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Background: Prostate cancer (PCa) is a highly heterogeneous disease, making tailored treatment approaches challenging. Magnetic resonance imaging (MRI), notably diffusion-weighted imaging (DWI) and the derived Apparent Diffusion Coefficient (ADC) maps, plays a crucial role in PCa characterization. In this context, radiomics is a very promising approach able to disclose insights from MRI data. However, the sensitivity of radiomic features to MRI settings, encompassing DWI protocols and multicenter variations, requires the development of robust and generalizable models., Purpose: To develop a comprehensive radiomics framework for noninvasive PCa characterization using ADC maps, focusing on identifying reliable imaging biomarkers against intra- and inter-institution variations., Materials and Methods: Two patient cohorts, including an internal cohort (118 PCa patients) used for both training (75%) and hold-out testing (25%), and an external cohort (50 PCa patients) for independent testing, were employed in the study. DWI images were acquired with three different DWI protocols on two different MRI scanners: two DWI protocols acquired on a 1.5-T scanner for the internal cohort, and one DWI protocol acquired on a 3-T scanner for the external cohort. One hundred and seven radiomics features (i.e., shape, first order, texture) were extracted from ADC maps of the whole prostate gland. To address variations in DWI protocols and multicenter variability, a dedicated pipeline, including two-way ANOVA, sequential-feature-selection (SFS), and ComBat features harmonization was implemented. Mann-Whitney U-tests (α = 0.05) were performed to find statistically significant features dividing patients with different tumor characteristics in terms of Gleason score (GS) and T-stage. Support-Vector-Machine models were then developed to predict GS and T-stage, and the performance was assessed through the area under the curve (AUC) of receiver-operating-characteristic curves., Results: Downstream of ANOVA, two subsets of 38 and 41 features stable against DWI protocol were identified for GS and T-stage, respectively. Among these, SFS revealed the most predictive features, yielding an AUC of 0.75 (GS) and 0.70 (T-stage) in the hold-out test. Employing ComBat harmonization improved the external-test performance of the GS model, raising AUC from 0.72 to 0.78., Conclusion: By incorporating stable features with a harmonization procedure and validating the model on an external dataset, model robustness, and generalizability were assessed, highlighting the potential of ADC and radiomics for PCa characterization., (© 2024 The Author(s). Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Objective: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institution cohort., Methods: Patients who underwent multiparametric MRI and prostatectomy in our institution in 2015-2018 were considered; a total of 949 patients were included. Gradient-boosted decision tree models were separately trained using clinical features alone and in combination with radiological reporting and/or prostate radiomic features to predict pathological T, pathological N, ISUP score, and their change from preclinical assessment. Model behavior was analyzed in terms of performance, feature importance, Shapley additive explanation (SHAP) values, and mean absolute error (MAE). The best model was compared against a naïve model mimicking clinical workflow., Results: The model including all variables was the best performing (AUC values ranging from 0.73 to 0.96 for the six endpoints). Radiomic features brought a small yet measurable boost in performance, with the SHAP values indicating that their contribution can be critical to successful prediction of endpoints for individual patients. MAEs were lower for low-risk patients, suggesting that the models find them easier to classify. The best model outperformed (p ≤ 0.0001) clinical baseline, resulting in significantly fewer false negative predictions and overall was less prone to under-staging., Conclusions: Our results highlight the potential benefit of integrative ML models for pathological status prediction in PCa. Additional studies regarding clinical integration of such models can provide valuable information for personalizing therapy offering a tool to improve non-invasive prediction of pathological status., Clinical Relevance Statement: The best machine learning model was less prone to under-staging of the disease. The improved accuracy of our pathological prediction models could constitute an asset to the clinical workflow by providing clinicians with accurate pathological predictions prior to treatment., Key Points: • Currently, the most common strategies for pre-surgical stratification of prostate cancer (PCa) patients have shown to have suboptimal performances. • The addition of radiological features to the clinical features gave a considerable boost in model performance. Our best model outperforms the naïve model, avoiding under-staging and resulting in a critical advantage in the clinic. •Machine learning models incorporating clinical, radiological, and radiomics features significantly improved accuracy of pathological prediction in prostate cancer, possibly constituting an asset to the clinical workflow., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Purpose: To assess the ability of tumor apparent diffusion coefficient (ADC) values obtained from multiparametric magnetic resonance imaging (mpMRI) to predict the risk of 5-year biochemical recurrence (BCR) after radical prostatectomy (RP)., Materials and Methods: This retrospective analysis included 1207 peripheral and 232 non-peripheral zone prostate cancer (PCa) patients who underwent mpMRI before RP (2012-2015), with the outcome of interest being 5-year BCR. ADC was evaluated as a continuous variable and as categories: low (< 850 µm 2 /s), intermediate (850-1100 µm 2 /s), and high (> 1100 µm 2 /s). Kaplan-Meier curves with log-rank testing of BCR-free survival, multivariable Cox proportional hazard regression models were formed to estimate the risk of BCR., Results: Among the 1439 males with median age 63 (± 7) years, the median follow-up was 59 months, and 306 (25%) patients experienced BCR. Peripheral zone PCa patients with BCR had lower tumor ADC values than those without BCR (874 versus 1025 µm 2 /s, p < 0.001). Five-year BCR-free survival rates were 52.3%, 74.4%, and 87% for patients in the low, intermediate, and high ADC value categories, respectively (p < 0.0001). Lower ADC was associated with BCR, both as continuously coded variable (HR: 5.35; p < 0.001) and as ADC categories (intermediate versus high ADC-HR: 1.56, p = 0.017; low vs. high ADC-HR; 2.36, p < 0.001). In the non-peripheral zone PCa patients, no association between ADC and BCR was observed., Conclusion: Tumor ADC values and categories were found to be predictive of the 5-year BCR risk after RP in patients with peripheral zone PCa and may serve as a prognostic biomarker., (© 2024. Italian Society of Medical Radiology.)

