Dynamic contrast-enhanced CT for prostate cancer: relationship between image noise, voxel size, and repeatability

Synthesis, Preclinical Evaluation, and First-in-Human PET Study of [68Ga]-Labeled Biphenyl-Containing PSMA Tracers

Radioisotope-labeled prostate-specific membrane antigen (PSMA) PET tracers have gained popularity in diagnosing prostate cancer (PCa). This study aimed to improve the affinity and tumor-targeting capabilities of new PSMA tracers by increasing the number of pharmacophores that specifically bind to PSMA. Using biphenyl as a core scaffold, we investigated the relationship among spacer segments, affinity, and pharmacokinetic properties. In preclinical PET studies on mice with 22Rv1 tumors, compared with [68Ga]Ga-PSMA-11 (SUVmax = 3.37), [68Ga]Ga-PSMA-D5 (Ki = 0.15) showed higher tumor uptake (SUVmax = 3.51) and lower renal uptake (T/K = 1.84). In the first-in-human study, [68Ga]Ga-PSMA-D5 effectively detected small PCa-associated lesions and distant metastases. The advantages of [68Ga]Ga-PSMA-D5 include high tumor uptake, straightforward synthesis, and labeling, making it a promising PSMA PET tracer. Furthermore, [68Ga]Ga-PSMA-D5 contains a DOTA chelator, allowing convenient labeling with therapeutic radionuclides such as 177Lu and 225Ac, providing the potential for targeted radioligand therapy in PCa.

Optimized Therapeutic 177Lu-Labeled PSMA-Targeted Ligands with Improved Pharmacokinetic Characteristics for Prostate Cancer

Clinical trials have shown the significant efficacy of [¹⁷⁷Lu]Lu-PSMA-617 for treating prostate cancer. However, the pharmacokinetic characteristics and therapeutic performance of [¹⁷⁷Lu]Lu-PSMA-617 still need further improvement to meet clinical expectations. The aim of this study was to evaluate the feasibility and therapeutic potential of three novel ¹⁷⁷Lu-labeled ligands for the treatment of prostate cancer. The novel ligands were efficiently synthesized and radiolabeled with non-carrier added ¹⁷⁷Lu; the radiochemical purity of the final products was determined by Radio-HPLC. The specific cell-binding affinity to PSMA was evaluated in vitro using prostate cancer cell lines 22Rv1and PC-3. Blood pharmacokinetic analysis, biodistribution experiments, small animal SPCET imaging and treatment experiments were performed on normal and tumor-bearing mice. Among all the novel ligands developed in this study, [¹⁷⁷Lu]Lu-PSMA-Q showed the highest uptake in 22Rv1 cells, while there was almost no uptake in PC-3 cells. As the SPECT imaging tracer, [¹⁷⁷Lu]Lu-PSMA-Q is highly specific in delineating PSMA-positive tumors, with a shorter clearance half-life and higher tumor-to-background ratio than [¹⁷⁷Lu]Lu-PSMA-617. Biodistribution studies verified the SPECT imaging results. Furthermore, [¹⁷⁷Lu]Lu-PSMA-Q serves well as an effective therapeutic ligand to suppress tumor growth and improve the survival rate of tumor-bearing mice. All the results strongly demonstrate that [¹⁷⁷Lu]Lu-PSMA-Q is a PSMA-specific ligand with significant anti-tumor effect in preclinical models, and further clinical evaluation is worth conducting.

