Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion

Target Volume Optimization for Localized Prostate Cancer

PURPOSE

To provide a comprehensive review of the means by which to optimize target volume definition for the purposes of treatment planning for patients with intact prostate cancer with a specific emphasis on focal boost volume definition.

METHODS

Here we conduct a narrative review of the available literature summarizing the current state of knowledge on optimizing target volume definition for the treatment of localized prostate cancer.

RESULTS

Historically, the treatment of prostate cancer included a uniform prescription dose administered to the entire prostate with or without coverage of all or part of the seminal vesicles. The development of prostate magnetic resonance imaging (MRI) and positron emission tomography (PET) using prostate-specific radiotracers has ushered in an era in which radiation oncologists are able to localize and focally dose-escalate high-risk volumes in the prostate gland. Recent phase 3 data has demonstrated that incorporating focal dose escalation to high-risk subvolumes of the prostate improves biochemical control without significantly increasing toxicity. Still, several fundamental questions remain regarding the optimal target volume definition and prescription strategy to implement this technique. Given the remaining uncertainty, a knowledge of the pathological correlates of radiographic findings and the anatomic patterns of tumor spread may help inform clinical judgement for the definition of clinical target volumes.

CONCLUSION

Advanced imaging has the ability to improve outcomes for patients with prostate cancer in multiple ways, including by enabling focal dose escalation to high-risk subvolumes. However, many questions remain regarding the optimal target volume definition and prescription strategy to implement this practice, and key knowledge gaps remain. A detailed understanding of the pathological correlates of radiographic findings and the patterns of local tumor spread may help inform clinical judgement for target volume definition given the current state of uncertainty.

Interactive Cascaded Network for Prostate Cancer Segmentation from Multimodality MRI with Automated Quality Assessment

The accurate segmentation of prostate cancer (PCa) from multiparametric MRI is crucial in clinical practice for guiding biopsy and treatment planning. Existing automated methods often lack the necessary accuracy and robustness in localizing PCa, whereas interactive segmentation methods, although more accurate, require user intervention on each input image, thereby limiting the cost-effectiveness of the segmentation workflow. Our innovative framework addresses the limitations of current methods by combining a coarse segmentation network, a rejection network, and an interactive deep network known as Segment Anything Model (SAM). The coarse segmentation network automatically generates initial segmentation results, which are evaluated by the rejection network to estimate their quality. Low-quality results are flagged for user interaction, with the user providing a region of interest (ROI) enclosing the lesions, whereas for high-quality results, ROIs were cropped from the automatic segmentation. Both manually and automatically defined ROIs are fed into SAM to produce the final fine segmentation. This approach significantly reduces the annotation burden and achieves substantial improvements by flagging approximately 20% of the images with the lowest quality scores for manual annotation. With only half of the images manually annotated, the final segmentation accuracy is statistically indistinguishable from that achieved using full manual annotation. Although this paper focuses on prostate lesion segmentation from multimodality MRI, the framework can be adapted to other medical image segmentation applications to improve segmentation efficiency while maintaining high accuracy standards.

Prostate cancer segmentation from MRI by a multistream fusion encoder

BACKGROUND

Targeted prostate biopsy guided by multiparametric magnetic resonance imaging (mpMRI) detects more clinically significant lesions than conventional systemic biopsy. Lesion segmentation is required for planning MRI-targeted biopsies. The requirement for integrating image features available in T2-weighted and diffusion-weighted images poses a challenge in prostate lesion segmentation from mpMRI.

PURPOSE

A flexible and efficient multistream fusion encoder is proposed in this work to facilitate the multiscale fusion of features from multiple imaging streams. A patch-based loss function is introduced to improve the accuracy in segmenting small lesions.

METHODS

The proposed multistream encoder fuses features extracted in the three imaging streams at each layer of the network, thereby allowing improved feature maps to propagate downstream and benefit segmentation performance. The fusion is achieved through a spatial attention map generated by optimally weighting the contribution of the convolution outputs from each stream. This design provides flexibility for the network to highlight image modalities according to their relative influence on the segmentation performance. The encoder also performs multiscale integration by highlighting the input feature maps (low-level features) with the spatial attention maps generated from convolution outputs (high-level features). The Dice similarity coefficient (DSC), serving as a cost function, is less sensitive to incorrect segmentation for small lesions. We address this issue by introducing a patch-based loss function that provides an average of the DSCs obtained from local image patches. This local average DSC is equally sensitive to large and small lesions, as the patch-based DSCs associated with small and large lesions have equal weights in this average DSC.

RESULTS

The framework was evaluated in 931 sets of images acquired in several clinical studies at two centers in Hong Kong and the United Kingdom. In particular, the training, validation, and test sets contain 615, 144, and 172 sets of images, respectively. The proposed framework outperformed single-stream networks and three recently proposed multistream networks, attaining F1 scores of 82.2 and 87.6% in the lesion and patient levels, respectively. The average inference time for an axial image was 11.8 ms.

CONCLUSION

The accuracy and efficiency afforded by the proposed framework would accelerate the MRI interpretation workflow of MRI-targeted biopsy and focal therapies.

