Skip to main content
African Journal of Urology
Download PDF

Diagnostic accuracy of MRI-based PSA density for detection of prostate cancer among the Thai population

African Journal of Urology volume 29, Article number: 4 (2023) Cite this article

Abstract

Background

The PSAD calculating by the serum PSA level divided by prostate volume had more specificity and accuracy than the serum PSA level for detection of prostate cancer.

Methods

MRI examinations of 319 patients who had suspected prostate cancer between January 2014 and December 2019 were retrospectively reviewed. Prostate volumes were measured by MRI images and PSAD values were calculated. The accuracy and optimal cutoff points of MRI-based PSAD were evaluated using receiver operating characteristic curves (ROC curves). Correlations between the MRI-based PSAD and Gleason scores were also analyzed to predict prognosis of prostate cancer.

Results

Overall, of 154 patients were included in this study, 59 patients (38.31%) were diagnosed with prostate cancer. The optimal cutoff point of PSAD was 0.16 (81.40% sensitivity, 54.70% specificity, 52.70% PPV, 82.50% NPV), and the AUC was 0.680 (95% CI: 0.609–0.751). In subgroup analyses, the optimal cutoff point of PSAD in patients with serum PSA 4–10 ng/ml was 0.16 (61.10% sensitivity, 76.00% specificity) and for > 10 ng/ml was 0.30 (68.30% sensitivity, 64.30% specificity). Furthermore, there was a statistically significant correlation between PSAD and Gleason scores (p-value 0.014).

Conclusions

The optimal cutoff point of MRI-based PSAD was 0.16 which was relatively different from international consensus.

1 Background

Prostate cancer is the 4th most common cancer in Thai men with 6467 new cases in 2018 or 7.6% of all new cancer cases in Thai men [1]. Early treatments of the prostate cancer can improve survival rates and quality of life of the patients, thus the screening tools have an important role in improving quality of life of the patients [2]. Nowadays, Prostate-Specific-Antigen (PSA) is among the best screening tools for early detection due to high sensitivity. The limitation of PSA is its relative lack of specificity. Other conditions could elevate PSA level, such as benign prostatic hypertrophy (BPH), and prostatitis [3, 4].

The PSA density (PSAD) which is calculated from the PSA level (ng/ml) divided by prostate volume (ml) is more accurate and has more specificity than the PSA level alone for detection of prostate cancer [5,6,7,8,9]. The optimal cutoff point of PSAD for detection of prostate cancer was different among races [10,11,12,13].

This study was aimed to investigate the accuracy and optimal cutoff point of the MRI-based PSAD among Thai population. Ibrahim et al. reported there was a significant relationship between the PSAD and the Gleason score in prostate cancer patients [14]. Thus, this study was also aimed to investigate the correlation between the PSAD and Gleason score for predicting prognosis of prostate cancer patients.

2 Methods

2.1 Patient population

This retrospective study was approved by the Ethics Committee for Human Research. The MRIs of the prostate gland of patients who were suspected of prostate cancer between January 2014 and December 2019 were retrospectively reviewed.

2.1.1 Inclusion criteria

  1. 1.

    Patients who underwent MRI of the prostate gland.

  2. 2.

    Patients who underwent biopsy of the prostate gland and were pathologically confirmed, regardless of systemic or targeted biopsy, TRUS alone or MRI-fusion and number of core biopsy.

  3. 3.

    Serum PSA levels of patients who were investigated within 3 months from MRIs of their prostates, prior to biopsy.

2.1.2 Exclusion criteria

  1. 1.

    Patients who were treated before undergoing MRI of prostate gland, including surgery, radiation therapy, chemotherapy, or hormonal treatment.

2.2 MRI techniques and evaluation

All patients were imaged with the MRI technique using the 3-T MRI scanner (Achieva, Philips Heath Care) or 1.5-T MRI scanner (Aera, Siemens AG 2012), without an endorectal coil.

Width was measured in the axial T2W image; length and height were measured in the mid-sagittal T2W image, as shown in Fig. 1. Three dimensions of prostate gland were measured by two radiologists (one genitourinary radiologist, and a body imaging radiologist) for calculating prostate volume. The prostate volume was calculated using the ellipsoid formula:

Fig. 1
figure 1

Measurement of prostate gland size in three dimensions. a Mid-sagittal image using for measurement of length and height. b Axial T2W using for measurement of width

Full size image
$$Prostate\,\, volume \left(ml\right)=\,width\,\, \left(cm\right) \times length\,\, \left(cm\right) \times height\,\, \left(cm\right) \times \frac{\pi }{6}$$

Two radiologists independently reviewed images and blinded to patient information. The interrater reliability was also assessed.

