for high-risk prostate tumors.

Patients
Between January 2007 and December 2013, 1,844 prostate cancer patients underwent radical prostatectomy at our center. From among these patients, we included 549 who preoperatively underwent 3-T DW-MRI. After excluding patients who received neoadjuvant hormone therapy (33 persons) or radiation therapy (18 persons), we ultimately selected 157 patients who were determined to be at high risk according to D'Amico's criteria for prostate cancer (i.e., those with a biopsy Gleason score≥8, preoperative prostatespecific antigen [PSA] level≥20 ng/mL, or clinical stage≥T2c). The study protocol was approved by the Seoul National University Hospital Institutional Review Board (approval number: 1511-034-718); the requirement for informed consent was waived owing to the retrospective nature of the study.

Acquisition of ADC values
One uroradiologist examined the patients' ADC maps.  First, the darkest areas of the pertinent histopathologic lesions were identified ( Fig. 1) [15]. Next, lesions of similar or larger sizes were evaluated to obtain the mean ADC values. The diffusion-encoding gradients were applied as a bipolar pair at b-values of 0 and 1,000 s/mm 2 ; the ADC maps were automatically generated on a pixel-by-pixel basis [16][17][18][19].

Statistical analysis
The area under the receiver operating characteristics curve was used to determine the optimal ADC cutoff. We used the t-test, chi-square test, and Cox progression model to describe the relationships between the variables. The relation between the ADC mean and the biochemical recurrence (BCR)free survival rate was assessed using Kaplan-Meier analysis. Univariate and multivariate Cox proportional regression analyses were performed for the covariates of age, PSA, ADC value, pathologic Gleason score, and pathologic stage. A p-value of <0.05 was considered statistically significant; the IBM SPSS Statistics ver. 22.0 (IBM Co., Armonk, NY, USA) was used to analyze the data.

Patient demographics
A total of 157 patients underwent analysis for age, body mass index (BMI), prostate volume, preoperative PSA level, biopsy Gleason score, pathologic Gleason score, clinical stage, pathologic stage, positive surgical margin, BCR, and postoperative follow-up period ( Table 1). The mean patient age was 66.9 years, and the mean BMI was 24.2 kg/m 2 . The median prostate volume was 43. 1 mL, while the mean PSA level was 24.4 ng/mL. The incidence of clinical stage ≤T2 was 79.6% while that of pathologic stage ≤T2 was 42.7%. A biopsy Gleason score≥8 was recorded in 72.6% of the patients, and a pathologic Gleason score≥8 was found in 30.6%. The mean postoperative follow-up period was 33.8 months. The total BCR rate was 43.9%.

Determination of the ADC cutoff and grouping of patients
The patients showed a normal distribution curve, and the average ADC value was 677.3×10 −6 mm 2 /s (standard deviation, 184.0×10 −6 mm 2 /s). The area under the receiver

Relationship between ADC mean and BCR-free survival rate
On Kaplan-Meier analysis, there was a signif icant difference in the BCR-free survival rate according to the ADC mean (p<0.001) (Fig. 3A). There is no decrease in the BCR-free survival rate of group B 30 months after the prostatectomy, whereas that of group A continuously decreased. By 50-month postradical prostatectomy, the BCR-free survival rate of group B was approximately 80%; in group A, it was approximately 20%. Additionally, we analyzed the significance of ADC mean regarding BCRfree survival according to pathologic Gleason score (≤7 vs. ≥8) and pathologic T stage (≤T2 vs. ≥T3) through subgroup analyses. As shown Fig. 3, group A also had significantly worse BCR among the subgroup of patients with pathologic Gleason score≤7 (p=0.002) (Fig. 3B) and those with pathologic T stage≤T2 (p<0.001) (Fig. 3D). However, such phenomenon was not observed among the subgroup of patients with Gleason score≥8 (p=0.051) (Fig. 3C) or those with pathologic T stage≥T3 (p=0. 119) (Fig. 3E).