Toward mechatronic MRI-guided focal laser ablation of the prostate: Robust registration for improved needle delivery

BACKGROUND

Multiparametric MRI (mpMRI) is an effective tool for detecting and staging prostate cancer (PCa), guiding interventional therapy, and monitoring PCa treatment outcomes. MRI-guided focal laser ablation (FLA) therapy is an alternative, minimally invasive treatment method to conventional therapies, which has been demonstrated to control low-grade, localized PCa while preserving patient quality of life. The therapeutic success of FLA depends on the accurate placement of needles for adequate delivery of ablative energy to the target lesion. We previously developed an MR-compatible mechatronic system for prostate FLA needle guidance and validated its performance in open-air and clinical 3T in-bore experiments using virtual targets.

PURPOSE

To develop a robust MRI-to-mechatronic system registration method and evaluate its in-bore MR-guided needle delivery accuracy in tissue-mimicking prostate phantoms.

METHODS

The improved registration multifiducial assembly houses thirty-six aqueous gadolinium-filled spheres distributed over a 7.3 × 7.3 × 5.2 cm volume. MRI-guided needle guidance accuracy was quantified in agar-based tissue-mimicking prostate phantoms on trajectories (N = 44) to virtual targets covering the mechatronic system's range of motion. 3T gradient-echo recalled (GRE) MRI images were acquired after needle insertions to each target, and the air-filled needle tracks were segmented. Needle guidance error was measured as the shortest Euclidean distance between the target point and the segmented needle trajectory, and angular error was measured as the angle between the targeted trajectory and the segmented needle trajectory. These measurements were made using both the previously designed four-sphere registration fiducial assembly on trajectories (N = 7) and compared with the improved multifiducial assembly using a Mann-Whitney U test.

RESULTS

The median needle guidance error of the system using the improved registration fiducial assembly at a depth of 10 cm was 1.02 mm with an interquartile range (IQR) of 0.42-2.94 mm. The upper limit of the one-sided 95% prediction interval of needle guidance error was 4.13 mm. The median (IQR) angular error was 0.0097 rad (0.0057-0.015 rad) with a one-sided 95% prediction interval upper limit of 0.022 rad. The median (IQR) positioning error using the previous four-sphere registration fiducial assembly was 1.87 mm (1.77-2.14 mm). This was found to be significantly different (p = 0.0012) from the median (IQR) positioning error of 0.28 mm (0.14-0.95 mm) using the new registration fiducial assembly on the same trajectories. No significant difference was detected between the medians of the angular errors (p = 0.26).

CONCLUSION

This is the first study presenting an improved registration method and validation in tissue-mimicking phantoms of our remotely actuated MR-compatible mechatronic system for delivery of prostate FLA needles. Accounting for the effects of needle deflection, the system was demonstrated to be capable of needle delivery with an error of 4.13 mm or less in 95% of cases under ideal conditions, which is a statistically significant improvement over the previous method. The system will next be validated in a clinical setting.

Gross tumor volume delineation in primary prostate cancer on 18F-PSMA-1007 PET/MRI and 68Ga-PSMA-11 PET/MRI

Background

We aimed to assess the clinical value of 18F-PSMA-1007 and 68Ga-PSMA-11 PET/MRI in the gross tumor volume (GTV) delineation of radiotherapy for prostate cancer (PCa).

Methods

Sixty-nine patients were retrospectively enrolled (57 in the 18F subgroup and 12 in the 68Ga subgroup). Three physicians delineated the GTV and tumor length by the visual method and threshold method with thresholds of 30%, 40%, 50%, and 60% SUVmax. The volume correlation and differences in GTVs were assessed. The dice similarity coefficient (DSC) was applied to estimate the spatial overlap between GTVs. For 51 patients undergoing radical prostatectomy, the tumor length (Lpath) of the maximum area was measured, and compared with the longest tumor length obtained based on the images (LMRI, LPET/MRI, LPET, LPET30%, LPET40%, LPET50%, LPET60%) to determine the best delineation method.

Results

In the 18F subgroup, (1) GTV-PET/MRI (p < 0.001) was significantly different from the reference GTV-MRI. DSC between them was > 0.7. (2) GTV-MRI (R2 = 0.462, p < 0.05) was the influencing factor of DSC. In the 68Ga subgroup, (1) GTV-PET/MRI (p < 0.05) was significantly different from the reference GTV-MRI. DSC between them was > 0.7. (2) There was a significant correlation between GTV-MRI (r = 0.580, p < 0.05) and DSC. The longest tumor length measured by PET/MRI was in good agreement with that measured by histopathological analysis in both subgroups.

Conclusion

It is feasible to visually delineate GTV on PSMA PET/MRI in PCa radiotherapy, and we emphasize the utility of PET/MRI fusion images in GTV delineation. In addition, the overlap degree was the highest between GTV-MRI and GTV-PET/MRI, and it increased with increasing volume.

Prostate cancer classification using radiomics and machine learning on mp-MRI validated using co-registered histology

BACKGROUND

Multi-parametric magnetic resonance imaging (mp-MRI) is emerging as a useful tool for prostate cancer (PCa) detection but currently has unaddressed limitations. Computer aided diagnosis (CAD) systems have been developed to address these needs, but many approaches used to generate and validate the models have inherent biases.

