Multiparametric magnetic resonance imaging: Overview of the technique, clinical applications in prostate biopsy and future directions

Utility of quantitative measurement of T2 using restriction spectrum imaging for detection of clinically significant prostate cancer

The Restriction Spectrum Imaging restriction score (RSIrs) has been shown to improve the accuracy for diagnosis of clinically significant prostate cancer (csPCa) compared to standard DWI. Both diffusion and T2 properties of prostate tissue contribute to the signal measured in DWI, and studies have demonstrated that each may be valuable for distinguishing csPCa from benign tissue. The purpose of this retrospective study was to (1) determine whether prostate T2 varies across RSI compartments and in the presence of csPCa, and (2) evaluate whether csPCa detection with RSIrs is improved by acquiring multiple scans at different TEs to measure compartmental T2 (cT2). Data includes two cohorts scanned for csPCa with 3T multi-b-value diffusion-weighted sequences acquired at multiple TEs. cT2 values were computed from multi-TE RSI data and compared by compartment. CsPCa detection was compared between RSIrs and a logistic regression model (LRM) to predict the probability of csPCa using cT2 in combination with RSI measurements. Two-sample t-tests (α = 0.05) and the area under the receiver operating characteristic curve (AUC) were used for the statistical analyses. In both cohorts, T2 was different (p < 0.05) across the four RSI compartments (C1, C2, C3, C4). Voxel-level, cohort 1: T2 was different in csPCa for C1, C2, C3 (p < 0.001). Patient-level, cohort 1: T2 was different in csPCa patients in C3 (p = 0.02); cohort 2: T2 differed in csPCa patients in C1 (p = 0.01), C3 (p = 0.01) and C4 (p < 0.01). Voxel-level csPCa detection: cT2 did not improve discrimination over RSIrs alone (p = 0.9). Patient-level: RSIrs and the LRM performed better than diffusion alone (p < 0.001), but the difference in AUCs between RSIrs and the LRM was not significantly different (p = 0.54). In conclusion, significant differences in cT2 were observed between normal and cancerous prostatic tissue. With our data, however, consideration of cT2 in addition to diffusion did not significantly improve cancer detection performance.

Advanced Imaging for Localized Prostate Cancer

BACKGROUND/OBJECTIVES

Prostate cancer is a prevalent malignancy often presenting without early symptoms. Advanced imaging technologies have revolutionized its diagnosis and management. This review discusses the principles, benefits, and clinical applications of multiparametric magnetic resonance imaging (mpMRI), micro-ultrasound (microUS), and prostate-specific membrane antigen positron emission tomography-computed tomography (PSMA PET/CT) in localized prostate cancer.

METHODS

We conducted a comprehensive literature review of recent studies and guidelines on mpMRI, microUS, and PSMA PET/CT in prostate cancer diagnosis, focusing on their applications in biopsy-naïve patients, those with previous negative biopsies, and patients under active surveillance.

RESULTS

MpMRI has demonstrated high sensitivity and negative predictive value in detecting clinically significant prostate cancer (csPCa). MicroUS, a newer technology, has shown promising results in early studies, with sensitivity and specificity comparable to mpMRI. PSMA PET/CT has emerged as a highly sensitive and specific imaging modality, particularly valuable for staging and detecting metastatic disease. All three technologies have been incorporated into urologic practice for prostate cancer diagnosis and management, with each offering unique advantages in different clinical scenarios.

CONCLUSIONS

Advanced imaging techniques, including mpMRI, microUS, and PSMA PET/CT, have significantly improved the accuracy of prostate cancer diagnosis, staging, and management. These technologies enable more precise targeting of suspicious lesions during biopsy and therapy planning. However, further research, especially randomized controlled trials, is needed to fully establish the optimal use and inclusion of these imaging modalities in various stages of prostate cancer care.

