How accurately can multiparametric magnetic resonance imaging measure the tumour volume of a prostate cancer? Results of a systematic review

Can contralateral lymph-node metastases be ruled out in prostate cancer patients with only unilaterally positive prostate biopsy?

PURPOSE

Our study evaluated the diagnostic benefits of bilateral pelvic lymphadenectomy in prostate cancer patients with unilaterally positive prostate biopsy.

METHODS

Our retrospective analysis included clinical, surgical, and histopathological data of 440 prostate cancer patients treated with radical prostatectomy and bilateral sentinel-guided and risk-adapted complementary extended pelvic lymphadenectomy at our hospital between 2015 and 2022. We performed multiparametric logistic regression analysis to identify the most relevant predictive factors for detecting lymph-node metastasis in this group of patients.

RESULTS

Overall, 373 patients (85%) had histopathologically bilateral tumours and 45 (10%) pN1 status, of which 22 (49%) also had lymph-node metastasis contralateral to the side of the positive prostate biopsy. In two patients with confirmed unilateral disease in prostatectomy specimens, bilateral lymph-node metastases were observed. Eight pN1 patients would have been missed by unilateral pelvic lymphadenectomy, resulting in a false-negative rate of 18%, 82% sensitivity, and 98% accuracy. Clinical tumour category, International Society of Urological Pathology grade, and percentage of prostate biopsy cores that are positive, as well as number of dissected lymph nodes contralateral to positive prostate biopsy, were determined as the most relevant predictive factors for detecting lymph-node metastasis. Our analysis was limited by its retrospective nature as well as by the fact that 80% of the patients did not receive MRI-targeted biopsy.

CONCLUSION

Our study highlights the diagnostic value of bilateral pelvic lymphadenectomy and the need for careful planning in surgery for prostate cancer patients with unilaterally positive prostate biopsy.

Prediction and Mapping of Intraprostatic Tumor Extent with Artificial Intelligence

Background

Magnetic resonance imaging (MRI) underestimation of prostate cancer extent complicates the definition of focal treatment margins.

Objective

To validate focal treatment margins produced by an artificial intelligence (AI) model.

Design setting and participants

Testing was conducted retrospectively in an independent dataset of 50 consecutive patients who had radical prostatectomy for intermediate-risk cancer. An AI deep learning model incorporated multimodal imaging and biopsy data to produce three-dimensional cancer estimation maps and margins. AI margins were compared with conventional MRI regions of interest (ROIs), 10-mm margins around ROIs, and hemigland margins. The AI model also furnished predictions of negative surgical margin probability, which were assessed for accuracy.

Outcome measurements and statistical analysis

Comparing AI with conventional margins, sensitivity was evaluated using Wilcoxon signed-rank tests and negative margin rates using chi-square tests. Predicted versus observed negative margin probability was assessed using linear regression. Clinically significant prostate cancer (International Society of Urological Pathology grade ≥2) delineated on whole-mount histopathology served as ground truth.

Results and limitations

The mean sensitivity for cancer-bearing voxels was higher for AI margins (97%) than for conventional ROIs (37%, p < 0.001), 10-mm ROI margins (93%, p = 0.24), and hemigland margins (94%, p < 0.001). For index lesions, AI margins were more often negative (90%) than conventional ROIs (0%, p < 0.001), 10-mm ROI margins (82%, p = 0.24), and hemigland margins (66%, p = 0.004). Predicted and observed negative margin probabilities were strongly correlated (R2 = 0.98, median error = 4%). Limitations include a validation dataset derived from a single institution's prostatectomy population.

Conclusions

The AI model was accurate and effective in an independent test set. This approach could improve and standardize treatment margin definition, potentially reducing cancer recurrence rates. Furthermore, an accurate assessment of negative margin probability could facilitate informed decision-making for patients and physicians.

Patient summary

Artificial intelligence was used to predict the extent of tumors in surgically removed prostate specimens. It predicted tumor margins more accurately than conventional methods.

Comparison of prostate volume measured by transabdominal ultrasound and MRI with the radical prostatectomy specimen volume: a retrospective observational study

BACKGROUND

Few studies have compared the use of transabdominal ultrasound (TAUS) and magnetic resonance imaging (MRI) to measure prostate volume (PV). In this study, we evaluate the accuracy and reliability of PV measured by TAUS and MRI.