Optimized 68Ga-Labeled Urea-Based PSMA-Targeted PET Tracers for Prostate Cancer

Prostate-specific membrane antigen (PSMA)-targeting radiopharmaceuticals have become some of the most promising tools for the diagnosis and therapy prostate cancer (PCa). The structure of existing PSMA-targeted PET tracers still needs to be optimized to improve their pharmacokinetic properties and tumor-to-background ratio. In this study, we modified the structure of a well-studied PSMA tracer, and six novel tracers with variable hydrophilicity and pharmacokinetics were developed and evaluated both in vitro and in vivo. All of the novel tracers showed high hydrophilicity (log p = −2.99 ± 0.33 to −3.49 ± 0.01), rapid clearance rates (elimination half-times = 15.55 to 35.97 min), and high affinity for PSMA (Ki = 8.11 ± 0.49 to 42.40 ± 2.11 nM) in vitro. Specific cell binding and micro-PET experiments showed that [⁶⁸Ga]Ga-PSMA-Q displayed the highest specific PSMA+ cell uptake (3.75 ± 0.35 IA%/10⁶ at 60 min), tumor uptake (SUVmax = 0.97 ± 0.24 at 60 min p.i.), and tumor-to-muscle ratio (59.33 ± 5.72 at 60 min p.i.), while the tumor-to-muscle ratio was much higher than that of [⁶⁸Ga]Ga-PSMA-617. The results of this study validate the clinical potential of [⁶⁸Ga]Ga-PSMA-Q for PET imaging and further targeted therapy of prostate cancer.

Synthesis, preclinical evaluation, and first-in-human study of Al18F-PSMA-Q for prostate cancer imaging

PURPOSE

To investigate the potential of a novel Al¹⁸F-labeled PSMA-targeted radiotracer for PCa diagnosis through both preclinical and pilot clinical studies.

METHODS

Al¹⁸F-PSMA-Q was prepared automatically. The binding affinity to PSMA was evaluated in vitro using the 22Rv1 (PSMA +) and PC-3 (PSMA -) cell lines. Pharmacokinetics evaluation, biodistribution study, Micro-PET imaging of Al¹⁸F-PSMA-Q in normal mice and tumor-bearing mice, and a comparison with ¹⁸F-DCFPyL were performed. PET/CT imaging was performed on 8 healthy volunteers and 20 newly diagnosed PCa patients at 1 h post-injection (p.i.). The biodistribution in human and preliminary diagnostic efficacy of Al¹⁸F-PSMA-Q were evaluated, and the radiation dosimetry was estimated using OLINDA/EXM 2.0 software.

RESULT

Qualified Al¹⁸F-PSMA-Q was efficiently prepared with a non-decay-corrected radiochemical yield (RCY) of 22.0-28.3%, a specific activity (SA) of > 50 GBq/μmol. The hydrophilicity was comparably high with a log P value of - 3.69 ± 0.39. Al¹⁸F-PSMA-Q was found to bind to PSMA specifically with a Ki value of 17.05 ± 1.14 nM. The distribution and elimination half-lives of Al¹⁸F-PSMA-Q were 3.93 min and 14.22 min, respectively, which were shorter than those of ¹⁸F-DCFPyL. Micro-PET imaging of Al¹⁸F-PSMA-Q can clearly differentiate 22Rv1 tumors from PC-3 tumors and background with a high SUVmax of 2.17 ± 0.42 and a tumor-to-muscle ratio of 84.37 ± 31.62, which were higher than those of ¹⁸F-DCFPyL (1.79 ± 0.39 and 13.25 ± 1.65). The uptake of Al¹⁸F-PSMA-Q in 22Rv1 cells and tumors can be substantially blocked by 2-PMPA. High level accumulation of Al¹⁸F-PSMA-Q was observed in organs physiologically expressing PSMA. Twenty-six tumor lesions were detected in 20 PCa patients, and the mean SUVmax values of primary tumors, lymph node metastasis, bone metastases, and tumor-muscle ratios were 19.71 ± 16.52, 5.11, 31.30 ± 29.85, and 44.77 ± 22.29, respectively. The mean SUVmax of tumors in patients with PSA > 10 ng/mL was significantly higher than that in patients with PSA ≤ 10 ng/mL (25.97 ± 18.64 vs. 10.33 ± 3.74). Meanwhile, the mean SUVmax of tumors in patients with a Gleason score ≥ 8 was significantly higher than that in patients with a Gleason score < 8 (31.85 ± 22.09 vs. 13.18 ± 11.58). The kidneys received the highest estimated dose of 0.098 ± 0.006 mGy/MBq, and the effective dose was calculated as 0.0128 ± 0.007 mGy/MBq.