Acknowledging the increasing use of whole-body magnetic resonance imaging (WB-MRI) in the oncological setting, we conducted a narrative review focusing on practical aspects of the examination and providing a synthesis of various acquisition protocols described in the literature. Firstly, we addressed the topic of patient preparation, emphasizing methods to enhance examination acceptance. This included strategies for reducing anxiety and patient distress, improving staff-patient interactions, and increasing overall patient comfort. Secondly, we analysed WB-MRI acquisition protocols recommended in existing imaging guidelines, such as MET-RADS-P, MY-RADS, and ONCO-RADS, and provided an overview of acquisition protocols reported in the literature regarding other expanding applications of WB-MRI in oncology, in patients with breast cancer, ovarian cancer, melanoma, colorectal and lung cancer, lymphoma, and cancers of unknown primary. Finally, we suggested possible acquisition parameters for whole-body images across MR systems from three different vendors., (© 2024. Italian Society of Medical Radiology.)

Tofts models have failed to produce reliable quantitative markers for prostate cancer. We examined the differences between prostate zones and lesion PI-RADS categories and grade group (GG) using regions of interest drawn in tumor and normal-appearing tissue for a two-compartment uptake (2CU) model (including plasma volume (v p ), plasma flow (F p ), permeability surface area product (PS), plasma mean transit time (MTT p ), capillary transit time (T c ), extraction fraction (E), and transfer constant (K trans )) and exponential (amplitude (A), arrival time (t 0 ), and enhancement rate (α)), sigmoidal (amplitude (A 0 ), center time relative to arrival time (A 1 - T 0 ), and slope (A 2 )), and empirical mathematical models, and time to peak (TTP) parameters fitted to high temporal resolution (1.695 s) DCE-MRI data. In 25 patients with 35 PI-RADS category 3 or higher tumors, we found F p and α differed between peripheral and transition zones. Parameters F p , MTT p , T c , E, α, A 1 - T 0 , and A 2 and TTP all showed associations with PI-RADS categories and with GG in the PZ when normal-appearing regions were included in the non-cancer GG. PS and K trans were not associated with any PI-RADS category or GG. This pilot study suggests early enhancement parameters derived from ultrafast DCE-MRI may become markers of prostate cancer.

Background Current predictive tools to estimate the risk of biochemical recurrence (BCR) after treatment of prostate cancer do not consider multiparametric MRI (mpMRI) information. Purpose To develop a risk prediction tool that considers mpMRI findings to assess the risk of 5-year BCR after radical prostatectomy. Materials and Methods In this retrospective single-center analysis in 1459 patients with prostate cancer who underwent mpMRI before radical prostatectomy (in 2012-2015), the outcome of interest was 5-year BCR (two consecutive prostate-specific antigen [PSA] levels > 0.2 ng/mL [0.2 µg/L]). Patients were randomly divided into training (70%) and test (30%) sets. Kaplan-Meier plots were applied to the training set to estimate survival probabilities. Multivariable Cox regression models were used to test the relationship between BCR and different sets of exploratory variables. The C-index of the final model was calculated for the training and test sets and was compared with European Association of Urology, University of California San Francisco Cancer of the Prostate Risk Assessment, Memorial Sloan-Kettering Cancer Center, and Partin risk tools using the partial likelihood ratio test. Five risk categories were created. Results The median duration of follow-up in the whole cohort was 59 months (IQR, 32-81 months); 376 of 1459 (25.8%) patients had BCR. A multivariable Cox regression model (referred to as PIPEN, and composed of PSA density, International Society of Urological Pathology grade group, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extraprostatic extension score, nodes) fitted to the training data yielded a C-index of 0.74, superior to that of other predictive tools (C-index 0.70 for all models; P ≤ .01) and a median higher C-index on 500 test set replications (C-index, 0.73). Five PIPEN risk categories were identified with 5-year BCR-free survival rates of 92%, 84%, 71%, 56%, and 26% in very low-, low-, intermediate-, high-, and very high-risk patients, respectively (all P < .001). Conclusion A five-item model for predicting the risk of 5-year BCR after radical prostatectomy for prostate cancer was developed and internally verified, and five risk categories were identified. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Aguirre and Ortegón in this issue.