2.3 PSAD calculation

The PSAD was calculated by

$$PSAD= \frac{PSA\,\, level\,\, (ng/ml)}{prostate\,\, volume (ml)}$$

2.4 Statistical analyses

Categorical variables were demonstrated as numbers (percentage). Continuous variables were demonstrated as mean (± standard deviation) or median (± interquartile range), as appropriate. Comparison of categorical variables was done using Fisher’s exact test or Chi-square test, as appropriate. Comparison of continuous variables using the independent Student t-test or Mann–Whitney U test, as appropriate.

Subgroup analyses of PSAD were also performed and categorized in three groups; patients with serum PSA levels < 4 ng/ml, 4–10 ng/ml, and > 10 ng/ml. Comparisons of categorical and continuous variables of subgroups were performed using the Chi-square test and one-way ANOVA or Kruskal-Walis test, as appropriate.

The receiver operating characteristic curves (ROC curves) were used to evaluate the accuracy of PSAD for detection of prostate cancer and optimal cutoff points. Correlation between PSAD and the Gleason score was analyzed using the Kruskal-Walis test.

Inter-rater reliability was also performed using the Intraclass Correlation Coefficient (ICC).

All analyses were performed using RelSTATA version 10. A p-value < 0.05 was considered statistically significant.

3 Results

3.1 Patient population

MRI examinations of 319 patients who had suspected prostate cancer between January 2014 and December 2019 were retrospectively reviewed. Among these patients, 165 were excluded due to incomplete data (92) and prior treatments (73). Therefore, 154 patients were included in analyses.

Patient ages ranged from 50 to 90 years (mean 66.70 ± 7.15). Fifty-nine of the 154 patients (38.31%) were positive for prostate cancer.

The median serum PSA level and median prostate volume of prostate cancer patients was 14.00 ng/ml (IQR, 9.58–45.13) and 46.99 ml (IQR, 32.68–63.92). The median serum PSA level of 9.30 ng/ml (IQR, 6.49–13.79) and median prostate volume of patients without prostate cancer was 62.41 ml (40.60–79.79). Patients with prostate cancer had significantly higher serum PSA levels, and PSADs than patients without prostate cancer, p-values < 0.001, and 0.017. Demographic data of all patients are shown in Table 1. The patients were categorized into 3 subgroups with serum PSA levels of < 4 ng/ml, 4–10 ng/ml, and > 10 ng/ml. There were only 3 patients (1.95%) with serum PSA levels < 4 ng/ml, and none of these patients was diagnosed with prostate cancer. There were 68 patients (44.16%) with serum PSA levels 4–10 ng/ml, and 83 patients (53.90%) with serum PSA > 10 ng/ml. Eighteen patients (30.51%) with serum PSA levels 4–10 ng/ml and 41 patients (69.49%) with serum PSA levels > 10 ng/ml were diagnosed with prostate cancer, (p-value 0.006). PSAD among these subgroups were those with serum PSA levels < 4, 0.04 (0.015–0.065), 4–10, 0.13 (0.09–0.22), and > 10 ng/ml, 0.32 (0.19–0.79) among patients with significant differences (p-value < 0.001). Demographic data of these subgroups are shown in Table 2.

Table 1 Demographic data of all patients
Full size table
Table 2 Demographic data of patients with serum PSA levels < 4 ng/ml, 4–10 ng/ml, and > 10 ng/ml
Full size table

3.2 ROC curves of PSAD were analyzed for detection of prostate cancer

The optimal cutoff point was 0.16 (81.40% sensitivity, 54.70% specificity, 52.70% positive predictive value, 82.50% negative predictive value) as shown in Table 3, and the area under the curve was 0.680 (95%CI: 0.609–0.751).

Table 3 Cutoff point for PSAD in the discrimination of prostate cancer of all patients
Full size table

In subgroup analyses, the optimal cutoff point of patients with serum PSA levels 4–10 ng/ml, and > 10 ng/ml was 0.16 (61.10% sensitivity, 76.00% specificity) and 0.30 (68.30% sensitivity, 64.30% specificity) as shown in Table 4. The receiver operating characteristic (ROC) curves of PSAD in identification of prostate cancer are shown in Fig. 2.