Men's sociotechnical imaginaries of artificial intelligence for prostate cancer diagnostics - A focus group study

Artificial intelligence (AI) is increasingly used for diagnostic purposes in cancer care. Prostate cancer is one of the most prevalent cancers affecting men worldwide, but current diagnostic approaches have limitations in terms of specificity and sensitivity. Using AI to interpret MR images in prostate cancer diagnostics shows promising results, but raises questions about implementation, user acceptance, trust, and doctor-patient communication. Drawing on approaches from the sociology of expectations and theories about sociotechnical imaginaries, we explore men's expectations of artificial intelligence for prostate cancer diagnostics. We conducted ten focus groups with 48 men aged 54-85 in Norway with various experiences of prostate cancer diagnostics. Five groups of men had been treated for prostate cancer, one group was on active surveillance, two groups had been through prostate cancer diagnostics without having a diagnosis, and two groups of men had no experience with prostate cancer diagnostics or treatment. Data was subject to reflexive thematic analysis. Our analysis suggests that men's expectations of AI for prostate cancer diagnostics come from two perspectives: Technology-centered expectations that build on their conceptions of AI's form and agency, and human-centered expectations of AI that build on their perceptions of patient-professional relationships and decision-making processes. These two perspectives are intertwined in three imaginaries of AI: The tool imaginary, the advanced machine imaginary, and the intelligence imaginary - each carrying distinct expectations and ideas of technologies and humans' role in decision-making processes. These expectations are multifaceted and simultaneously optimistic and pessimistic; while AI is expected to improve the accuracy of cancer diagnoses and facilitate more personalized medicine, AI is also expected to threaten interpersonal and communicational relationships between patients and healthcare professionals, and the maintenance of trust in these relationships. This emphasizes how AI cannot be implemented without caution about maintaining human healthcare relationships.

Diagnostic Accuracy of a Combination of Preoperative 68-Ga Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography and Multiparametric Magnetic Resonance Imaging in Localized Prostate Cancer

INTRODUCTION

Prostate cancer (PCa) is a common and leading course of cancer-related death in men. Although there are studies on multiparametric magnetic resonance imaging (MpMRI) with good diagnostic results in detecting clinically significant PCa, new methods have been investigated due to the low positive predictive values. In this context, prostate-specific membrane antigen positron emission tomography (PSMA PET) emerges as an alternative imaging method to MpMRI. This study aimed to compare 68Ga PSMA I&T-PET/CT and MpMRI in determining tumor location.

METHODS

Preoperative MpMRI and 68Ga PSMA I&T-PET/CT scans and pathology specimens of patients who underwent radical prostatectomy for PCa at our clinic between 2018 and 2021 were retrospectively evaluated. PSMA I&T-PET/CT, MpMRI, combined imaging were compared for tumor localization according to histopathological data.

RESULTS

In terms of tumor localization, MpMRI demonstrated overall accuracy rates of 75.9% (p kappa [κ] 0.0001* [0.525]). 68Ga PSMA I&T-PET/CT showed 71.5% (p κ 0.0001* [0.438]). For the combined imaging approach, the overall accuracy rate was calculated as 79.2% (p κ 0.0001* [0.576]). Additionally, high diagnostic accuracy was achieved for the combined imaging approach, particularly in the intermediate ISUP group. Moreover, SUVmax was calculated as 6.37.

CONCLUSION

The combined use of 68Ga PSMA I&T-PET/CT and MpMRI has high diagnostic rates. However, the high cost is a significant disadvantage that limits their routine combined use.

A current role status of micro-ultrasound imaging in prostate cancer diagnosis

 Recently diagnostic field in medicine was enriched by advances in ultrasonography (US) technology, which led to establishment of novel modalities, one of which is micro-ultrasound. Results demonstrated by early studies have been promising, simultaneously rising a question if those new modalities could become an alternative in diagnosis of prostatic carcinoma (PCa). To answer this question, several studies have been conducted where micro-ultrasound have been compared to standard diagnostic tools, such as conventional TRUS or mpMRI. Nevertheless, new technology presents with some limitations, which include inconsistent results, necessity for specialized equipment, need of training for investigators to understand the findings, and external validation. In this publication, we have identified studies that provided evaluation of the accuracy and efficiency of the micro-ultrasound technology. Additionally, analysis of the results provided a better understanding of the novel imaging tool when compared standard modalities in diagnosis of PCa. Increasing number of studies demonstrated that micro-ultrasound carries high detection rate of PCa and clinically significant prostatic cancer (csPCa), suggesting a similar performance to mpMRI and even showing superiority over conventional TRUS. Recent studies have also showed that micro-ultrasound takes active role in improving the detection of csPCa and guidance for prostate biopsy (PBx) as well as further treatment. Moreover, certain practical aspects such as lower costs, decreased waiting time, real-time imaging and application of the imaging tool for patients that are not suitable for mpMRI (contrast allergy, prosthetics etc.) are significant advantages. Analysis of the results still does not provide clear answer whether micro-ultrasound outperforms mpMRI. Further studies are necessary in order to completely understand the potential of this new technology.