Objective: Magnetic resonance often produces feelings of anxiety before, or during, the examination. The aim of this study was to assess anxiety and potential causes of anxiety in cancer patients undergoing whole-body magnetic resonance imaging (WB-MRI)., Methods: This monocentric study recruited 70 cancer patients who were scheduled to undergo WB-MRI for detection, staging or therapy monitoring. At baseline (prior to the WB-MRI), assessments were performed using the State-Trait Anxiety Inventory (STAI-Y 1), Illness Perception Questionnaire (IPQ-R), Big Five Inventory (BIF-10) and Revised Life Orientation Test (LOT-R), while at the end of the WB-MRI examination the patients repeated the STAI-Y 1 questionnaire and were asked to indicate their preference between WB-MRI and computed tomography., Results: We found a positive correlation between pre- and post-examination STAI-Y 1 scores (r = 0.536, p < .0001), with no significant difference between them. Pre-examination STAI-Y 1 scores had a negative correlation with the emotional stability in the BIF-10 questionnaire (r = -0.47, p = .001) and a positive correlation with emotional representation (r = 0.57, p = .001) in IPQ-R. The post-examination STAI-Y 1 had a negative correlation with optimistic orientation (r = -0.59, p = .001)., Conclusions: The anxiety associated with a WB-MRI examination was only in small part associated with the examination itself, and in fact, most patients preferred WB-MRI to computed tomography. Concern with the outcome of the examination was likely a greater source of anxiety., (© 2022 The Authors. Cancer Reports published by Wiley Periodicals LLC.)

Whole-body magnetic resonance imaging (WB-MRI) is an all-in-one non-invasive technique that can be used also in early cancer diagnosis in asymptomatic individuals. The aim of this work was to identify the personal characteristics predicting the satisfaction for the WB-MRI in a sample of healthy subjects. Before undergoing a WB-MRI examination, 154 participants completed a questionnaire covering sociodemographics (age, gender, education), personality traits (agreeableness, conscientiousness, emotional stability, extroversion, openness), and expectations about the procedure (expected usefulness, risks, noise, lack of air, duration). After the examination, participants reported their satisfaction with the WB-MRI. Results showed that agreeableness had a significant and positive effect on satisfaction. Expectations about its utility and the possible noise had a positive effect on satisfaction. Expectations of lack of air showed a negative significant effect on satisfaction. Sociodemographics showed no significant effects. Our study confirmed the important impact of individuals' personality and expectations on satisfaction with the procedure. Moreover, it provides useful insights for developing consultations aimed at increasing the acceptability of the procedure.

Purpose: To investigate the use of apparent diffusion coefficient (ADC) values and other MRI features for predicting positive surgical margins (PSMs) in patients undergoing radical prostatectomy., Materials and Methods: We retrospectively identified 400 consecutive patients who underwent surgery for prostate cancer between January 2015 and June 2016. ADC values of the index lesion and other preoperative magnetic resonance imaging features, including tumor site, laterality, level, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extracapsular extension score, and prostate volume, were assessed. Univariate and multivariable logistic regression were performed. Performance in predicting the occurrence of PSMs was measured using the area under the curve (AUC). AUC differences were evaluated with the DeLong method. The Youden index was calculated to identify the ADC threshold to best discriminate patients with PSMs., Results: Of the 400 patients, 105 (26.2%) had PSMs after radical prostatectomy. ADC values, Prostate Imaging Reporting and Data System category, extracapsular extension score, tumor site, and laterality were significantly associated with PSMs (P < .001) in univariate analysis. The AUC of the predictive model based on ADC alone was 68.2% (95% confidence interval, 62.2-74.2%) and did not significantly differ from the best multivariable predictive model which combined laterality, and site with ADC to attain an AUC of 70.0% (95% confidence interval, 64.2-75.8%; DeLong P = .318). The ADC threshold that maximized the Youden index was 960.3 µm 2 /s., Conclusion: ADC values and preoperative magnetic resonance imaging features can help estimate the risk of PSMs after radical prostatectomy., Competing Interests: Disclosure Paul Summers declares a relationship with the following companies: QMRI Tech. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Whole-body magnetic resonance imaging (WB-MRI) is currently recommended for cancer screening in adult and paediatric subjects with cancer predisposition syndromes, representing a substantial aid for prolonging health and survival of these subjects with a high oncological risk. Additionally, the number of studies exploring the use of WB-MRI for cancer screening in asymptomatic subjects from the general population is growing. The primary aim of this review was to analyse the acquisition protocols found in the literature, in order to identify common sequences across published studies and to discuss the need of additional ones for specific populations. The secondary aim of this review was to provide a synthesis of current recommendations regarding the use of WB-MRI for cancer screening., (© 2021. The Author(s).)