Table 4 Cutoff point for PSAD in the discrimination of prostate cancer among patients with PSA levels 4–10 and > 10 ng/ml
Full size table
Fig. 2
figure 2

Receiver operating characteristic (ROC) curves of PSAD in discrimination of prostate cancer

Full size image

3.3 Correlation between PSAD and gleason score

The median PSADs were 0.27, 0.19, 0.27, 0.23, 0.23, 1.62, 0.86, 2.42 in patients with Gleason scores of 2 + 3, 3 + 3, 3 + 4, 4 + 3, 4 + 4, 4 + 5, 5 + 4, 5 + 5. A statistically significant correlation between PSAD and Gleason scores (p-value 0.014) was found. Box plots of PSADs stratified by the Gleason score are shown in Fig. 3.

Fig. 3
figure 3

Correlation between PSAD and gleason score

Full size image

3.4 Interobserver agreement

Intraclass Correlation Coefficient (ICC) between two radiologists was 0.9894 (95%CI 0.9855–0.9922), indicating good reliability.

4 Discussion

Serum PSA levels are currently used as screening tools for detection of prostate cancer, however, there is a relative lack of specificity. The current study found the median serum PSA level in patients with prostate cancer was significantly higher than its patients without prostate cancer (14.00 ng/ml of serum PSA in patients with prostate cancer, and 9.30 ng/ml of patients without prostate cancer), p-value < 0.001. Furthermore, the median prostate volume in patients with prostate cancer was significantly lower than its patients without prostate cancer (46.99 ml of volume in patients with prostate cancer and 62.41 ml of volume in patients without prostate cancer), p-value = 0.016. These findings were concordant with previous studies that revealed benign prostate hypertrophy could elevate serum PSA levels. [3, 4, 7]

Many studies reported PSA density (PSAD) which calculated from the PSA level (ng/ml) divided by prostate volume (ml) had more accuracy and more specificity than PSA level alone for detection of prostate cancer [5,6,7,8,9]. Most studies used TRUS determined the prostate volume, which differed from MRI in our study. The previous studies suggested PSAD cut-off ranged from 0.15 to 0.2, our study suggested the optimal cut-off at 0.16 which was also within that range.

Previous studies reported the PSA level was different among Asians and Caucasians, therefore, the PSAD and cutoff points were also different. Saema et al. reported the optimal cutoff point was 0.15 (sensitivity 78%, specificity 43%) in the Thai population with PSA levels between 4 and 10 ng/ml [15]. Sathean et al. investigated the optimal cutoff point within the Thai population with different BMI and PSA levels between 4 and 10 ng/ml. This study reported the optimal cutoff points were 0.15 in normal weight patients (BMI < 23), and overweight patients (BMI 23–24.9), and 0.06 in obese patients (BMI ≥ 25) [16]. These studies, however, used the prostate volume by measuring transrectal ultrasonography (TRUS). Previous studies reported prostate volume measuring by MRI to be more accurate than measuring by TRUS [17,18,19,20,21].

In the current study, the optimal cutoff point of PSAD for discrimination of prostate cancer was 0.16 (81.40% sensitivity, 54.70% specificity, 52.70% positive predictive value, 82.50% negative predictive value), and the area under the curve was 0.680 (95%CI: 0.609–0.751). Although the PSAD level of 0.17 demonstrated no difference in terms of sensitivity and specificity, the lower the better, especially for decreasing the unnecessary biopsy. Thai ethnic may make these results different from a few previous studies that reported the optimal cutoff points of PSAD in Brazilian, Iranian, and Indonesian patients were 0.11, 0.11, and 0.70 [8,9,10] .

In subgroup analyses of patients with serum PSA < 4 ng/ml, 4–10 ng/ml, and > 10 ng/ml, it was found that none of patients with serum PSA < 4 ng/ml was diagnosed with prostate cancer. These results could be supported that the patients with serum PSA < 4 ng/ml were low risk groups for cancer. Thus, follow-up of these patients could be more beneficial than biopsies taken. This current study also reported optimal cutoff points of PSAD in patients with serum PSA 4–10 ng/ml, and > 10 ng/ml were 0.16 (61.10% sensitivity, 76.00% specificity) and 0.30 (68.30% sensitivity, 64.30% specificity). These results were similar to those in previous studies. Lin et al. reported the optimal cutoff points in patients with serum PSA 2.5–10 ng/ml, and 10–20 ng/ml were 0.15, and 0.33 [11].

