Updated 2022 ACC/AHA Guideline Improves Concordance Between TTE and CT in Monitoring Marfan Snydrome and Related Disorders, but Relevant Measurement Differences Remain Frequent.

Background: Patients diagnosed with Marfan syndrome or a related syndrome require frequent aorta monitoring using imaging techniques like transthoracic echocardiography (TTE) and computed tomography (CT). Accurate aortic measurement is crucial, as even slight enlargement (>2 mm) often necessitates surgical intervention. The 2022 ACC/AHA guideline for Aortic Disease Diagnosis and Management includes updated imaging recommendations. We aimed to compare these with the 2010 guideline. Methods: This retrospective study involved 137 patients with Marfan syndrome or a related disorder, undergoing TTE and ECG-triggered CT. Aortic diameter measurements were taken based on the old 2010 guideline (TTE: inner edge to inner edge, CT: external diameter) and the new 2022 guideline (TTE: leading edge to leading edge, CT: internal diameter). Bland-Altman plots compared measurement differences. Results: Using the 2022 guideline significantly reduced differences outside the clinical agreement limit from 49% to 26% for the aortic sinus and from 41% to 29% for the ascending aorta. Mean differences were -0.30 mm for the aortic sinus and +1.12 mm for the ascending aorta using the 2022 guideline, compared to -2.66 mm and +1.21 mm using the 2010 guideline. Conclusion: This study demonstrates for the first time that the 2022 ACC/AHA guideline improves concordance between ECG-triggered CT and TTE measurements in Marfan syndrome patients, crucial for preventing life-threatening aortic complications. However, the frequency of differences >2 mm remains high. Clinical Relevance/Application: Accurate aortic diameter measurement is vital for patients at risk of fatal aortic complications. While the 2022 guideline enhances concordance between imaging modalities, frequent differences >2 mm persist, potentially impacting decisions on aortic repair. The risk of repeat radiation exposure from ECG-triggered CT, considered the 'gold standard', continues to be justified.

Complications of cochlear implants with MRI scans in different body regions: type, frequency and impact.

OBJECTIVES: The aim was to assess the type, frequency and impact of MRI-related complications in patients with cochlear implants (CI) and MRI indications in different body regions. METHODS: For that purpose, the institutional radiology database of a single tertiary hospital was searched for patients with a CI who underwent MRI between 2001 and 2018. The number of MRI examinations and complications were retrieved from the patient record. Examinations were categorized into five distinct body regions or combinations thereof. Records of CI artifacts in the head also included basic information on diagnostic image quality. RESULTS: Out of 1017 MRI database entries (examinations) of patients with a CI, 91 records were after implantation (71 patients) and 66 were attempted (no contraindications, 49 patients). In four cases (4/66, 6.1%), the magnet was dislocated and had to be replaced surgically. Three out of four severe complications occurred for examination regions outside the head. Thirteen MRI examinations were aborted due to pain (19.7%) and one because of artifacts-resulting in 48 scans (72.7%) completed successfully (36 patients). All cranial scans featured device artifacts in all sequences, but the majority of them did not affect proper imaging diagnostics in the respective region. CONCLUSION: This retrospective, single-center analysis of patients with MRI-conditional cochlear implants shows that MRI-related complications were common, at least in models with a fixed magnet, despite appropriate precautions and compliance with the manufacturers' guidelines. MRI examinations of CI patients should therefore be indicated strictly until the exact causes have been clarified.

MRI-targeted biopsy cores from prostate index lesions: assessment and prediction of the number needed.