The use of multiparametric prostate magnetic resonance imaging (mpMRI) is recommended, in the European Association of Urology (EAU) guidelines, for local staging of patients with prostate cancer (PCa). Systemic staging is recommended only for patients with unfavourable intermediate and high-risk disease; with bone and lymph node assessments usually being performed using bone scan (BS) and computed tomography (CT), respectively. Magnetic resonance imaging (MRI) is the imaging technique with the highest sensitivity for the detection of bone metastases and has shown promising results also for lymph node assessments. In this report we illustrate how MRI provided a comprehensive assessment of local disease as well as bone and lymph node metastases in a patient with PCa. (www.actabiomedica.it).

We read with great interest the paper entitled "Impact of physical activity of cognitive functions: a new field for research and management of Cystic Fibrosis" by Elce et al. [...].

This study aimed to identify the main factors that asymptomatic individuals considered when deciding to undergo self-referred Whole-body MRI (WB-MRI) for early cancer diagnosis and the subjective values attributed to each mentioned factor in a Decision tree analysis. Personal characteristics such as risk perception and personality were investigated as possible factors affecting value attribution. Seventy-four volunteers (mean age 56.4; male = 47) filled a simplified decision tree by expressing the expected factors and related subjective values associated with two screening options for early cancer diagnosis (standard procedures vs. WB-MRI+standard procedures) while waiting for a WB-MRI examination. Questionnaires on risk perception and personality traits were also administered. Expected factors were summarized in 5 clusters: diagnostic certainty, psychological well-being, safety, test validity and time/cost. Test validity and time/cost were evaluated as potential losses in both procedures. Diagnostic Certainty and safety were evaluated as losses in standard screening, and as an advantage when considering WB-MRI+standard screening. Forty-five percent of participants considered WB-MRI+standard screening as beneficial for their psychological well-being. Finally, personal absolute and comparative risk to get cancer was associated with a positive value attribution to WB-MRI ( p < 0.05). Our results showed the addition of WB-MRI to be generally considered a good option to increase individuals' perceptions of diagnostic certainty and the safety of the exam, and to increase psychological well-being. The positive value of such a screening option increased with the individual's cancer risk perception.

We aimed to describe the relationships between the relative fat fraction (%FF), muscle-normalized diffusion-weighted (DW) image signal intensity and water apparent diffusion coefficient (ADC), sex and age for normal bone marrow, in the normal population. Our retrospective cohort consisted of 100 asymptomatic individuals, equally divided by sex and 10-year age groups, who underwent whole-body MRI at 1.5 T for early cancer detection. Semi-automated segmentation of global bone marrow volume was performed using the DW images and the resulting segmentation masks were projected onto the ADC and %FF maps for extraction of parameter values. Differences in the parameter values between sexes at age ranges were assessed using the Mann-Whitney and Kruskal-Wallis tests. The Spearman correlation coefficient r was used to assess the relationship of each imaging parameter with age, and of %FF with ADC and normalized DW signal intensity values. The average %FF of normal bone marrow was 65.6 ± 7.2%, while nSI b50 , nSI b900 and ADC were 1.7 ± 0.5, 3.2 ± 0.9 and 422 ± 67 μm 2 /s, respectively. The bone marrow %FF values increased with age in both sexes (r = 0.63 and r = 0.64, respectively, p < 0.001). Values of nSI b50 and nSI b900 were higher in younger women compared to men of the same age groups ( p < 0.017), but this difference decreased with age. In our cohort of asymptomatic individuals, the values of bone marrow relative %FF, normalized DW image signal intensity and ADC indicate higher cellularity in premenopausal women, with increasing bone marrow fat with aging in both sexes.

