Potential synergy between PSMA uptake and tumour blood flow for prediction of human prostate cancer aggressiveness

All [⁸²Rb]Rb PET/CT scans but one were performed on GE Discovery MI Digital Ready PET/CT (GE Healthcare, Waukesha, Wisconsin, USA), and a single scan was performed on GE Discovery MI (5 ring) PET/CT. Details of the scan and reconstruction protocols have previously been described [31]. A bolus of [⁸²Rb]RbCl (1110 MBq) was injected at scan start by the Cardiogen-82 generator infusion system (Bracco, Monroe Township, New Jersey, USA). The static image series of [⁸²Rb]Rb PET (3 to7 min post-injection) were used for SUV analysis.

[⁶⁸Ga]Ga-PSMA-11 PET/CT scans were performed one hour post-injection of 2.14 MBq [⁶⁸Ga]Ga-PSMA-11 (⁶⁸Ga-Glu-CO-Lys(Ahx)-HBED-CC) per kilogram body weight on a Siemens Biograph TruePoint PET/CT scanner (Siemens, Erlangen, Germany). 3D PET acquisitions with 3 min per bed position from vertex cranii to mid-femur were performed. Low-dose CT for attenuation correction was performed with all common corrections applied using the TrueX reconstruction algorithm (4 iterations and 21 subsets) and a 3-mm Gaussian post-filter (XYZ).

The mpMRI scans were performed according to clinical guidelines and the PIRADS v 2.1 minimum protocol [34] on 3 T platform Siemens Skyra (Siemens, Erlangen, Germany).

[⁶⁸Ga]Ga-PSMA-11 PET/CT scans and [⁸²Rb]Rb PET/CT scans were co-registered using the CT scan as bridge. Co-registrations with the T2 weighted sequence of the mpMRI were also carried out in the 24 patients where mpMRI was available, again using the CT scan as bridge. Volume-of-interests (VOI) were defined in two different ways. First, the tumour VOIs were defined by the [⁶⁸Ga]Ga-PSMA-11 activity. The threshold used for automatic VOI drawing on [⁶⁸Ga]Ga-PSMA-11 PET varied between individual patients, as no universal threshold could be defined. In two patients with basal tumour location, the bladder activity was masked. An external tumour VOI defined by the mpMRI was applied in the 24 patients with mpMRI scan available. The tumour VOIs were transferred to the [⁸²Rb]Rb PET/CT and/or [⁶⁸Ga]Ga-PSMA-11 PET/CT scans for measurement of TBF and [⁶⁸Ga]Ga-PSMA-11-uptake, respectively. The analyses were mainly performed on the data from [⁶⁸Ga]Ga-PSMA-11-guided VOIs; forty-eight lesions could be automatically drawn from the [⁶⁸Ga]Ga-PSMA-11 hotspot, whereas the last four lesions (benign and ISUP GG-1) displayed too low activity and was drawn manually, guided by MRI. The cohort with MRI-guided VOIs was analysed for using an external modality to test the models on less biased data.

Image co-registration and VOI analysis were performed with Hermes Viewer version 5.0 (Hermes Medical Solutions, Stockholm, Sweden).

The ISUP GG used in analysis was a “best estimate”, using post-prostatectomy ISUP GG if available, otherwise MRI-guided biopsy ISUP GG if available and, if none of the previous were accessible, trans-rectal ultrasound-guided biopsy ISUP GG were used.

Q-Q-plots and histograms were used for testing data normality. Normally distributed data are reported as mean ± standard deviation and non-normally distributed data as median with range and log-transformation in parametric analysis. p values < 0.05 were considered statistically significant.

As ISUP GG is an ordinal scale, Spearman’s rank correlation (rho) was applied for analysis of correlations involving ISUP GG. For continuous variables, Pearson’s correlation (r) was applied. For correlation analysis, ISUP GG = 0 was used for benign lesions in some analyses. Receiver operating characteristic (ROC) analyses were used for calculating area under the curve (AUC), sensitivity and specificity. Negative predictive value (NPV) and positive predictive value (PPV) were calculated according to standard definitions. McNemar’s test for difference between paired nominal data was used to compare the diagnostic accuracies. The interaction between [⁶⁸Ga]Ga-PSMA-11 SUVmax and [⁸²Rb]Rb SUVmax for separation of ISUP GG was tested using ordinal and nominal logistic fit models.

Data were collected and managed using REDCap (Vanderbilt University Medical Center, Nashville, Tennessee, USA), hosted at Aarhus University [35]. Statistical analysis was performed in STATA version 16.1 (StataCorp LLC, College Station, Texas, USA) and JMP (SAS Institute Inc., Cary, North Carolina, United States).

The correlation between [⁶⁸Ga]Ga-PSMA-11 SUVmax and ISUP GG varies greatly across the published studies. The present correlation is in line with the study by Chen et al. (rho = 0.55, p < 0.01, n = 51, radical prostatectomy Gleason Score) [8] and notably higher than in previous studies by our group (rho = 0.21, p < 0.001, n = 690, for biopsy ISUP GG) and (rho = 0.38, p < 0.001, n = 247, radical prostatectomy ISUP GG) [10] and by Cytawa et al. (rho = 0.35, p = 0.001, n = 82, biopsy Gleason Score) [9]. Another study by Demirci et al. found a good correlation (r = 0.66, p < 0.001) between SUVmax and ISUP GG in 141 patients [6]; however, they used Pearson’s correlation, which should not be applied for ordinal variables such as ISUP GG. A direct comparison between the above-mentioned studies is challenging, as some studies used Gleason Score while others used ISUP GG, Klingenberg et al. [10] included high-risk patients only, where the correlation seemed to disappear in the present study, and finally Cytawa et al. [9] used the [⁶⁸Ga]Ga-PSMA-I&T ligand.