METHOD

All clinically significant PCa on histology was mapped to mp-MRI using a previously validated registration algorithm. Shape and size matched non-PCa regions were selected using a proposed sampling algorithm to eliminate biases towards shape and size. Further analysis was performed to assess biases regarding inter-zonal variability.

RESULTS

A 5-feature Naïve-Bayes classifier produced an area under the receiver operating characteristic curve (AUC) of 0.80 validated using leave-one-patient-out cross-validation. As mean inter-class area mismatch increased, median AUC trended towards positively biasing classifiers to producing higher AUCs. Classifiers were invariant to differences in shape between PCa and non-PCa lesions (AUC: 0.82 vs 0.82). Performance for models trained and tested only in the peripheral zone was found to be lower than in the central gland (AUC: 0.75 vs 0.95).

CONCLUSION

We developed a radiomics based machine learning system to classify PCa vs non-PCa tissue on mp-MRI validated on accurately co-registered mid-gland histology with a measured target registration error. Potential biases involved in model development were interrogated to provide considerations for future work in this area.

Imaging Biomarkers in Prostate Stereotactic Body Radiotherapy: A Review and Clinical Trial Protocol

Advances in imaging have changed prostate radiotherapy through improved biochemical control from focal boost and improved detection of recurrence. These advances are reviewed in the context of prostate stereotactic body radiation therapy (SBRT) and the ARGOS/CLIMBER trial protocol. ARGOS/CLIMBER will evaluate 1) the safety and feasibility of SBRT with focal boost guided by multiparametric MRI (mpMRI) and ¹⁸F-PSMA-1007 PET and 2) imaging and laboratory biomarkers for response to SBRT. To date, response to prostate SBRT is most commonly evaluated using the Phoenix Criteria for biochemical failure. The drawbacks of this approach include lack of lesion identification, a high false-positive rate, and delay in identifying treatment failure. Patients in ARGOS/CLIMBER will receive dynamic ¹⁸F-PSMA-1007 PET and mpMRI prior to SBRT for treatment planning and at 6 and 24 months after SBRT to assess response. Imaging findings will be correlated with prostate-specific antigen (PSA) and biopsy results, with the goal of early, non-invasive, and accurate identification of treatment failure.

Targeting prostate lesions on multiparametric MRI with HDR brachytherapy: Optimal planning margins determined using whole-mount digital histology

PURPOSE

Multiparametric magnetic resonance imaging (mpMRI) has demonstrated the ability to localize intraprostatic lesions. It is our goal to determine how to optimally target the underlying histopathological cancer within the setting of high-dose-rate brachytherapy (HDR-BT).

METHODS AND MATERIALS

Ten prostatectomy patients had pathologist-annotated mid-gland histology registered to pre-procedural mpMRI, which were interpreted by four different observers. Simulated HDR-BT plans with realistic catheter placements were generated by registering the mpMRI lesions and corresponding histology annotations to previously performed clinical HDR-BT implants. Inverse treatment planning was used to generate treatment plans that treated the entire gland to a single dose of 15 Gy, as well as focally targeted plans that aimed to escalate dose to the mpMRI lesions to 20.25 Gy. Three margins to the lesion were explored: 0 mm, 1 mm, and 2 mm. The analysis compared the dose that would have been delivered to the corresponding histologically-defined cancer with the different treatment planning techniques.

RESULTS

mpMRI-targeted plans delivered a significantly higher dose to the histologically-defined cancer (p < 0.001), in comparison to the standard treatment plans. Additionally, adding a 1 mm margin resulted in significantly higher D98, and D90 to the histologically-defined cancer in comparison to the 0 mm margin targeted plans (p = 0.019 & p = 0.0026). There was no significant difference between plans using 1 mm and 2 mm margins.

CONCLUSIONS

Adding a 1 mm margin to intraprostatic mpMRI lesions significantly increased the dose to histologically-defined cancer, in comparison applying no margin. No significant effect was observed by further expanding the margins.

Defining radio-recurrent intra-prostatic target volumes using PSMA-targeted PET/CT and multi-parametric MRI

PURPOSE

Our purpose was to evaluate intra-prostatic cancer volumes for salvage radiotherapy in men with recurrent prostate cancer confined to the prostate post-primary radiotherapy using mpMRI and 18F-DCFPyL PET/CT (PET).

METHODS

Men with biochemical failure post-primary radiotherapy were enrolled in a multi-centre trial investigating mpMRI and PET. All men with isolated intra-prostatic recurrence are included in this secondary analysis. The intra-prostatic gross tumour volume (GTV) was manually delineated on mpMRI and was also delineated on PET using three methods: 1. manually, 2. using a 30% threshold of maximum intra-prostatic standard uptake value (SUVmax), and 3. using a 67% threshold of this SUVmax. Clinical target volumes (CTV) including expansions on each GTV were generated. Conformity indices were performed between the mpMRI CTV and each PET CTV. Correlation with biopsy and clinical outcomes were performed.

RESULTS

Of the 36 men included, 30 (83%) had disease in two quadrants or less using the combination of mpMRI and PET. Mean target volume (union of CTV on mpMRI and CTV manually delineated on PET) was 12.2 cc (49% of prostate gland volume). 12/36 (33%) men had a biopsy. Per-patient sensitivity was 91% for mpMRI and 82% for PET.