Using semi-automated software simplifies quantitative analysis of the visible burden of disease on whole-body MRI diffusion-weighted images. To establish the intra- and inter-observer reproducibility of apparent diffusion coefficient (ADC) measures, we retrospectively analyzed data from 20 patients with bone metastases from breast (BCa; n = 10; aged 62.3 ± 14.8) or prostate cancer (PCa; n = 10; aged 67.4 ± 9.0) who had undergone examinations at two timepoints, before and after hormone-therapy. Four independent observers processed all images twice, first segmenting the entire skeleton on diffusion-weighted images, and then isolating bone metastases via ADC histogram thresholding (ADC: 650-1400 µm 2 /s). Dice Similarity, Bland-Altman method, and Intraclass Correlation Coefficient were used to assess reproducibility. Inter-observer Dice similarity was moderate (0.71) for women with BCa and poor (0.40) for men with PCa. Nonetheless, the limits of agreement of the mean ADC were just ±6% for women with BCa and ±10% for men with PCa (mean ADCs: 941 and 999 µm 2 /s, respectively). Inter-observer Intraclass Correlation Coefficients of the ADC histogram parameters were consistently greater in women with BCa than in men with PCa. While scope remains for improving consistency of the volume segmented, the observer-dependent variability measured in this study was appropriate to distinguish the clinically meaningful changes of ADC observed in patients responding to therapy, as changes of at least 25% are of interest.

Objective: To evaluate the satisfaction of asymptomatic subjects who self-referring Whole-Body Magnetic Resonance Imaging (WB-MRI) for early cancer diagnosis., Methods: Subjects completed a pre-examination questionnaire, while waiting for their WB-MRI examination, recording demographics, expected discomfort, perceived knowledge and usefulness of the procedure and health risk perceptions, as well as a post-examination questionnaire, measuring discomfort experienced, acceptability and satisfaction with WB-MRI. We examined which factors influenced discomfort and satisfaction associated with WB-MRI., Results: 65 asymptomatic subjects (median age 51; 29 females) completed the questionnaire. Before WB-MRI, 29% of subjects expected discomfort of some form with claustrophobia (27.7%) and exam duration (24.6%) being the most common concerns. Experienced discomfort due to shortness of breath was significantly lower than expected. This difference was significantly associated with the personal risk perception to get a disease ( p = 0.01) and educational level ( p = 0.002). More specifically, higher level of perceived personal risk of getting a disease and lower level of education were associated with higher expected than experienced discomfort. Similarly, experiencing less claustrophobia than expected was significantly associated with gender ( p = 0.005) and more pronounced among females. A majority (83%) of subjects expressed high levels of satisfaction with WB-MRI for early cancer diagnosis and judged it more acceptable than other diagnostic exams., Conclusions: Asymptomatic subjects self-referring to WB-MRI for early cancer diagnosis showed high levels of satisfaction and acceptability with the examination. Nevertheless, a relevant proportion of participants reported some form of discomfort. Interestingly, participants with higher perceived personal risk to get a disease, lower education and females showed to expect higher discomfort than experienced., Advances in Knowledge: Scope exists for measures to assess expected feelings and develop personalized interventions to reduce the stress anticipated by individuals deciding to undergo WB-MRI for early cancer diagnosis.

Objectives: Radiomic involves testing the associations of a large number of quantitative imaging features with clinical characteristics. Our aim was to extract a radiomic signature from axial T2-weighted (T2-W) magnetic resonance imaging (MRI) of the whole prostate able to predict oncological and radiological scores in prostate cancer (PCa)., Methods: This study included 65 patients with localized PCa treated with radiotherapy (RT) between 2014 and 2018. For each patient, the T2-W MRI images were normalized with the histogram intensity scale standardization method. Features were extracted with the IBEX software. The association of each radiomic feature with risk class, T-stage, Gleason score (GS), extracapsular extension (ECE) score, and Prostate Imaging Reporting and Data System (PI-RADS v2) score was assessed by univariate and multivariate analysis., Results: Forty-nine out of 65 patients were eligible. Among the 1702 features extracted, 3 to 6 features with the highest predictive power were selected for each outcome. This analysis showed that texture features were the most predictive for GS, PI-RADS v2 score, and risk class; intensity features were highly associated with T-stage, ECE score, and risk class, with areas under the receiver operating characteristic curve (ROC AUC) ranging from 0.74 to 0.94., Conclusions: MRI-based radiomics is a promising tool for prediction of PCa characteristics. Although a significant association was found between the selected features and all the mentioned clinical/radiological scores, further validations on larger cohorts are needed before these findings can be applied in the clinical practice., Key Points: • A radiomic model was used to classify PCa aggressiveness. • Radiomic analysis was performed on T2-W magnetic resonance images of the whole prostate gland. • The most predictive features belong to the texture (57%) and intensity (43%) domains.