DISCUSSION
In this study, we investigated only patients with highrisk prostate cancer (PSA≥20 ng/mL or a preoperative biopsy Gleason score≥8), and found that ADC mean is significantly associated with BCR-free survival in this specific patient subset. MRI technology is continuously evolving, and its more extensive use in clinical trials and practice has shown to improve prostate cancer diagnosis and treatment planning [3]. Additionally, newly developed 3-T MRI systems have provided several useful diagnostic measures, such as the ADC value, for evaluating prostate cancer [4][5][6][8][9][10].
Verma et al. [4] claim that ADC values might help to predict the incidence of prostate cancer, especially for tumors located in the peripheral zone [8]. They also reported that the ADC values were negatively correlated with the postsurgical Gleason grade in patients with prostate cancer (r=−0.39 for peripheral zone cancer). Furthermore, both ADC values and tumor volumes were found to significantly predict tumor aggressiveness, specifically in the peripheral   [5] reported that the ADC values obtained using 3-T MRI showed an inverse relationship with the Gleason grade in peripheral zone prostate cancer [9,10]. Moreover, a high discriminatory performance was attained when differentiating between low-, intermediate-, and highgrade cancer. However, because our cohort comprised only high-risk prostate cancer patients, a pathologic Gleason score ≥8 had no significant correlations with the BCR.
Both the tumor volume and true diffusion ADC were reported as signif icant and independent predictors of histologic progression by van As et al. [7] This was consistent with our findings that pathologic stage≥T3 disease and low ADC values were significant predictors of progression as determined by BCR on univariate Cox regression analyses. Furthermore, ADC mean <746×10 −6 mm 2 /s measured on the ADC maps correlated with early BCR on Kaplan-Meier

ADC in patients with high-risk prostate cancer
analysis and multivariate Cox regression analysis. The prognoses of patients with high-risk prostate cancers who had lower ADC mean values were worse. As mentioned in the introduction, the ADC decreases as tissue cells become denser. A tumor typically demonstrates denser cell distribution and sparser extracellular space; therefore, the ADC value is lower in prostate cancer tissue. Denser tumor cellularity may be related with tumor stage and aggressiveness. So ADC value can be used as surrogate marker of tumor biology.
Because low risk patient group of prostate cancer has higher ADC value than high risk patient group of prostate cancer, it is more difficult to detect cancer and estimate prognosis in low risk patient group of prostate cancer than high risk patient group of prostate cancer. So we chose the high risk patient group of prostate cancer for analysis. The reason that the PSA level and pathologic Gleason score≥8 did not affect BCR is that our inclusion criteria encompassed patients with PSA≥20 ng/mL or a preoperative biopsy Gleason score≥8; hence, our study was already aimed towards patients with advanced disease. We selected the 3-T MRI protocol because of higher magnetic field homogeneity and future applicability. Kitajima et al. [21] claim said that 3-T MRI may detect prostate cancer more effectively than 1.5 T MRI because of higher signal-noise ratio, faster acquisition time, and higher spatial resolution. Positioning lesions with low ADC values was difficult owing to the ADC readers' subjective differences, which resulted in subtle variations in the reading of these values; however, the range of ADC reading variations was small. Automated reading of ADC values using computer software would be helpful for future studies.
One abnormal result which we found is the discrepancy between biopsy Gleason score≥8 (72.6%) and pathologic Gleason score≥8 (30.6%). Not only group A (ADC<746×10 −6 mm 2 /s) but also group B (ADC≥746×10 −6 mm 2 /s) have lower pathologic Gleason score≥8 than biopsy Gleason score≥8 (Table 1). We discussed this down grading with Department of Pathology in Seoul National University Hospital, but could not find causes. So we need to investigate this problem further.
One limitation of our study is its retrospective nature; selection bias was possible because we only included patients who initially underwent prostatectomy. Additionally, we used the average ADC value, whereas other studies reported the minimum, 10th, and/or 25th percentiles as well as other metrics such as skewness and kurtosis. Inability to use b-values other than 0 and 1,000 s/mm 2 is also a limitation of our study; moreover, translating our specific cutoff value across different scanners and protocols is also difficult. Therefore, devising a new universal cutoff value is warranted. When we tried propensity score matching about relationship between pathologic lymph node positive and BCR-free survival rate, we could not secure statistic significance because of small number of patients. This means that we cannot exclude confounding factor except ADC value. Nevertheless, our research has important clinical implications in that the ADC mean can predict the prognoses of patients with high-risk prostate cancer.