CONCLUSIONS

mpMRI and PET provide complementary information for delineation of intra-prostatic recurrent disease. Union of CTV on mpMRI and PET is often less than 50% of the prostate, suggesting this imaging could help define a target for focal salvage therapy.

Prostate specific membrane antigen positron emission tomography for lesion-directed high-dose-rate brachytherapy dose escalation

•

This paper evaluated lesion-directed prostatic high dose rate brachytherapy.

•

Lesions defined by prostate specific membrane antigen positron emission tomography.

•

Dose escalation was confirmed using whole-mount digital histology.

•

Targeting lesions led to significantly higher dose to high-grade histologic cancer.

Background and purpose

Prostate specific membrane antigen positron emission tomography imaging (PSMA-PET) has demonstrated potential for intra-prostatic lesion localization. We leveraged our existing database of co-registered PSMA-PET imaging with cross sectional digitized pathology to model dose coverage of histologically-defined prostate cancer when tailoring brachytherapy dose escalation based on PSMA-PET imaging.

Materials and methods

Using a previously-developed automated approach, we created segmentation volumes delineating underlying dominant intraprostatic lesions for ten men with co-registered pathology-imaging datasets. To simulate realistic high-dose-rate brachytherapy (HDR-BT) treatments, we registered the PSMA-PET-defined segmentation volumes and underlying cancer to 3D trans-rectal ultrasound images of HDR-BT cases where 15 Gray (Gy) was delivered. We applied dose/volume optimization to focally target the dominant intraprostatic lesion identified on PSMA-PET. We then compared histopathology dose for all high-grade cancer within whole-gland treatment plans versus PSMA-PET-targeted plans. Histopathology dose was analyzed for all clinically significant cancer with a Gleason score of 7or greater.

Results

The standard whole-gland plans achieved a median [interquartile range] D98 of 15.2 [13.8–16.4] Gy to the histologically-defined cancer, while the targeted plans achieved a significantly higher D98 of 16.5 [15.0–19.0] Gy (p = 0.007).

Conclusion

This study is the first to use digital histology to confirm the effectiveness of PSMA-PET HDR-BT dose escalation using automatically generated contours. Based on the findings of this study, PSMA-PET lesion dose escalation can lead to increased dose to the ground truth histologically defined cancer.

A multiobserver study investigating the effectiveness of prostatic multiparametric magnetic resonance imaging to dose escalate corresponding histologic lesions using high-dose-rate brachytherapy

PURPOSE

Using multiparametric MRI data and the pathologic data from radical prostatectomy specimens, we simulated the treatment planning of dose-escalated high-dose-rate brachytherapy (HDR-BT) to the Multiparametric MRI dominant intraprostatic lesion (mpMRI-DIL) to compare the dose potentially delivered to the pathologically confirmed locations of the high-grade component of the cancer.

METHODS AND MATERIALS

Pathologist-annotated prostatectomy midgland histology sections from 12 patients were registered to preprostatectomy mpMRI scans that were interpreted by four radiologists. To simulate realistic HDR-BT, we registered each observer's mpMRI-DILs and corresponding histology to two transrectal ultrasound images of other HDR-BT patients with a 15-Gy whole-gland prescription. We used clinical inverse planning to escalate the mpMRI-DILs to 20.25 Gy. We compared the dose that the histopathology would have received if treated with standard treatment plans to the dose mpMRI-targeting would have achieved. The histopathology was grouped as high-grade cancer (any Gleason Grade 4 or 5) and low-grade cancer (only Gleason Grade 3).

RESULTS

212 mpMRI-targeted HDR-BT plans were analyzed. For high-grade histology, the mpMRI-targeted plans achieved significantly higher median [IQR] D98 and D90 values of 18.2 [16.7-19.5] Gy and 19.4 [17.8-20.9] Gy, respectively, in comparison with the standard plans (p = 0.01 and p = 0.003). For low-grade histology, the targeted treatment plans would have resulted in a significantly higher median D90 of 17.0 [16.1-18.4] Gy in comparison with standard plans (p = 0.015); the median D98 was not significantly higher (p = 0.2).

CONCLUSIONS

In this retrospective pilot study of 12 patients, mpMRI-based dose escalation led to increased dose to high-grade, but not low-grade, cancer. In our data set, different observers and mpMRI sequences had no substantial effect on dose to histologic cancer.

Isotropic Expansion of the Intraprostatic Gross Tumor Volume of Primary Prostate Cancer Patients Defined in MRI-A Correlation Study With Whole Mount Histopathological Information as Reference

Introduction

An accurate delineation of the intraprostatic gross tumor volume (GTV) is of importance for focal treatment in patients with primary prostate cancer (PCa). Multiparametric MRI (mpMRI) is the standard of care for lesion detection but has been shown to underestimate GTV. This study investigated how far the GTV has to be expanded in MRI in order to reach concordance with the histopathological reference and whether this strategy is practicable in clinical routine.