A radiomics-incorporated deep ensemble learning model for multi-parametric MRI-based glioma segmentation

Objective.To develop a deep ensemble learning (DEL) model with radiomics spatial encoding execution for improved glioma segmentation accuracy using multi-parametric magnetic resonance imaging (mp-MRI).Approach.This model was developed using 369 glioma patients with a four-modality mp-MRI protocol: T1, contrast-enhanced T1 (T1-Ce), T2, and FLAIR. In each modality volume, a 3D sliding kernel was implemented across the brain to capture image heterogeneity: 56 radiomic features were extracted within the kernel, resulting in a fourth-order tensor. Each radiomic feature can then be encoded as a 3D image volume, namely a radiomic feature map (RFM). For each patient, all RFMs extracted from all four modalities were processed using principal component analysis for dimension reduction, and the first four principal components (PCs) were selected. Next, a DEL model comprised of four U-Net sub-models was trained for the segmentation of a region-of-interest: each sub-model utilizes the mp-MRI and one of the four PCs as a five-channel input for 2D execution. Last, four softmax probability results given by the DEL model were superimposed and binarized using Otsu's method as the segmentation results. Three DEL models were trained to segment the enhancing tumor (ET), tumor core (TC), and whole tumor (WT), respectively. The segmentation results given by the proposed ensemble were compared to the mp-MRI-only U-Net results.Main Results.All three radiomics-incorporated DEL models were successfully implemented: compared to the mp-MRI-only U-net results, the dice coefficients of ET (0.777 → 0.817), TC (0.742 → 0.757), and WT (0.823 → 0.854) demonstrated improvement. The accuracy, sensitivity, and specificity results demonstrated similar patterns.Significance.The adopted radiomics spatial encoding execution enriches the image heterogeneity information that leads to the successful demonstration of the proposed DEL model, which offers a new tool for mp-MRI-based medical image segmentation.

MRI-guided thoraco-abdominal percutaneous needle biopsy: our initial experience

OBJECTIVE

The aim of this study is to describe the technique and to report early results of thoraco-abdominal biopsies in the Interventional Magnetic Resonance Imaging Suite (IMRIS).

MATERIALS AND METHODS

We prospectively evaluated patients with indications for MRI-guided biopsy between January 2021 and May 2022. Exclusion criteria were indication for US-/CT-guided biopsy, contraindication to percutaneous biopsy, inability to lie flat for at least 30 min, claustrophobic, severe obesity, or non-MRI compatible devices. Biopsies were performed by 3 interventional radiologists, with at least 8 years of experience in oncological interventional radiology. Epidemiological, clinical, procedural, and histopathological data were retrospectively collected.

RESULTS

From an initial population of 117 patients, 57 patients (32 male, mean age 64 ± 8 y) were finally enrolled. All 57 patients suspected thoraco-abdominal malignant lesions finally underwent MRI-guided percutaneous biopsy. The mean duration of the entire procedure was 37 min (range 28-65 min); the mean duration of the total needle-in-patient time was 10 min (range 6-19 min). Technical and clinical success were obtained for all the biopsies performed. Malignancy was demonstrated in 47/57 (82%) cases and benignancy in the remaining 10/57 (18%) cases. No major complications were detected after the biopsies; two minor compliances (severe pain) occurred and were managed conservatively.

CONCLUSION

Our initial experience demonstrated the technical feasibility and the accuracy of MRI-guided biopsies of thoraco-abdominal masses. The reported data associated with the best comfort for the patient and for the operator make the use of MRI a valid alternative to other methods, especially in lesions that are difficult to approach via US or CT.