Karademir et al. reported there was a significant relationship between the PSAD and the Gleason score in prostate cancer patients [14]. The current study also found statistically significant correlations between PSAD and Gleason scores (p-value 0.014) that supported their results. These findings would help to predict the prognosis of prostate cancer patients.

We had several limitations in this study. First, this was the retrospective study. Second, we tried our best to recruit all available prostate cancer patients examined by MRI during the study period; however, there were a small number.

5 Conclusions

The optimal cutoff point of PSAD was 0.16 which was relatively different from the international consensus (81.40% sensitivity, 54.70% specificity, 52.70% PPV, 82.50% NPV), and the AUC was 0.680 (95%CI: 0.609–0.751).

In subgroup analyses, the optimal cutoff points of PSAD in patients with serum PSA 4–10 ng/ml, and > 10 ng/ml were 0.16 (61.10% sensitivity, 76.00% specificity) and 0.30 (68.30% sensitivity, 64.30% specificity). Furthermore, there were statistically significant correlations between the PSAD and Gleason scores (p-value 0.014).

Availability of data and materials

All data and material in this study are available to your request.

Abbreviations

AUC:

Area under curve

BPH:

Benign prostatic hyperplasia

ICC:

Interclass correlation coefficient

IQR:

Interquartile range

MRI:

Magnetic resonance imaging

PSA:

Prostatic specific antigen

PSAD:

PSA density

ROC:

Receiver operating characteristic

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. https://doi.org/10.3322/caac21660

    Article  Google Scholar 

  2. Kim HW, Ko YH, Kang SH, Lee JG (2011) Predictive factors for prostate cancer in biopsy of patients with prostate-specific antigen levels equal to or less than 4 ng/ml. Korean J Urol 52:166–171

    Article  Google Scholar 

  3. Postma R, Schroder FH (2005) Screening for prostate cancer. Eur J Cancer 41:825–833

    Article  CAS  Google Scholar 

  4. Partin AW, Oesterling JE (1994) The clinical usefulness of prostate specific antigen: update 1994. J Urol 152:1358–1368

    Article  CAS  Google Scholar 

  5. Mueller-Lisse UG, Mueller-Lisse UL, Haller S, Schneede P, Scheidler JE, Schmeller N et al (2002) Likelihood of prostate cancer based on prostate-specific antigen density by MRI: retrospective analysis. J Comput Assist Tomogr 26:432–437

    Article  Google Scholar 

  6. Aksoy Y, Oral A, Aksoy H, Demirel A, Akcay F (2003) PSA density and PSA transitional zone density in the diagnosis of prostate cancer in PSA gray zone cases. Ann Clin Lab Sci 33:320–323

    Google Scholar 

  7. Stephan C, Stroebel G, Heinau M, Lenz A, Roemer A, Lein M et al (2005) The ratio of prostate-specific antigen (PSA) to prostate volume (PSA density) as a parameter to improve the detection of prostate carcinoma in PSA values in the range of < 4 ng/mL. Cancer 104:993–1003

    Article  Google Scholar 

  8. Gregorio EP, Grando JP, Saqueti EE, Almeida SH, Moreira HA, Rodrigues MA (2007) Comparison between PSA density, free PSA percentage and PSA density in the transitional zone in the detection of prostate cancer in patients with serum PSA between 4 and 10 ng/mL. Int Braz J Urol 33:151–160

    Article  Google Scholar 

  9. Ghafoori M, Varedi P, Hosseini SJ, Asgari M, Shakiba M (2009) Value of prostate-specific antigen and prostate-specific antigen density in detection of prostate cancer in an Iranian population of men. Urol J 6:182–188

    Google Scholar 

  10. Shahab AA, Soebadi DM, Djatisoesanto W, Hardjowijoto S, Soetojo S, Hakim L (2013) Prostate-specific antigen and prostate-specific antigen density cutoff points among Indonesian population suspected for prostate cancer. Prostate Int 1:23–30

    Article  Google Scholar 

  11. Lin YR, Wei XH, Uhlman M, Lin XT, Wu SF, Diao PF et al (2015) PSA density improves the rate of prostate cancer detection in Chinese men with a PSA between 2.5–10.0 ngml−1 and 10.1–20.0 ngml−1: a multicenter study. Asian J Androl 17:503–507