Patients and Methods

Twenty-two patients with planned prostatectomy and preceded 3 Tesla mpMRI were prospectively examined. After surgery, PCa contours delineated on histopathological slides (GTV-Histo) were superimposed on MRI using ex-vivo imaging as support for co-registration. According to the PI-RADSv2 classification, GTV was manually delineated in MRI (GTV-MRI) by two experts in consensus. For volumetric analysis, we compared GTV-MRI and GTV-Histo. Subsequently, we isotropically enlarged GTV-MRI in 1 mm increments within the prostate and also compared those with GTV-Histo regarding the absolute volumes. For evaluating the spatial accuracy, we considered the coverage ratio of GTV-Histo, the Sørensen–Dice coefficient (DSC), as well as the contact with the urethra.

Results

In 19 of 22 patients MRI underestimated the intraprostatic tumor volume compared to histopathological reference: median GTV-Histo (4.7 cm³, IQR: 2.5–18.8) was significantly (p<0.001) lager than median GTV-MRI (2.6 cm³, IQR: 1.2–6.9). A median expansion of 1 mm (range: 0–4 mm) adjusted the initial GTV-MRI to at least the volume of GTV-Histo (GTV^exp-MRI). Original GTV-MRI and expansion with 1, 2, 3, and 4 mm covered in median 39% (IQR: 2%–78%), 62% (10%–91%), 70% (15%–95%), 80% (21–100), 87% (25%–100%) of GTV-Histo, respectively. Best DSC (median: 0.54) between GTV-Histo and GTV-MRI was achieved by median expansion of 2 mm. The urethra was covered by initial GTVs-MRI in eight patients (36%). After applying an expansion with 2 mm the urethra was covered in one more patient by GTV-MRI.

Conclusion

Using histopathology as reference, we demonstrated that MRI underestimates intraprostatic tumor volume. A 2 mm–expansion may improve accurate GTV-delineation while respecting the balance between histological tumor coverage and overtreatment.

Histologic validation of auto-contoured dominant intraprostatic lesions on [18F] DCFPyL PSMA-PET imaging

BACKGROUND

PSMA-PET¹ has shown good concordance with histology, but there is a need to investigate the ability of PSMA-PET to delineate DIL² boundaries for guided biopsy and focal therapy planning.

OBJECTIVE

To determine threshold and margin combinations that satisfy the following criteria: ≥95% sensitivity with max specificity and ≥95% specificity with max sensitivity.

DESIGN, SETTING AND PARTICIPANTS

We registered pathologist-annotated whole-mount mid-gland prostatectomy histology sections cut in 4.4 mm intervals from 12 patients to pre-surgical PSMA-PET/MRI by mapping histology to ex-vivo imaging to in-vivo imaging. We generated PET-derived tumor volumes using boundaries defined by thresholded PET volumes from 1-100% of SUV³_max in 1% intervals. At each interval, we applied margins of 0-30 voxels in one voxel increments, giving 3000 volumes/patient.

OUTCOME MEASUREMENTS

Mean and standard deviation of sensitivity and specificity for cancer detection within the 2D oblique histologic planes that intersected with the 3D PET volume for each patient.

RESULTS AND LIMITATIONS

A threshold of 67% SUV max with an 8.4 mm margin achieved a (mean ± std.) sensitivity of 95.0 ± 7.8% and specificity of 76.4 ± 14.7%. A threshold of 81% SUV max with a 5.1 mm margin achieved sensitivity of 65.1 ± 28.4% and specificity of 95.1 ± 5.2%.

CONCLUSIONS

Preliminary evidence of thresholding and margin expansion of PSMA-PET images targeted at DILs validated with histopathology demonstrated excellent mean sensitivity and specificity in the setting of focal therapy/boosting and guided biopsy. These parameters can be used in a larger validation study supporting clinical translation.

Interim Results of a Prospective Prostate-Specific Membrane Antigen-Directed Focal Stereotactic Reirradiation Trial for Locally Recurrent Prostate Cancer

PURPOSE

To report the feasibility, toxicity, and preliminary outcomes (metabolic and biochemical) of ⁶⁸Ga-prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT)-directed focal prostate reirradiation using linear accelerator (LINAC)-based stereotactic body radiation treatment (SBRT).

METHODS AND MATERIALS

From March 2016 to March 2019, 25 patients were enrolled in a prospective single institution trial (ACTRN12617000035325). Eligibility criteria included patients with biopsy proven isolated prostate recurrence after definitive irradiation, with concordant multiparametric MRI and ⁶⁸Ga-PSMA PET/CT findings, and a prostate-specific antigen of less than 15 ng/mL at the time of recurrence. The study included a sequential dose escalation component with the first 18 patients receiving 36 Gy in 6 fractions on alternate days with subsequent patients receiving 38 Gy in 6 fractions assuming acceptable toxicity.

RESULTS

Median age was 72 years (range, 62-83) with a median time between first radiation treatment and salvage SBRT of 8.3 years (range, 4.5- 13.6). Median prostate-specific antigen at reirradiation was 4.1 (range, 1.1-16.6). The median follow-up was 25 months (range, 13-46). Acute grade 1 and 2 genitourinary (GU) toxicity occurred in 6 (24%) and 1 (4%) men, respectively. Acute grade 1 gastrointestinal (GI) toxicity occurred in 8% with one acute grade 3 GI toxicity (4%) due to a rectal ulcer overlying the hydrogel. Late grade 1 and 2 GU toxicity occurred in 28% and 4%. Late grade 1 GI toxicity occurred in 8% with no grade 2 or greater toxicity. Twenty-four patients have undergone per-protocol 12-month ⁶⁸Ga-PSMA PET/CT, of which 23 (92%) demonstrated a complete metabolic response. Biochemical freedom from failure was 80% at 2 years with 3 out of 4 of the biochemical failures exhibiting recurrent local disease.