BACKGROUND: Magnetic resonance imaging (MRI) is used to detect the prostate index lesion before targeted biopsy. However, the number of biopsy cores that should be obtained from the index lesion is unclear. The aim of this study is to analyze how many MRI-targeted biopsy cores are needed to establish the most relevant histopathologic diagnosis of the index lesion and to build a prediction model. METHODS: We retrospectively included 451 patients who underwent 10-core systematic prostate biopsy and MRI-targeted biopsy with sampling of at least three cores from the index lesion. A total of 1587 biopsy cores were analyzed. The core sampling sequence was recorded, and the first biopsy core detecting the most relevant histopathologic diagnosis was identified. In a subgroup of 261 patients in whom exactly three MRI-targeted biopsy cores were obtained from the index lesion, we generated a prediction model. A nonparametric Bayes classifier was trained using the PI-RADS score, prostate-specific antigen (PSA) density, lesion size, zone, and location as covariates. RESULTS: The most relevant histopathologic diagnosis of the index lesion was detected by the first biopsy core in 331 cases (73%), by the second in 66 cases (15%), and by the third in 39 cases (9%), by the fourth in 13 cases (3%), and by the fifth in two cases (<1%). The Bayes classifier correctly predicted which biopsy core yielded the most relevant histopathologic diagnosis in 79% of the subjects. PI-RADS score, PSA density, lesion size, zone, and location did not independently influence the prediction model. CONCLUSION: The most relevant histopathologic diagnosis of the index lesion was made on the basis of three MRI-targeted biopsy cores in 97% of patients. Our classifier can help in predicting the first MRI-targeted biopsy core revealing the most relevant histopathologic diagnosis; however, at least three MRI-targeted biopsy cores should be obtained regardless of the preinterventionally assessed covariates.

Comparison of a High-Pitch Non-ECG-Gated and a Prospective ECG-Gated Protocol for Preprocedural Computed Tomography Imaging Before TAVI/TAVR.

PURPOSE: Preprocedural computed tomography (CT) imaging before transcatheter aortic valve implantation/replacement (TAVI/TAVR) requires high diagnostic accuracy without motion artifacts. The aim of this retrospective study is to compare the image quality of a high-pitch non-electrocardiography (ECG)-gated CT protocol used in patients with atrial tachyarrhythmias with a prospectively ECG-gated CT protocol used in patients with sinus rhythm. MATERIALS AND METHODS: We retrospectively included 108 patients who underwent preprocedural CT imaging before TAVI/TAVR. 52 patients with sinus rhythm were imaged using a prospectively ECG-gated protocol (Group A), and 56 patients with atrial tachyarrhythmias were imaged using the high-pitch non-ECG-gated protocol (Group B). Image quality was rated subjectively by two experienced radiologists and assessed by objective parameters including radiation dose, image noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) at the levels of the aortic root and abdominal aorta. RESULTS: Subjective image quality was equally good with both CT protocols, and interrater agreement was substantial in both groups but tended to be higher in Group B at the level of the aortic root (Group A: κw = 0.644, Group B: κw = 0.741). With the high-pitch non-ECG-gated CT protocol, image noise was significantly increased (p = 0.001), whereas the SNR, CNR, and radiation dose were significantly decreased (p = 0.002, p = 0.003, and p < 0.001, respectively) at the level of the aortic root compared to the prospectively ECG-gated CT protocol. CONCLUSION: The high-pitch non-ECG-gated protocol yields images with similar subjective image quality compared with the prospectively ECG-gated CT protocol and allows motion-free assessment of the aortic root for accurate TAVI/TAVR planning. The high-pitch non-ECG-gated protocol may be used as an alternative for preprocedural CT imaging in patients with atrial tachyarrhythmias. KEY POINTS: · In patients with atrial tachyarrhythmias, a high-pitch non-ECG-gated CT protocol achieves similar subjective image quality compared to a prospective ECG-gated CT protocol.. · At the level of the aortic root, image noise is significantly increased, whereas SNR and CNR are significantly decreased using the high-pitch non-ECG-gated protocol.. · Radiation dose is reduced by 55 % using the high-pitch non-ECG-gated protocol.. CITATION FORMAT: · Shnayien S, Beetz N, Bressem KK et al. Comparison of a High-Pitch Non-ECG-Gated and a Prospective ECG-Gated Protocol for Preprocedural Computed Tomography Imaging Before TAVI/TAVR. Fortschr Röntgenstr 2023; 195: 139 - 147.

Discrepancy of echocardiography and computed tomography in initial assessment and 2-year follow-up for monitoring Marfan syndrome and related disorders.