CONCLUSION

The novel qualified PSMA-targeted radiotracer Al¹⁸F-PSMA-Q was conveniently prepared with favorable yield and SA. The results of preclinical and pilot clinical studies exhibited a high specific uptake in PCa lesions and an excellent tumor-to-background ratio with a reasonable radiation exposure, which indicated the great potential of Al¹⁸F-PSMA-Q for PCa imaging.

TRIAL REGISTRATION

Chinese Clinical trial registry ChiCTR2100053507, Registered 23 November 2021, retrospectively registered.

Quantitative imaging for radiotherapy purposes

Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

4D perfusion CT of prostate cancer for image-guided radiotherapy planning: A proof of concept study

Purpose

Advanced forms of prostate cancer (PCa) radiotherapy with either external beam therapy or brachytherapy delivery techniques aim for a focal boost and thus require accurate lesion localization and lesion segmentation for subsequent treatment planning. This study prospectively evaluated dynamic contrast-enhanced computed tomography (DCE-CT) for the detection of prostate cancer lesions in the peripheral zone (PZ) using qualitative and quantitative image analysis compared to multiparametric magnet resonance imaging (mpMRI) of the prostate.

Methods

With local ethics committee approval, 14 patients (mean age, 67 years; range, 57–78 years; PSA, mean 8.1 ng/ml; range, 3.5–26.0) underwent DCE-CT, as well as mpMRI of the prostate, including standard T2, diffusion-weighted imaging (DWI), and DCE-MRI sequences followed by transrectal in-bore MRI-guided prostate biopsy. Maximum intensity projections (MIP) and DCE-CT perfusion parameters (CTP) were compared between healthy and malignant tissue. Two radiologists independently rated image quality and the tumor lesion delineation quality of PCa using a five-point ordinal scale. MIP and CTP were compared using visual grading characteristics (VGC) and receiver operating characteristics (ROC)/area under the curve (AUC) analysis.

Results

The PCa detection rate ranged between 57 to 79% for the two readers for DCE-CT and was 92% for DCE-MRI. DCE-CT perfusion parameters in PCa tissue in the PZ were significantly different compared to regular prostate tissue and benign lesions. Image quality and lesion visibility were comparable between DCE-CT and DCE-MRI (VGC: AUC 0.612 and 0.651, p>0.05).

Conclusion

Our preliminary results suggest that it is feasible to use DCE-CT for identification and visualization, and subsequent segmentation for focal radiotherapy approaches to PCa.

Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data

The most widespread technique used to register sets of medical images consists of selecting one image as fixed reference, to which all remaining images are successively registered. This pairwise scheme requires one optimization procedure per pair of images to register. Pairwise mutual information is a common dissimilarity measure applied to a large variety of datasets. Alternative methods, called groupwise registrations, have been presented to register two or more images in a single optimization procedure, without the need of a reference image. Given the success of mutual information in pairwise registration, we adapt one of its multivariate versions, called total correlation, in a groupwise context. We justify the choice of total correlation among other multivariate versions of mutual information, and provide full implementation details. The resulting total correlation measure is remarkably close to measures previously proposed by Huizinga et al. based on principal component analysis. Our experiments, performed on five quantitative imaging datasets and on a dynamic CT imaging dataset, show that total correlation yields registration results that are comparable to Huizinga's methods. Total correlation has the advantage of being theoretically justified, while the measures of Huizinga et al. were designed empirically. Additionally, total correlation offers an alternative to pairwise mutual information on quantitative imaging datasets.