The AUC, sensitivity and specificity for [⁶⁸Ga]Ga-PSMA-11 SUVmax in the present study (Table 4) were in line with the results from Demirci et al. [6], and again, substantially higher than the results from Klingenberg et al. [10]. A direct comparison is, again, not fair, as Klingenberg et al. examined high-risk patients exclusively. Meanwhile, the large overlap between the ISUP GGs, where even very aggressive ISUP GG-4–5 tumours can display very low [⁶⁸Ga]Ga-PSMA-11 uptake, are also seen in the present study (Fig. 2a).

Tumour delineation is not always identical between the three modalities used in the present study, as the MRI VOI is occasionally expanded, especially by the [⁶⁸Ga]Ga-PSMA-11 activity. As proposed by Zamboglou et al. [36], this could mean that the tumour delineation is more precise if not based on a sole modality. Hence, tumour delineation for radiation planning [36] and biopsy guidance [37] could be potential indications for [⁶⁸Ga]Ga-PSMA-11 PET/MRI.

The coherency between quantitative TBF and PCa aggressiveness is being established, and the present results are in line with our previous publications [31, 33]. However, the potential clinical role of quantitative TBF is undetermined in PCa management. The results of TBF measurement with [⁸²Rb]Rb complements other studies using quantitative pharmacokinetic analysis of the dynamic contrast-enhanced series of MRI, which found an improvement in the PPV of mpMRI for primary local staging of PCa [38‐41]. Meanwhile, the studies using the simpler qualitative analysis of the dynamic contrast-enhanced series generally report more limited additional value of the Gadolinium contrast examination [42]. Hence, there could be an unexploited potential in the quantitative pharmacokinetic analysis of prostate dynamic contrast-enhanced MRI at selecting which patients to biopsy, as absolute quantification of perfusion with DCE MRI might provide comparable information to perfusion PET. In PET studies on other cancers though, low blood flow—high metabolism mismatch, which is essentially a sign of hypoxia, was found to be the best predictor of tumour grade, treatment response, and/or survival [43‐46].

Studies showed that the decrease in TBF as response to neoadjuvant chemotherapy in locally advanced breast cancer was a strong predictor of disease-free survival and overall survival [21, 23] and that TBF change in metastases from different primary tumours after sunitinib malate treatment was predictive of clinical benefit [19]. Another study showed that the change in TBF provides information on anti-angiogenic treatment response beyond prostate-specific antigen (PSA) in androgen independent PCa [15]. Hence, another potential gain could be to measure changes in TBF over time, for example during therapy or during active surveillance.

Even though both PSMA uptake and TBF can classify most lesions correctly into significant or non-significant PCa, the accuracies of the methods individually are probably too low for clinical decision-making. The main limitation for both methods is the number of false negatives, which means that clinically significant PCa are missed. It is well known that cancers become increasingly heterogeneous as they dedifferentiate and becomes more aggressive. This heterogeneity regards PSMA expression [47]] and apparently, TBF too, as both parameters can occasionally be low in ISUP GG-4 and GG-5 patients (Fig. 2a, c). Due to the complex tumour biology, a single aspect of physiology seems too sparse for full separation of significant from insignificant PCa. The highly significant interaction parameter found in the present study shows a crossed interaction between PSMA uptake and TBF. This means that PSMA uptake and TBF are complementary in some of the high-risk patients, where the correlation between the two parameters is lost (Fig. 3). By utilizing this complementary tumour biology information with a combined analysis using both PSMA uptake and TBF, especially the NPV for separation of clinically significant PCa from insignificant findings improves, without compromising the PPV. This results in a significant reduction in the false negatives (missed significant PCa) from six to one in this cohort (Table 4). The model, including the interaction parameter, was significant regardless of VOI drawing methods and compensation for multiple lesions per patient. The model is preliminary though and needs further external validation in larger studies, but the basic principles should be generalizable. Such multiparametric PET approach may be the key to non-invasive risk evaluation. These results illustrate that two aspects of tumour biology characterizes the tumour more precisely than one. A similar synergy with other physiologic parameters, hypoxia for example, may very well show the same tendency. An advantage is that PSMA PET and TBF are very much within clinical reach, as PSMA PET is already a dominating imaging modality in PCa imaging, and TBF can be estimated with various modalities. Other studies found correlations between PCa aggressiveness and K₁ influx of other tracers including [¹⁵O]-H₂O [17], [¹⁸F]-flourocholine [48, 49], [¹¹C]-donepezil [50], and [¹¹C]-acetate [51]. The authors believe that the most promising applications of this combined analysis is characterization of tumour metabolism for primary risk evaluation and monitoring more than for detection of biochemical recurrence.

We found it important that the two tracers performed with such similarity in the analyses. The correlation between tumour [⁶⁸Ga]Ga-PSMA-11- and [⁸²Rb]Rb uptake suggests that the tumour PSMA uptake may be flow-limited (Fig. 3). We found this sufficiently interesting to design a future study with dynamic PSMA PET and ¹⁵O-H₂O PET, which is gold standard of perfusion, to characterize the composition of the PSMA signal. If the PSMA uptake rate is an appropriate reflection of TBF in PCa, an approach with early dynamic plus late static PSMA PET scanning may examine both PSMA uptake and TBF and provide valuable additional information of biological potential of the tumour in selected patient categories. This could be a further step towards PSMA PET as a one-stop shop in PCa imaging to assess both whole body tumour burden and biological potential of the primary tumour.