Magnetic resonance imaging (MRI) is particularly attractive for clinical application in perfusion imaging thanks to the absence of ionizing radiation and limited volumes of contrast agent (CA) necessary. Dynamic contrast-enhanced MRI (DCE-MRI) involves sequentially acquiring T 1 -weighted images through an organ of interest during the passage of a bolus administration of CA. It is a particularly flexible approach to perfusion imaging as the signal intensity time course allows not only rapid qualitative assessment, but also quantitative measures of intrinsic perfusion and permeability parameters. We examine aspects of the T 1 -weighted image series acquisition, CA administration, post-processing that constitute a DCE-MRI study in clinical practice, before considering some heuristics that may aid in interpreting the resulting contrast enhancement time series. While qualitative DCE-MRI has a well-established role in the diagnostic assessment of a range of tumours, and a central role in MR mammography, clinical use of quantitative DCE-MRI remains limited outside of clinical trials. The recent publication of proposals for standardized acquisition and analysis protocols for DCE-MRI by the Quantitative Imaging Biomarker Alliance may be an opportunity to consolidate and advance clinical practice.

Clinical suspicion of Prostate Cancer (PCa) is largely based on increased prostate specific antigen (PSA) level and/or abnormal digital rectal examination (DRE) and/or positive imaging and, up today, biopsy is mandatory to confirm the diagnosis. The old model consisted of Standard Biopsy (SBx), that is random sampling of the prostate gland under ultrasound guidance (TRUS), in subjects with clinical suspicion of PCa. This involves the risk of not diagnosing a high percentage of tumors (up to 30%) and of an incorrect risk stratification. Multiparametric Magnetic Resonance Imaging (mpMRI) has transformed the diagnostic pathway of PCa, not only as an imaging method for detecting suspicious lesions, but also as an intraprocedural guidance for Target Biopsy (MRI-TBx), thus bridging the diagnostic gap. Several single and multicenter randomized trials, such as PROMIS, MRI first, PRECISION and that reported by Van der Leest et al. have confirmed the superiority of the "MRI pathway", consisting of mpMRI and MRI-TBx of suspicious lesions, over the "standard pathway" of SBx in all patients with elevated PSA and/or positive DRE. MRI-TBx appears to be advantageous in reducing the overall number of biopsies performed, as well as in reducing the diagnosis of clinically insignificant disease while maintaining or improving the diagnosis of clinically significant PCa (cs-PCa). Moreover, it shows a reduction in the diagnosis of ins-PCa, and therefore, of overdiagnosis, when using MRI-TBx without sacrificing performance in the diagnosis of cs-PCa.

Background: The number of studies describing the use of whole-body magnetic resonance imaging (WB-MRI) for screening of malignant tumours in asymptomatic subjects is increasing. Our aim is to review the methodologies used and the results of the published studies on per patient and per lesion analysis, and to provide recommendations on the use of WB-MRI for cancer screening., Main Body: We identified 12 studies, encompassing 6214 WB-MRI examinations, which provided the rates of abnormal findings and findings suspicious for cancer in asymptomatic subjects, from the general population. Eleven of 12 studies provided imaging protocols that included T1- and T2-weighted sequences, while only five included diffusion weighted imaging (DWI) of the whole body. Different categorical systems were used for the classification and the management of abnormal findings. Of 17,961 abnormal findings reported, 91% were benign, while 9% were oncologically relevant, requiring further investigations, and 0.5% of lesions were suspicious for cancer. A per-subject analysis showed that just 5% of subjects had no abnormal findings, while 95% had abnormal findings. Findings requiring further investigation were reported in 30% of all subjects, though in only 1.8% cancer was suspected. The overall rate of histologically confirmed cancer was 1.1%., Conclusion: WB-MRI studies of cancer screening in the asymptomatic general population are too heterogeneous to draw impactful conclusions regarding efficacy. A 5-point lesion scale based on the oncological relevance of findings appears the most appropriate for risk-based management stratification. WB-MRI examinations should be reported by experienced oncological radiologists versed on WB-MRI reading abnormalities and on onward referral pathways.