Performance of a fast and high-resolution multi-echo spin-echo sequence for prostate T2 mapping across multiple systems

PURPOSE

To evaluate the performance of a multi-echo spin-echo sequence with k-t undersampling scheme (k-t T₂ ) in prostate cancer.

METHODS

Phantom experiments were performed at five systems to estimate the bias, short-term repeatability, and reproducibility across all systems expressed with the within-subject coefficient of variation (wCV). Monthly measurements were performed on two systems for long-term repeatability estimation. To evaluate clinical repeatability, two T₂ maps (voxel size 0.8 × 0.8 × 3 mm³ ; 5 min) were acquired at separate visits on one system for 13 prostate cancer patients. Repeatability was assessed per patient in relation to spatial resolution. T₂ values were compared for tumor, peripheral zone, and transition zone.

RESULTS

Phantom measurements showed a small bias (median = -0.9 ms) and good short-term repeatability (median wCV = 0.5%). Long-term repeatability was 0.9 and 1.1% and reproducibility between systems was 1.7%. The median bias observed in patients was -1.1 ms. At voxel level, the median wCV was 15%, dropping to 4% for structures of 0.5 cm³ . The median tumor T₂ values (79 ms) were significantly lower (P < 0.001) than in the peripheral zone (149 ms), but overlapped with the transition zone (91 ms).

CONCLUSIONS

Reproducible T₂ mapping of the prostate is feasible with good spatial resolution in a clinically reasonable scan time, allowing reliable measurement of T₂ in structures as small as 0.5 cm³ . Magn Reson Med 79:1586-1594, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF

PURPOSE

This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF.

PROCEDURES

Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data.

RESULTS

When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach.

CONCLUSIONS

The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.

Technical prerequisites and imaging protocols for CT perfusion imaging in oncology

The aim of this review article is to define the technical prerequisites of modern state-of-the-art CT perfusion imaging in oncology at reasonable dose levels. The focus is mainly on abdominal and thoracic tumor imaging, as they pose the largest challenges with respect to attenuation and patient motion. We will show that low kV dynamic scanning in conjunction with detection technology optimized for low photon fluxes has the highest impact on reducing dose independently of other choices made in the protocol selection. We discuss, derived from relatively simple first principles, on what appropriate temporal sampling and total scan duration depend on and why optimized contrast medium injection protocols are also essential in limiting dose. Finally we will examine the possibility of simultaneously extracting standard morphological and functional information from one single 4D examination as a potential enabler for a more widespread use of dynamic contrast enhanced CT in oncology.

Patient characteristics influencing the variability of distributed parameter-based models in DCE-CT kinetic analysis

Kinetic parameter variability may be sensitive to kinetic model choice, kinetic model implementation or patient-specific effects. The purpose of this study was to assess their impact on the variability of dynamic contrast-enhanced computed tomography (DCE-CT) kinetic parameters. A total of 11 canine patients with sinonasal tumours received high signal-to-noise ratio, test-double retest DCE-CT scans. The variability for three distributed parameter (DP)-based models was assessed by analysis of variance. Mixed-effects modelling evaluated patient-specific effects. Inter-model variability (CV_inter ) was comparable to or lower than intra-model variability (CV_intra ) for blood flow (CV_inter :[4-28%], CV_intra :[28-31%]), fractional vascular volume (CV_inter :[3-17%], CV_intra :[16-19%]) and permeability-surface area product (CV_inter :[5-12%], CV_intra :[14-15%]). The kinetic models were significantly (P<0.05) impacted by patient characteristics for patient size, area underneath the curve of the artery and of the tumour. In conclusion, DP-based models demonstrated good agreement with similar differences between models and scans. However, high variability in the kinetic parameters and their sensitivity to patient size may limit certain quantitative applications.