CLINICAL RELEVANCE STATEMENT

Interventional MRI is one of the most important innovations available for interventional radiologists. This method will broaden the diagnostic and therapeutic possibilities, allowing treatment of lesions up to now not approachable percutaneously. For this, it is necessary to start publishing the data of the few groups that are developing the method.

KEY POINTS

• To evaluate the use of MRI as a guide for percutaneous biopsies of various districts. • Our preliminary experience confirms experience demonstrated the technical feasibility and the accuracy of MRI-guided biopsies of thoraco-abdominal masses. • Interventional MRI can become the reference method for percutaneous biopsies in particular for lesions with difficult percutaneous approach.

Could Biparametric MRI Replace Multiparametric MRI in the Management of Prostate Cancer?

Prostate cancer (PCa) is a worldwide epidemiological problem, since it is one of the most prevalent types of neoplasia among men, and the third-leading cause of cancer-related deaths, after lung and colorectal tumors. Unfortunately, the early stages of PCa have a wide range of unspecific symptoms. For these reasons, early diagnosis and accurate evaluation of suspicious lesions are crucial. Multiparametric MRI (mpMRI) is currently the imaging modality of choice for diagnostic screening and local staging of PCa, but also has a leading role in guiding biopsies and in treatment biparametric MRI (bpMRI) could partially replace mpMRI due to its lack of adverse reactions caused by contrast agents, relatively lower costs, and shorter acquisition time. Further, 31 relevant articles regarding the advantages and disadvantages of the aforementioned imaging techniques were scanned. As a result, while bpMRI has comparable accuracy in detecting PCa, its roles in the other steps of PCa management are limited.

Prostate imaging features on magnetic resonance imaging of young patients

OBJECTIVE

To identify magnetic resonance imaging findings of the prostate in young adults, including symptomatic and asymptomatic patients. The aim of this study is to evaluate the main aspects of prostate imaging in young patients.

METHODS

A total of 102 patients under 40 years of age, who underwent prostate magnetic resonance imaging between January 2016 and January 2019, were included in this study. The patients were divided into two groups: symptomatic for prostatitis (Group 1) and asymptomatic (Group 2). Magnetic resonance imaging scans were anonymized and interpreted by a radiologist blinded for clinical information. The study evaluated peripheral zone signal in T2-weighted sequences, diffusion and apparent diffusion coefficient map; peripheral zone enhancement pattern; seminal vesicles and periprostatic fat.

RESULTS

All evaluated criteria did not present statistically significant differences between the two groups. The most common pattern was heterogeneous hyposignal on T2 (57.9% in Group 1 and 57.8% in Group 2; p=0.506), mild diffuse / wedge-shaped areas of hypointensity on apparent diffusion coefficient map (61.4% in Group 1 and 64.4% in Group 2; p=0.931) and early post-contrast enhancement (73.7% in Group 1 and 68.9% in Group 2, p=0719).

CONCLUSION

The magnetic resonance imaging aspect of young patients showed no differences between symptomatic and asymptomatic patients.

Complexities of Prostate Cancer

Prostate cancer has a long disease history and a wide variety and uncertainty in individual patients' clinical progress. In recent years, we have seen a revolutionary advance in both prostate cancer patient care and in the research field. The power of deep sequencing has provided cistromic and transcriptomic knowledge of prostate cancer that has not discovered before. Our understanding of prostate cancer biology, from bedside and molecular imaging techniques, has also been greatly advanced. It is important that our current theragnostic schemes, including our diagnostic modalities, therapeutic responses, and the drugs available to target non-AR signaling should be improved. This review article discusses the current progress in the understanding of prostate cancer biology and the recent advances in diagnostic and therapeutic strategies.