CONCLUSIONS

PSMA-directed salvage focal reirradiation to the prostate using linear accelerator-based SBRT is feasible and safe. Toxicity was low, with very favorable short term local and biochemical control in a carefully selected cohort of patients.

Manual prostate cancer segmentation in MRI: interreader agreement and volumetric correlation with transperineal template core needle biopsy

OBJECTIVES

To assess interreader agreement of manual prostate cancer lesion segmentation on multiparametric MR images (mpMRI). The secondary aim was to compare tumor volume estimates between MRI segmentation and transperineal template saturation core needle biopsy (TTSB).

METHODS

We retrospectively reviewed patients who had undergone mpMRI of the prostate at our institution and who had received TTSB within 190 days of the examination. Seventy-eight cancer lesions with Gleason score of at least 3 + 4 = 7 were manually segmented in T2-weighted images by 3 radiologists and 1 medical student. Twenty lesions were also segmented in apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) series. First, 20 volumetric similarity scores were computed to quantify interreader agreement. Second, manually segmented cancer lesion volumes were compared with TTSB-derived estimates by Bland-Altman analysis and Wilcoxon testing.

RESULTS

Interreader agreement across all readers was only moderate with mean T2 Dice score of 0.57 (95%CI 0.39-0.70), volumetric similarity coefficient of 0.74 (0.48-0.89), and Hausdorff distance of 5.23 mm (3.17-9.32 mm). Discrepancy of volume estimate between MRI and TTSB was increasing with tumor size. Discrepancy was significantly different between tumors with a Gleason score 3 + 4 vs. higher grade tumors (0.66 ml vs. 0.78 ml; p = 0.007). There were no significant differences between T2, ADC, and DCE segmentations.

CONCLUSIONS

We found at best moderate interreader agreement of manual prostate cancer segmentation in mpMRI. Additionally, our study suggests a systematic discrepancy between the tumor volume estimate by MRI segmentation and TTSB core length, especially for large and high-grade tumors.

KEY POINTS

• Manual prostate cancer segmentation in mpMRI shows moderate interreader agreement. • There are no significant differences between T2, ADC, and DCE segmentation agreements. • There is a systematic difference between volume estimates derived from biopsy and MRI.

Dosimetric Evaluation of PSMA PET-Delineated Dominant Intraprostatic Lesion Simultaneous Infield Boosts

PURPOSE

Prostate cancer is multifocal. However, there often exists a single dominant focus in the gland responsible for driving the biology of the disease. Dose escalation to the dominant lesion is a proposed strategy to increase tumor control. We applied radiobiological modeling to evaluate the dosimetric feasibility and benefit of dominant intraprostatic lesion simultaneous in-field boosts (DIL-SIB) to the gross tumor volume (GTV), defined using a novel molecular positron emission tomography (PET) probe (18F-DCFPyL) directed against prostate specific membrane antigen (PSMA).

METHODS AND MATERIALS

Patients with clinically localized, biopsy-proven prostate cancer underwent preoperative [18F]-DCFPyL PET/computed tomography (CT). DIL-SIB plans were generated by importing the PET/CT into the RayStation treatment planning system. GTV-PET for the DIL-SIB was defined by the highest %SUVmax (percentage of maximum standardized uptake value) that generated a biologically plausible volume. Volumetric arc-based plans incorporating prostate plus DIL-SIB treatment were generated. Tumor control probability (TCP) and normal tissue complication probability (NTCP) with fractionation schemes and boost doses specified in the FLAME (Investigate the Benefit of a Focal Lesion Ablative Microboost in Prostate Cancer; NCT01168479), PROFIT (Prostate Fractionated Irradiation Trial; NCT00304759), PACE (Prostate Advances in Comparative Evidence; NCT01584258), and hypoFLAME (Hypofractionated Focal Lesion Ablative Microboost in prostatE Cancer 2.0; NCT02853110) protocols were compared.

RESULTS

Comparative DIL-SIB plans for 6 men were generated from preoperative [18F]-DCFPyL PET/CT. Median boost GTV volume was 1.015 cm3 (0.42-1.83 cm3). Median minimum (D99%) DIL-SIB dose for F35BS, F20BS, F5BS, and F5BSH were 97.3 Gy, 80.8 Gy, 46.5 Gy, and 51.5Gy. TCP within the GTV ranged from 84% to 88% for the standard plan and 95% to 96% for the DIL-SIB plans. Within the rest of the prostate, TCP ranged from 89% to 91% for the standard plans and 90% to 92% for the DIL-SIB plans. NTCP for the rectum NTCP was similar for the DIL-SIB plans (0.3%-2.7%) compared with standard plans (0.7%-2.6%). Overall, DIL-SIB plans yielded higher uncomplicated TCP (NTCP, 90%-94%) versus standard plans (NTCP, 83%-85%).