Purpose: The evaluation of the surgical margin in breast conservative surgery is a matter of general interest as such treatments are subject to the critical issue of margin status as positive surgical margins can undermine the effectiveness of the procedure. The relatively unexplored ability of millimeter-wave (mm-wave) spectroscopy to provide insight into the dielectric properties of breast tissues was investigated as a precursor to their possible use in assessment of surgical margins., Methods: We assessed the ability of a mm-wave system with a roughly hemispherical sensitive volume of ∼3 mm radius to distinguish malignant breast lesions in prospectively and consecutively collected tumoral and non-tumoral ex-vivo breast tissue samples from 91 patients. We characterized the dielectric properties of 346 sites in these samples, encompassing malignant, fibrocystic disease and normal breast tissues. An expert pathologist subsequently evaluated all measurement sites., Results: At multivariate analysis, mm-wave dielectric properties were significantly correlated to histologic diagnosis and fat content. Further, using 5-fold cross-validation in a Bayesian logistic mixed model that considered the patient as a random effect, the mm-wave dielectric properties of neoplastic tissues were significantly different from normal breast tissues, but not from fibrocystic tissue., Conclusion: Reliable discrimination of malignant from normal, fat-rich breast tissue to a depth compatible with surgical margin assessment requirements was achieved with mm-wave spectroscopy., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The past decade has witnessed a growing role and increasing use of whole-body magnetic resonance imaging (WB-MRI). Driving these successes are developments in both hardware and software that have reduced overall examination times and significantly improved MR imaging quality. In addition, radiologists and clinicians have continued to find promising new applications of this innovative imaging technique that brings together morphologic and functional characterization of tissues. In oncology, the role of WB-MRI has expanded to the point of being recommended in international guidelines for the assessment of several cancer histotypes (multiple myeloma, melanoma, prostate cancer) and cancer-prone syndromes (Li-Fraumeni and hereditary paraganglioma-pheochromocytoma syndromes). The literature shows growing use of WB-MRI for the staging and follow-up of other cancer histotypes and cancer-related syndromes (including breast cancer, lymphoma, neurofibromatosis, and von Hippel-Lindau syndromes). The main aim of this review is to examine the current scientific evidence for the use of WB-MRI in oncology.

Purpose: Peptide receptor radionuclide therapy (PRRT) with 90 Y-labelled and 177 Lu-labelled peptides is an effective strategy for the treatment of metastatic/nonresectable neuroendocrine tumours (NETs). Dosimetry provides important information useful for optimizing PRRT with individualized regimens to reduce toxicity and increase tumour responses. However, this strategy is not applied in routine clinical practice, despite the fact that several dosimetric studies have demonstrated significant dose-effect correlations for normal organ toxicity and tumour response that can better guide therapy planning. The present study reviews the key relationships and the radiobiological models available in the literature with the aim of providing evidence that optimization of PRRT is feasible through the implementation of dosimetry., Methods: The MEDLINE database was searched combining specific keywords. Original studies published in the English language reporting dose-effect outcomes in patients treated with PRRT were chosen., Results: Nine of 126 studies were selected from PubMed, and a further five were added manually, reporting on 590 patients. The studies were analysed and are discussed in terms of weak and strong elements of correlations., Conclusion: Several studies provided evidence of clinical benefit from the implementation of dosimetry in PRRT, indicating the potential contribution of this approach to reducing severe toxicity and/or reducing undertreatment that commonly occurs. Prospective trials, possibly multicentre, with larger numbers of patients undergoing quantitative dosimetry and with standardized methodologies should be carried out to definitively provide robust predictive paradigms to establish effective tailored PRRT.

Purpose: We sought to measure quantitative magnetization transfer (qMT) properties of the substantia nigra pars compacta (SNc) in patients with Parkinson's disease (PD) and healthy controls (HCs) using a full qMT analysis and determine whether a rapid single-point measurement yields equivalent results for pool size ratio (PSR)., Methods: Sixteen different MT-prepared MRI scans were obtained at 3 T from 16 PD patients and eight HCs, along with B1, B0, and relaxation time maps. Maps of PSR, free and macromolecular pool transverse relaxation times ([Formula: see text], [Formula: see text]) and rate of MT exchange between pools (k mf ) were generated using a full qMT model. PSR maps were also generated using a single-point qMT model requiring just two MT-prepared images. qMT parameter values of the SNc, red nucleus, cerebral crus, and gray matter were compared between groups and methods., Results: PSR of the SNc was the only qMT parameter to differ significantly between groups (p < 0.05). PSR measured via single-point analysis was less variable than with the full MT model, provided slightly better differentiation of PD patients from HCs (area under curve 0.77 vs. 0.75) with sensitivity of 0.75 and specificity of 0.87, and was better than transverse relaxation time in distinguishing PD patients from HCs (area under curve 0.71, sensitivity 0.87, and specificity 0.50)., Conclusion: The increased PSR observed in the SNc of PD patients may provide a novel biomarker of PD, possibly associated with an increased macromolecular content. Single-point PSR mapping with reduced variability and shorter scan times relative to the full qMT model appears clinically feasible.