Deep autoencoder based hybrid dimensionality reduction approach for classification of SERS for melanoma cancer diagnostics

Melanoma, a kind of fatal skin cancer, originates in melanin secreting cells of the dermis. Disease identification in the early stages assures a high survival rate for the patient. Most of the existing techniques retard the cancer detection phase. Surface-Enhanced Raman Spectroscopy (SERS) can capture fine details from the specimens that machine learning models can utilize to discriminate between healthy and diseased individuals rapidly. Our research work proposes a deep autoencoder based hybrid dimensionality reduction approach with a machine learning model on SERS spectrums of human skin fibroblast for melanoma cancer diagnostics. SERS measurements of 307 samples in total, belonging to two different classes, such as normal (157 samples) and malignant melanoma (150 samples), are used in this study. The SERS spectra measurements for both the samples lie between 100cm - 1 and 4278cm - 1. The variations in the intensity of Raman bands between both classes are intrinsically subtle. Neighborhood Component Analysis (NCA) technique has been exerted to transform 2090 dimensional spectral features into 2090 dimensional vectors and then the Deep Autoencoder (DAE) model is used to handle the nonlinearity in the data and produce the latent space, while Linear Discriminant Analysis (LDA) classifier have been employed for discriminating the normal and cancer cells. The k-fold cross-validation technique with a k value of 10 is implemented to assess the metrics of the model. The stated hybrid (NCA and DAE) model with 10-dimension latent space achieves an accuracy of 98%, the sensitivity of 99% and specificity of 97%, respectively. Due to the high-intensity nature of the SERS spectrum, the existing linear dimensionality reduction based discriminating model fails if the class label (Normal or Cancer) gets distributed on the low variance side. The proposed methodology captures both linear and nonlinear underlying structures present in the spectrums, resulting in better classification compared to the standard dimensionality reduction techniques.

Assessment of the Utility of Multiparametric Magnetic Resonance Imaging for Initial Detection of Prostate Cancer

BACKGROUND: An accurate diagnosis is essential for the effective treatment of prostate cancer (PCa) and for the patients’ well-being. AIM: Thе main purpose of this study was to assess the utility of multiparametric magnetic resonance imaging (mp-MRI) for initial detection of PCa among the Bulgarian population of men with prostate diseases. MATERIALS AND METHODS: Fifty-three patients, aged 44 to 82 years, were evaluated for clinically significant PCa. Assessment methods included prostate-specific antigen (PSA) serum levels, transrectal ultrasonography (TRUS), GE Discovery 3T MRI, and 12-core TRUS biopsy. RESULTS: mp-MRI showed 83.20% concordance with TRUS biopsy: sensitivity of 91.43% (76.90–98.20), specificity of 75.00% (34.90–96.80), positive predictive values 94.10% (82.80–98.20) and negative predictive values 66.70% (38.70–86.40). Of the patients classified in prostate imaging–reporting and data system (PI-RADS) levels 4 and 5, 94.12% had positive TRUS biopsy, as well as 44.40% of PI-RADS had level 3. Irrespective of the patients’ age and PSA, PI-RADS was found to be a significant predictor of a positive TRUS biopsy (p = 0.009). PSA serum levels showed a low concordance with TRUS biopsy (area under the curve = 0.539; 95% confidence interval [CI]: 0.363–0.712) and a low, although significant, correlation with PI-RADS (rs = 0.416; 95% CI: 0.164–0.617). CONCLUSION: According to our findings, mp-MRI and TRUS biopsy have a high level of concordance for the initial detection of PCa. The incorporation of mp-MRI into the diagnostic pathway for PCa can significantly reduce the number of incorrect diagnoses based on PSA serum levels and/or suspicious physical and digital examinations.

Multi-parametric Magnetic Resonance Imaging Fusion for Automatic Classification of Prostate Cancer

Computer-aided diagnosis (CAD) of prostate cancer (PCa) using multi-parametric magnetic resonance imaging (mp-MRI) has recently gained great research interest. In this work, a fully automatic CAD pipeline of PCa using mp-MRI data is presented. In order to fully explore the mp-MRI data, we systematically investigate three multi-modal medical image fusion strategies in convolutional neural networks, namely input-level fusion, feature-level fusion, and decision-level fusion. Extensive experiments are conducted on two datasets with different PCa-related diagnostic tasks. We identify a pipeline that works relatively the best for both diagnostic tasks, two important components of which are stacking three adjacent slices as the input and performing decision-level fusion with specific loss weights. Clinical relevance- This work provides a practical method for automated diagnosis of PCa based on multi-parametric MRI.