CONCLUSIONS

PSMA PET provides a novel approach to define GTV for SIB-DIL dose escalation. Work is ongoing to validate PSMA PET-delineated GTV through correlation to coregistered postprostatectomy digitized histopathology.

Evaluation of tumor coverage after MR-guided prostate focal laser ablation therapy

PURPOSE

Prostate cancer is the most common noncutaneous cancer among men in the USA. Focal laser thermal ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. In this study, we evaluated the location of ablation zones relative to targeted lesions in 23 patients who underwent FLA therapy in a phase II trial. The ablation zone margins and unablated tumor volume were measured to determine whether complete coverage of each tumor was achieved, which would be considered a clinically successful ablation.

METHODS

Preoperative mpMRI was acquired for each patient 2-3 months preceding the procedure and the prostate and lesion(s) were manually contoured on 3 T T2-weighted axial images. The prostate and ablation zone(s) were also manually contoured on postablation 1.5 T T1-weighted contrast-enhanced axial images acquired immediately after the procedure intraoperatively. The lesion surface was nonrigidly registered to the postablation image using an initial affine registration followed by nonrigid thin-plate spline registration of the prostate surfaces. The margins between the registered lesion and ablation zone were calculated using a uniform spherical distribution of rays, and the volume of intersection was also calculated. Each prostate was contoured five times to determine the segmentation variability and its effect on intersection of the lesion and ablation zone.

RESULTS

Our study showed that the boundaries of the segmented tumor and ablation zone were close. Of the 23 lesions that were analyzed, 11 were completely covered by the ablation zone and 12 were partially covered. A shift of 1.0, 2.0, and 2.6 mm would result in 19, 21, and all tumors completely covered by the ablation zone, respectively. The median unablated tumor volume across all tumors was 0.1  mm 3 with an IQR of 3.7  mm 3 , which was 0.2% of the median tumor volume (46.5  mm 3 with an IQR of 46.3  mm 3 ). The median extension of the tumors beyond the ablation zone, in cases which were partially ablated, was 0.9 mm (IQR of 1.3 mm), with the furthest tumor extending 2.6 mm.

CONCLUSION

In all cases, the boundary of the tumor was close to the boundary of the ablation zone, and in some cases, the boundary of the ablation zone did not completely enclose the tumor. Our results suggest that some of the ablations were not clinically successful and that there is a need for more accurate needle tracking and guidance methods. Limitations of the study include errors in the registration and segmentation methods used as well as different voxel sizes and contrast between the registered T2 and T1 MRI sequences and asymmetric swelling of the prostate postprocedurally.

Accuracy Validation of an Automated Method for Prostate Segmentation in Magnetic Resonance Imaging

Three dimensional (3D) manual segmentation of the prostate on magnetic resonance imaging (MRI) is a laborious and time-consuming task that is subject to inter-observer variability. In this study, we developed a fully automatic segmentation algorithm for T2-weighted endorectal prostate MRI and evaluated its accuracy within different regions of interest using a set of complementary error metrics. Our dataset contained 42 T2-weighted endorectal MRI from prostate cancer patients. The prostate was manually segmented by one observer on all of the images and by two other observers on a subset of 10 images. The algorithm first coarsely localizes the prostate in the image using a template matching technique. Then, it defines the prostate surface using learned shape and appearance information from a set of training images. To evaluate the algorithm, we assessed the error metric values in the context of measured inter-observer variability and compared performance to that of our previously published semi-automatic approach. The automatic algorithm needed an average execution time of ∼60 s to segment the prostate in 3D. When compared to a single-observer reference standard, the automatic algorithm has an average mean absolute distance of 2.8 mm, Dice similarity coefficient of 82%, recall of 82%, precision of 84%, and volume difference of 0.5 cm³ in the mid-gland. Concordant with other studies, accuracy was highest in the mid-gland and lower in the apex and base. Loss of accuracy with respect to the semi-automatic algorithm was less than the measured inter-observer variability in manual segmentation for the same task.

[PI-RADS 2.0 for Prostate MRI]

The PI-RADS 2.0 classification was established by an international collaboration of the European Society of Urogenital Radiology (ESUR), the American College of Radiology (ACR), and AdMetech Foundation to globally standardize the acquisition and interpretation of multiparametric prostate magnetic resonance imaging (MRI). The PI-RADS 2.0 aims to improve the detection, localization, staging and risk stratification of patients with suspected or histologically confirmed prostate cancer. Suspicious areas on T2-weighted (T2w) MRI, diffusion-weighted MRI (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) were assessed for the presence of a clinically significant prostate cancer with scale from 1 to 5 with 5 being most likely to represent clinically significant prostate cancer. The dominant sequence to detect significant prostate cancer in the peripheral zone is DWI and for the transition zone T2w images. For the local staging of prostate cancer criteria for the assessment of an extracapsular growth were formulated.