Purpose: To investigate the physical mechanisms associated with the contrast observed in neuromelanin MRI., Methods: Phantoms having different concentrations of synthetic melanins with different degrees of iron loading were examined on a 3 Tesla scanner using relaxometry and quantitative magnetization transfer (MT)., Results: Concentration-dependent T 1 and T 2 shortening was most pronounced for the melanin pigment when combined with iron. Metal-free melanin had a negligible effect on the magnetization transfer spectra. On the contrary, the presence of iron-laden melanins resulted in a decreased magnetization transfer ratio. The presence of melanin or iron (or both) did not have a significant effect on the macromolecular content, represented by the pool size ratio., Conclusion: The primary mechanism underlying contrast in neuromelanin-MRI appears to be the T 1 reduction associated with melanin-iron complexes. The macromolecular content is not significantly influenced by the presence of melanin with or without iron, and thus the MT is not directly affected. However, as T 1 plays a role in determining the MT-weighted signal, the magnetization transfer ratio is reduced in the presence of melanin-iron complexes. Magn Reson Med 78:1790-1800, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

Objectives: To assess the independent prognostic value of standardized uptake value (SUV) and apparent diffusion coefficient (ADC), separately and combined, in order to evaluate if the combination of these two variables allows further prognostic stratification of patients with head and neck squamous cell carcinomas (HNSCC)., Methods: Pretreatment SUV and ADC were calculated in 57 patients with HNSCC. Mean follow-up was 21.3 months. Semiquantitative analysis of primary tumours was performed using SUV maxT/B , ADC mean , ADC min and ADC max . The prognostic value of SUV maxT/B , ADC mean , ADC min and ADC max in predicting disease-free survival (DFS) was evaluated with log-rank test and Cox regression models., Results: Patients with SUV maxT/B ≥5.75 had an overall worse prognosis (p = 0.003). After adjusting for lymph node status and diameter, SUV maxT/B and ADC min were both significant predictors of DFS with hazard ratio (HR) = 10.37 (95 % CI 1.22-87.95) and 3.26 (95 % CI 1.20-8.85) for SUV maxT/B ≥5.75 and ADC min ≥0.58 × 10 -3 mm 2 /s, respectively. When the analysis was restricted to subjects with SUV maxT/B ≥5.75, high ADC min significantly predicted a worse prognosis, with adjusted HR = 3.11 (95 % CI 1.13-8.55)., Conclusions: The combination of SUV maxT/B and ADC min improves the prognostic role of the two separate parameters; patients with high SUV maxT/B and high ADC min are associated with a poor prognosis., Key Points: • High SUV maxT/B is a poor prognostic factor in HNSCC • High ADC min is a poor prognostic factor in HNSCC • In patients with high SUV maxT/B , high ADC min identified those with worse prognosis.

Particle therapy (PT) has shown positive therapeutic results in local control of locally advanced pancreatic lesions. PT effectiveness is highly influenced by target localization accuracy both in space, since the pancreas is located in proximity to radiosensitive vital organs, and in time as it is subject to substantial breathing-related motion. The purpose of this preliminary study was to quantify pancreas range of motion under typical PT treatment conditions. Three common immobilization devices (vacuum cushion, thermoplastic mask, and compressor belt) were evaluated on five male patients in prone and supine positions. Retrospective four-dimensional magnetic resonance imaging data were reconstructed for each condition and the pancreas was manually segmented on each of six breathing phases. A k-means algorithm was then applied on the manually segmented map in order to obtain clusters representative of the three pancreas segments: head, body, and tail. Centers of mass (COM) for the pancreas and its segments were computed, as well as their displacements with respect to a reference breathing phase (beginning exhalation). The median three-dimensional COM displacements were in the range of 3 mm. Latero-lateral and superior-inferior directions had a higher range of motion than the anterior-posterior direction. Motion analysis of the pancreas segments showed slightly lower COM displacements for the head cluster compared to the tail cluster, especially in prone position. Statistically significant differences were found within patients among the investigated setups. Hence a patient-specific approach, rather than a general strategy, is suggested to define the optimal treatment setup in the frame of a millimeter positioning accuracy., (© 2016 The Authors.)

There is a growing interest in identifying neuroimaging-based biomarkers for Parkinson's disease (PD), a progressive neurodegenerative disorder in which the major pathologic substrate is the loss of pigmented dopaminergic neurons in the substantia nigra (SN). Recently, an MRI technique dubbed "neuromelanin-sensitive MRI" (NM-MRI), has been found to provide notable contrast between the SN and surrounding brain tissues with potential applications as biomarker of PD. The contrast in NM-MRI has been associated with magnetization transfer (MT) effects, and thus the goal of this study was to characterize the impact of MT on NM-MRI, and to demonstrate the feasibility of performing quantitative MT (qMT) imaging in human SN. The results of this study demonstrate that high-resolution rapid qMT imaging of the SN can be reliably obtained within reasonable scan times, thereby can be translatable into clinical practice.