A multicenter retrospective study on evaluation of predicative factors for positive biopsy of prostate cancer in real-world setting

OBJECTIVE

This study aimed to evaluate the predictors for positive biopsy in prostate cancer (PCa) patients and develop a risk-stratification score model for positive biopsy rate in patients with prostate specific antigen (PSA) in the gray zone.

METHODS

In this retrospective, multicenter, real-world study, Chinese patients receiving prostate biopsy for the first time were included. The study evaluated the positive biopsy rate, predictors for positive biopsy and a risk prediction model for PSA 4-10 ng/mL PCa was developed. The univariate and multivariate logistic regression analyses were used to identify the risk factors.

RESULTS

A total of 2426 patients were included in the study. The biopsy positive rate was 47.57%, 25.77%, and 60.57% among overall patients, total PSA (t-PSA) 4-10 ng/mL patients, and PSA > 10 ng/mL patients respectively. Elderly age 60-74, ≥75, multi parametric magnetic resonance imaging (MP-MRI), pre-operative PSA > 10 and PSA density (PSAD) significantly increased the positive rate in overall population, and elderly age, MP-MRI, positive digital rectal examination and f-PSA were significant predictors for positive biopsy in PSA 4-10 ng/mL population. A risk prediction model for positive biopsy rate in patients with PSA in the gray zone was developed. Area under curve (AUC) was associated with low accuracy for all the variables used such as tPSA (0.53), PSAD (0.57), frequency of puncture (0.53) and MP-MRI (0.64) in prediction of biopsy positive rate.

CONCLUSION

Our study evaluated the significant predicative factors for positive biopsy and the PCa risk prediction model developed might help Clinicians to avoid unnecessary biopsy in patients with PSA in gray zone.

Magnetic Resonance-Guided High-Intensity Focused Ultrasound Ablation of Uterine Fibroids-Efficiency Assessment with the Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging and the Potential Role of the Administration of Uterotonic Drugs

OBJECTIVE

The assessment of the usefulness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) when qualifying patients with uterine fibroids (UFs) for magnetic resonance-guided high-intensity ultrasound (MR-HIFU).

MATERIAL AND METHODS

This retrospective, single center study included 283 women who underwent DCE-MRI and were treated with MR-HIFU. The patients were divided according to non-perfused volume (NPV) as well as by the type of curve for patients with a washout curve in the DCE-MRI study and patients without a washout curve. The studied women were assessed in three groups according to the type of uterotonics administered. Group A (57 patients) received one dose of misoprostol/diclofenac transvaginally and group B (71 patients) received oxytocin intravenously prior to the MR-HIFU procedure. The remaining 155 women (group C) were treated with the traditional non-drug enhanced MR-HIFU procedure.

RESULTS

The average NPV value was higher in no washout group, and depended on the uterotonics used.

CONCLUSIONS

We demonstrated a correlation between dynamic contrast enhancement curve types and the therapeutic efficacy of MR-HIFU. Our results suggest that DCE-MRI has the potential to assess treatment outcomes among patients with UFs, and patients with UFs that present with a washout curve may benefit from the use of uterotonic drugs. More studies are required to draw final conclusions.

Radiomics and Prostate MRI: Current Role and Future Applications

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine learning and deep learning) applied to the field of prostate cancer.

State-of-the-art imaging for diagnosis of metastatic bone disease

Metastatic bone disease (MBD) is common—it is detected in up to 65–75% of patients with breast or prostate cancer, in over 35% of patients with lung cancer; and almost all patients with symptomatic multiple myeloma have focal lesions or a diffuse bone marrow infiltration. Metastatic bone disease can cause a variety of symptoms and is often associated with a poorer prognosis, with high social and health-care costs. Population-based cohort studies confirm significantly increased health-care utilization costs in patients presenting with cancer with MBD compared with those without MBD. The prolonged survival of patients with bone metastasis thanks to advances in therapy presents an opportunity for better treatments for this patient cohort. Early and accurate diagnosis of bone metastases is therefore crucial. The patterns and presentation of MBD are quite heterogeneous and necessitate good knowledge of the possibilities and limitations of each imaging modality. Here, we review the state-of-the-art imaging techniques, assess the need for evidence-based and cost-effective patient care pathways, and advocate multidisciplinary management based on collaborations between orthopedic surgeons, pathologists, oncologists, radiotherapists, and radiologists aimed at improving patient outcomes. Radiologists play a key role in this multidisciplinary approach to decision-making through correlating the tumor entity, the tumor biology, the impact on the surrounding tissues and progression, as well as the overall condition of the patient. This approach helps to choose the best patient-tailored imaging plan advocating a “choose wisely” strategy throughout the initial diagnosis, minimally invasive treatment procedures, as well as follow-up care plans.