    Google Scholar 

  12. Teoh JY, Yuen SK, Tsu JH, Wong CK, Ho BS, Ng AT et al (2017) The performance characteristics of prostate-specific antigen density in Chinese men. Asian J Androl 19:113–116

    Google Scholar 

  13. Jue JS, Barboza MP, Prakash NS, Venkatramani V, Sinha VR, Pavan N et al (2017) Re-examining prostate-specific antigen (PSA) density: defining the optimal PSA range and patients for using PSA density to predict prostate cancer using extended template biopsy. Urology 105:123–128

    Article  Google Scholar 

  14. Karademir I, Shen D, Peng Y, Liao S, Jiang Y, Yousuf A (2013) Prostate volume derived from MRI and volume-adjusted serum prostate-specific antigen: correlation with Gleason score of prostate cancer. AJR AM J Roentgenol 201:1041–1048

    Article  Google Scholar 

  15. Saema A, Kochakarn W, Lertsithichai P (2012) PSA density and prostate cancer detection. J Med Assoc Thai 95:661–666

    Google Scholar 

  16. Sathean T, Ekkarin C, Chaiyong N, Sunai L, Tawatchai T, Kittipong P (2015) Diagnostic accuracy of BMI and PSA density in screening prostate cancer patients in the PSA diagnostic gray zone (4–10 ng/ml). TJU 36:1–10

    Google Scholar 

  17. Hoshii T, Neshiyama T, Toyabe S, Akazawa K, Komatsu S, Kaneko M et al (2007) Evaluation of magnetic resonance imaging-based prostate-specific antigen density of the prostate in the diagnosis of prostate cancer. Int J Urol 14:305–310

    Article  Google Scholar 

  18. Sfoungaristos S, Perimenis P (2012) PSA density is superior than Gleason score for adverse pathologic feathers prediction in patients with clinically localized prostate cancer. Can Urol Assoc J 6:46–50

    Article  Google Scholar 

  19. Bhat NR, Vetter JM, Andriole GL, Shetty AS, Ippolito JE, Kim EH (2019) Magnetic resonance imaging-defined prostate-specific antigen density significantly improves the risk prediction for clinically significant prostate cancer on biopsy. Urology 126:152–157

    Article  Google Scholar 

  20. Jeong CW, Park HK, Hong SK, Byun SS, Lee HJ, Lee SE (2008) Comparison of prostate volume measured by transrectal ultrasonography and MRI with actual prostate volume measured after radical prostatectomy. Urol Int 81:179–185

    Article  Google Scholar 

  21. Paterson NR, Lavallee LT, Nguyen LN, Witiuk K, Ross J, Mallick R (2016) Prostate volume estimations using magnetic resonance imaging and transrectal ultrasound compared to radical prostatectomy specimens. Can Urol Assoc J 10:264–268

    Article  Google Scholar 

Download references

Acknowledgements

Ms Jitjira Chaiyarit from Clinical Epidemiology Unit, Faculty of Medicine, Khon Kaen University, for the biostatistical consultation. Emeritus Professor James A. Will who editing the manuscript via Publication Clinic KKU, Thailand.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Radiology, Faculty of Medicine, Khon Kaen University, 123 Group 16, Mittraparp Rd, Muang, Khon Kaen Province, 40002, Thailand

    Chalida Aphinives, Supajit Nawapun & Chutima Tungnithiboon

Authors
  1. Chalida Aphinives
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Supajit Nawapun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chutima Tungnithiboon
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CA conceptualization, methodology, validation, resources, writing review & editing, project administration. SN conceptualization, methodology, investigation, data curation, writing review & editing. CT methodology, investigation, writing original draft. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Chalida Aphinives.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Khon Kaen University Ethics Committee for Human Research based on the Declaration of Helsinki and the ICH Good Clinical Practice Guidelines with Reference No. HE621384. Consent to participate is not applicable as it is a retrospective study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aphinives, C., Nawapun, S. & Tungnithiboon, C. Diagnostic accuracy of MRI-based PSA density for detection of prostate cancer among the Thai population. Afr J Urol 29, 4 (2023). https://doi.org/10.1186/s12301-023-00335-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12301-023-00335-9

Keywords

  • PSAD
  • PSA density
  • MRI-based PSAD
  • Prostate cancer