Voxelwise comparison of perfusion parameters estimated using dynamic contrast enhanced (DCE) computed tomography and DCE-magnetic resonance imaging in locally advanced cervical cancer

PURPOSE

Dynamic contrast enhanced (DCE) imaging has gained interest as an imaging modality for assessment of tumor characteristics and response to cancer treatment. However, for DCE-magnetic resonance imaging (MRI) tissue contrast enhancement may vary depending on imaging sequence and temporal resolution. The aim of this study is to compare DCE-MRI to DCE-computed tomography (DCE-CT) as the gold standard.

MATERIAL AND METHODS

Thirteen patients with advanced cervical cancer were scanned once prior to chemo-radiation and during chemo-radiation with DCE-CT and -MRI in immediate succession. A total of 22 paired DCE-CT and -MRI scans were acquired for comparison. Kinetic modeling using the extended Tofts model was applied to both image series. Furthermore the similarity of the spatial distribution was evaluated using a Γ analysis. The correlation between the two imaging techniques was evaluated using Pearson's correlation and the parameter means were compared using a Student's t-test (p < 0.05).

RESULTS

A significant positive correlation between DCE-CT and -MRI was found for all kinetic parameters. The results showing the best correlation with the DCE-CT-derived parameters were obtained using a population-based input function for MRI. The median Pearson's correlations were: volume transfer constant K(trans) (r = 0.9), flux rate constant kep (r = 0.77), extracellular volume fraction ve (r = 0.58) and blood plasma volume fraction vp (r = 0.83). All quantitative parameters were found to be significantly different as estimated by DCE-CT and -MRI. The Γ analysis in normalized maps revealed that 45% of the voxels failed to find a voxel with the corresponding value allowing for an uncertainty of 3 mm in position and 3% in value (Γ3,3). By reducing the criteria, the Γ-failure rates were: Γ3,5 (37% failure), Γ3,10 (26% failure) and at Γ3,15 (19% failure).

CONCLUSION

Good to excellent correlations but significant bias was found between DCE-CT and -MRI. Both the Pearson's correlation and the Γ analysis proved that the spatial information was similar when analyzing the two sets of DCE data using the extended Tofts model. Improvement of input function sampling is needed to improve kinetic quantification using DCE-MRI.

Functional MRI for radiotherapy dose painting

Modern radiation therapy techniques are exceptionally flexible in the deposition of radiation dose in a target volume. Complex distributions of dose can be delivered reliably, so that the tumor is exposed to a high dose, whereas nearby healthy structures can be avoided. As a result, an increase in curative dose is no longer invariably associated with an increased level of toxicity. This modern technology can be exploited further by modulating the required dose in space so as to match the variation in radiation sensitivity in the tumor. This approach is called dose painting. For dose painting to be effective, functional imaging techniques are essential to identify regions in a tumor that require a higher dose. Several techniques are available in nuclear medicine and radiology. In recent years, there has been a considerable research effort concerning the integration of magnetic resonance imaging (MRI) into the external radiotherapy workflow motivated by the superior soft tissue contrast as compared to computed tomography. In MRI, diffusion-weighted MRI reflects the cell density of tissue and thus may indicate regions with a higher tumor load. Dynamic contrast-enhanced MRI reflects permeability of the microvasculature and blood flow, correlated to the oxygenation of the tumor. These properties have impact on its radiation sensitivity. New questions must be addressed when these techniques are applied in radiation therapy: scanning in treatment position requires alternative solutions to the standard patient setup in the choice of receive coils compared to a diagnostic department. This standard positioning also facilitates repeated imaging. The geometrical accuracy of MR images is critical for high-precision radiotherapy. In particular, when multiparametric functional data are used for dose painting, quantification of functional parameters at a high spatial resolution becomes important. In this review, we will address these issues and describe clinical developments in MRI-guided dose painting.

Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers

INTRODUCTION

Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse.

MATERIALS AND METHODS

Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K(trans) and ύ(e), were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters.

RESULTS

Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels.

CONCLUSIONS

Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control.