Role of metabolic imaging in diagnosis of primary, metastatic, and recurrent prostate cancer

PURPOSE OF REVIEW

The present review describes the current role of metabolic imaging techniques such as multiparametric MRI (mpMRI), magnetic resonance spectroscopic imaging (MRSI), hyperpolarized MRSI, and positron emission tomography (PET) in the diagnosis of primary prostate cancer, surveillance of low-grade disease, detection of metastases, and evaluation of biochemical recurrence after therapy.

RECENT FINDINGS

The natural history of prostate cancer ranges from indolent disease that is optimally monitored by active surveillance, to highly aggressive disease that can be lethal. Current diagnostic methods remain imperfect in noninvasively distinguishing between silent versus aggressive tumors. Hence, there is a high demand for noninvasive imaging techniques that offer insight into biological behavior of prostate cancer cells. Characterization of prostate cancer metabolism is a promising area to provide such insights.

SUMMARY

Metabolic imaging may allow for greater detection and ultimately characterization of tumor based on aggressiveness and spread. Hence, it has the potential to monitor tumor activity, predict prognostic outcomes, and guide individualized therapies.

Are TRUS-guided prostate biopsies in clinical practice robust enough to make a correct assessment of the surgical strategy in prostatectomies? Poor correlation between preoperative prostate biopsies and postoperative specimens

Objective: TRUS-guided prostatic biopsies are the mainstay procedure to diagnose prostatic cancer. The aim was to investigate how accurate and reliable these biopsies are by comparing them with the final pathology results after prostatectomy.Materials and methods: One hundred consecutive patients diagnosed with localized prostatic cancer using this technique and who subsequently underwent a radical prostatectomy in Västerbotten County were included in this study. From the pathological-anatomical diagnosis (PAD) of core needle biopsies, data was extracted on the location of the tumour within the prostate, the tumour volume and the Gleason score, and compared with the characteristics of the prostatectomy specimen. The frequency and type of deviation between the pre-operative and post-operative examinations was recorded.Results: In 95% of the cases there was a poor correlation between the pre-operative and post-operative pathological reports. In the final report, 48% had a higher Gleason score and 88% had deviations in localization when compared with the information from the biopsies. If known prior to surgery, a total of 104 of these deviations might have had a significant impact on the surgical strategy.Conclusions: The pre-operative biopsies in this setting rarely match the final prostate PAD results (5%). The most common deviations were in localization and in Gleason score, where the majority consisted of a higher Gleason score and/or tumour presence in a previously unknown location. This information, if known prior to surgery, might have altered the treatment strategy and ultimately the outcome of the treatment.

Focal therapy for localized prostate cancer: is there a "middle ground" between active surveillance and definitive treatment?

In recent years, it has come a long way in the diagnosis, treatment, and follow-up of prostate cancer. Beside this, it was argued that definitive treatments could cause overtreatment, particularly in the very low, low, and favorable risk group. When alternative treatment and follow-up methods are being considered for this group of patients, active surveillance is seen as a good alternative for patients with very low and low-risk groups in this era. However, it has become necessary to find other alternatives for patients in the favorable risk group or patients who cannot adopt active follow-up. In the light of technological developments, the concept of focal therapy was introduced with the intensification of research to treat only the lesioned area instead of treating the entire organ for prostate lesions though there are not many publications about many of them yet. According to the initial results, it was understood that the results could be good if the appropriate focal therapy technique was applied to the appropriate patient. Thus, focal therapies have begun to find their "middle ground" place between definitive therapies and active follow-up.