A comparison of prostate tumor targeting strategies using magnetic resonance imaging-targeted, transrectal ultrasound-guided fusion biopsy

PURPOSE

Magnetic resonance imaging (MRI)-targeted, three-dimensional (3D) transrectal ultrasound (TRUS)-guided prostate biopsy aims to reduce the 21-47% false-negative rate of clinical two-dimensional (2D) TRUS-guided systematic biopsy, but continues to yield false-negative results. This may be improved via needle target optimization, accounting for guidance system errors and image registration errors. As an initial step toward the goal of optimized prostate biopsy targeting, we investigated how needle delivery error impacts tumor sampling probability for two targeting strategies.

METHODS

We obtained MRI and 3D TRUS images from 49 patients. A radiologist and radiology resident assessed these MR images and contoured 81 suspicious regions, yielding tumor surfaces that were registered to 3D TRUS. The biopsy system's root-mean-squared needle delivery error (RMSE) and systematic error were modeled using an isotropic 3D Gaussian distribution. We investigated two different prostate tumor-targeting strategies using (a) the tumor's centroid and (b) a ring in the lateral-elevational plane. For each simulation, targets were spaced at equal arc lengths on a ring with radius equal to the systematic error magnitude. A total of 1000 biopsy simulations were conducted for each tumor, with RMSE and systematic error magnitudes ranging from 1 to 6 mm. The difference in median tumor sampling probability and probability of obtaining a 50% core involvement was determined for ring vs centroid targeting.

RESULTS

Our simulation results indicate that ring targeting outperformed centroid targeting in situations where systematic error exceeds RMSE. In these instances, we observed statistically significant differences showing 1-32% improvement in sampling probability due to ring targeting. Likewise, we observed statistically significant differences showing 1-39% improvement in 50% core involvement probability due to ring targeting.

CONCLUSIONS

Our results suggest that the optimal targeting scheme for prostate biopsy depends on the relative levels of systematic and random errors in the system. Where systematic error dominates, a ring-targeting scheme may yield improved probability of tumor sampling. The findings presented in this paper may be used to aid in target selection strategies for clinicians performing targeted prostate biopsies on any MRI targeted, 3D TRUS-guided biopsy system and could support earlier diagnosis of prostate cancer while it remains localized to the gland and curable.

Designing image segmentation studies: Statistical power, sample size and reference standard quality

Segmentation algorithms are typically evaluated by comparison to an accepted reference standard. The cost of generating accurate reference standards for medical image segmentation can be substantial. Since the study cost and the likelihood of detecting a clinically meaningful difference in accuracy both depend on the size and on the quality of the study reference standard, balancing these trade-offs supports the efficient use of research resources. In this work, we derive a statistical power calculation that enables researchers to estimate the appropriate sample size to detect clinically meaningful differences in segmentation accuracy (i.e. the proportion of voxels matching the reference standard) between two algorithms. Furthermore, we derive a formula to relate reference standard errors to their effect on the sample sizes of studies using lower-quality (but potentially more affordable and practically available) reference standards. The accuracy of the derived sample size formula was estimated through Monte Carlo simulation, demonstrating, with 95% confidence, a predicted statistical power within 4% of simulated values across a range of model parameters. This corresponds to sample size errors of less than 4 subjects and errors in the detectable accuracy difference less than 0.6%. The applicability of the formula to real-world data was assessed using bootstrap resampling simulations for pairs of algorithms from the PROMISE12 prostate MR segmentation challenge data set. The model predicted the simulated power for the majority of algorithm pairs within 4% for simulated experiments using a high-quality reference standard and within 6% for simulated experiments using a low-quality reference standard. A case study, also based on the PROMISE12 data, illustrates using the formulae to evaluate whether to use a lower-quality reference standard in a prostate segmentation study.

Ultrasound Elastography of the Prostate Using an Unconstrained Modulus Reconstruction Technique: A Pilot Clinical Study

A novel full-inversion-based technique for quantitative ultrasound elastography was investigated in a pilot clinical study on five patients for non-invasive detection and localization of prostate cancer and quantification of its extent. Conventional-frequency ultrasound images and radiofrequency (RF) data (~5 MHz) were collected during mechanical stimulation of the prostate using a transrectal ultrasound probe. Pre and post-compression RF data were used to construct the strain images. The Young's modulus (YM) images were subsequently reconstructed using the derived strain images and the stress distribution estimated iteratively using finite element (FE) analysis. Tumor regions determined based on the reconstructed YM images were compared to whole-mount histopathology images of radical prostatectomy specimens. Results indicated that tumors were significantly stiffer than the surrounding tissue, demonstrating a relative YM of 2.5 ± 0.8 compared to normal prostate tissue. The YM images had a good agreement with the histopathology images in terms of tumor location within the prostate. On average, 76% ± 28% of tumor regions detected based on the proposed method were inside respective tumor areas identified in the histopathology images. Results of a linear regression analysis demonstrated a good correlation between the disease extents estimated using the reconstructed YM images and those determined from whole-mount histopathology images (r² = 0.71). This pilot study demonstrates that the proposed method has a good potential for detection, localization and quantification of prostate cancer. The method can potentially be used for prostate needle biopsy guidance with the aim of decreasing the number of needle biopsies. The proposed technique utilizes conventional ultrasound imaging system only while no additional hardware attachment is required for mechanical stimulation or data acquisition. Therefore, the technique may be regarded as a non-invasive, low cost and potentially widely-available clinical tool for prostate cancer diagnosis.