METHODS

A total of 106 patients who underwent TAUS and MRI prior to radical prostatectomy were retrospectively analyzed. The TAUS-based and MRI-based PV were calculated using the ellipsoid formula. The specimen volume measured by the water-displacement method was used as a reference standard. Correlation analysis and intraclass correlation coefficients (ICC) were performed to compare different measurement methods and Bland Altman plots were drawn to assess the agreement.

RESULTS

There was a high degree of correlation and agreement between the specimen volume and PV measured with TAUS (r = 0.838, p < 0.01; ICC = 0.83) and MRI (r = 0.914, p < 0.01; ICC = 0.90). TAUS overestimated specimen volume by 2.4ml, but the difference was independent of specimen volume (p = 0.19). MRI underestimated specimen volume by 1.7ml, the direction and magnitude of the difference varied with specimen volume (p < 0.01). The percentage error of PV measured by TAUS and MRI was within ± 20% in 65/106(61%) and 87/106(82%), respectively. In patients with PV greater than 50 ml, MRI volume still correlated strongly with specimen volume (r = 0.837, p < 0.01), while TAUS volume showed only moderate correlation with specimen (r = 0.665, p < 0.01) or MRI volume (r = 0.678, p < 0.01).

CONCLUSIONS

This study demonstrated that PV measured by MRI and TAUS is highly correlated and reliable with the specimen volume. MRI might be a more appropriate choice for measuring the large prostate.

MR Imaging in Real Time Guiding of Therapies in Prostate Cancer

Magnetic resonance imaging (MRI)-guided therapy for prostate cancer (PCa) aims to reduce the treatment-associated comorbidity of existing radical treatment, including radical prostatectomy and radiotherapy. Although active surveillance has been used as a conservative method to reduce overtreatment, there is a growing demand for less morbidity and personalized (focal) treatment. The development of multiparametric MRI was of real importance in improving the detection, localization and staging of PCa. Moreover, MRI has been useful for lesion targeting within the prostate, as it is used in the guidance of prostate biopsies, by means of cognitive registration, MRI-ultrasound fusion guidance or direct in-bore MRI-guidance. With regard to PCa therapies, MRI is used for precise probe placement into the lesion and to accurately monitor the treatment in real-time. Moreover, advances in MR-compatible thermal ablation allow for noninvasive real-time temperature mapping during treatment. In this review, we present an overview of the current status of MRI-guided therapies in PCa, focusing on cryoablation, focal laser ablation, high intensity focused ultrasound and transurethral ultrasound ablation. We explain the important role of MRI in the evaluation of the completeness of the ablation and during follow-up. Finally, we will discuss the challenges and future development inherent to these new technologies.

Association Between Multiparametric Magnetic Resonance Imaging of the Prostate and Oncological Outcomes after Primary Treatment for Prostate Cancer: A Systematic Review and Meta-analysis

CONTEXT

The diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) diagnosis has been extensively explored. Little is known about the prognostic value of mpMRI suspicion scores and other quantitative mpMRI information.

OBJECTIVE

To systematically review the current literature assessing the relationship between pretreatment mpMRI and oncological outcomes after primary treatment for PCa to assess the role of mpMRI as a prognostic tool.

EVIDENCE ACQUISITION

A computerized bibliographic search of MEDLINE/PubMed, EMBASE, Scopus, and the Cochrane Library CENTRAL databases was performed for all studies assessing the relationship between mpMRI and oncological outcomes after primary treatment for PCa. The review protocol is registered in the PROSPERO database (CRD42020209899).

EVIDENCE SYNTHESIS

A total of six studies were included. Reliable evidence is still limited in this field. The Prostate Imaging-Reporting and Data System (PI-RADS) score was an independent predictor of biochemical recurrence (BCR) after radical prostatectomy (RP) in the majority of the studies included. The tumor volume at mpMRI was not significantly associated with BCR after RP for PCa. Data on disease progression and PCa-specific mortality are limited. Heterogeneity among the studies was substantial.

CONCLUSIONS

The review shows that PI-RADS scores provide information on the future likelihood of cancer recurrence or progression, at least for men undergoing RP. We are of the view that this information should be taken into account to identify men at higher risk of unfavorable outcomes.

PATIENT SUMMARY

A higher Prostate Imaging-Reporting and Data System score for magnetic resonance imaging of the prostate seems to be positively associated with oncological failure in prostate cancer and should be incorporated into future risk models.