Patients with Marfan syndrome and related disorders are at risk for aortic dissection and aortic rupture and therefore require appropriate monitoring. Computed tomography (CT) and transthoracic echocardiography (TTE) are routinely used for initial diagnosis and follow-up. The purpose of this study is to compare whole-heart CT and TTE aortic measurement for initial work-up, 2-year follow-up, and detection of progressive aortic enlargement. This retrospective study included 95 patients diagnosed with Marfan syndrome or a related disorder. All patients underwent initial work-up including aortic diameter measurement using both electrocardiography-triggered whole-heart CT and TTE. Forty-two of these patients did not undergo aortic repair after initial work-up and were monitored by follow-up imaging within 2 years. Differences between the two methods for measuring aortic diameters were compared using Bland-Altman plots. The acceptable clinical limit of agreement (acLOA) for initial work-up, follow-up, and progression within 2 years was predefined as < ± 2 mm. Bland-Altman analysis revealed a small bias of 0.2 mm with wide limits of agreement (LOA) from + 6.3 to - 5.9 mm for the aortic sinus and a relevant bias of - 1.6 mm with wide LOA from + 5.6 to - 8.9 mm for the ascending aorta. Follow-up imaging yielded a small bias of 0.5 mm with a wide LOA from + 6.7 to - 5.8 mm for the aortic sinus and a relevant bias of 1.1 mm with wide LOA from + 8.1 to - 10.2 mm for the ascending aorta. Progressive aortic enlargement at follow-up was detected in 57% of patients using CT and 40% of patients using TTE. Measurement differences outside the acLOA were most frequently observed for the ascending aorta. Whole-heart CT and TTE measurements show good correlation, but the frequency of measurement differences outside the acLOA is high. TTE systematically overestimates aortic diameters. Therefore, whole-heart CT may be preferred for aortic monitoring of patients with Marfan syndrome and related disorders. TTE remains an indispensable imaging tool that provides additional information not available with CT.

Influence of Baseline CT Body Composition Parameters on Survival in Patients with Pancreatic Adenocarcinoma.

Pancreatic cancer is the seventh leading cause of cancer death in both sexes. The aim of this study is to analyze baseline CT body composition using artificial intelligence to identify possible imaging predictors of survival. We retrospectively included 103 patients. First, the presence of surgical treatment and cut-off values for sarcopenia and obesity served as independent variates. Second, the presence of surgery, subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle index (SMI) served as independent variates. Cox regression analysis was performed for 1-year, 2-year, and 3-year survival. Possible differences between patients undergoing surgical versus nonsurgical treatment were analyzed. Presence of surgery significantly predicted 1-year, 2-year, and 3-year survival (p = 0.01, <0.001, and <0.001, respectively). Across the follow-up periods of 1-year, 2-year, and 3-year survival, the presence of sarcopenia became an equally important predictor of survival (p = 0.25, 0.07, and <0.001, respectively). Additionally, increased VAT predicted 2-year and 3-year survival (p = 0.02 and 0.04, respectively). The impact of sarcopenia on 3-year survival was higher in the surgical treatment group (p = 0.02 and odds ratio = 2.57) compared with the nonsurgical treatment group (p = 0.04 and odds ratio = 1.92). Fittingly, a lower SMI significantly affected 3-year survival only in patients who underwent surgery (p = 0.02). Especially if surgery is performed, AI-derived sarcopenia and reduced muscle mass are unfavorable imaging predictors.

Inter-Reader Variability Using PI-RADS v2 Versus PI-RADS v2.1: Most New Disagreement Stems from Scores 1 and 2.

PURPOSE: To analyze possible differences in the inter-reader variability between PI-RADS version 2 (v2) and version 2.1 (v2.1) for the classification of prostate lesions using multiparametric MRI (mpMRI) of the prostate. METHODS: In this retrospective and randomized study, 239 annotated and histopathologically correlated prostate lesions (104 positive and 135 negative for prostate cancer) were rated twice by three experienced uroradiologists using PI-RADS v2 and v2.1 with an interval of at least two months between readings. Results were tabulated across readers and reading timepoints and inter-reader variability was determined using Fleiss' kappa (κ). Thereafter, an additional analysis of the data was performed in which PI-RADS scores 1 and 2 were combined, as they have the same clinical consequences. RESULTS: PI-PI-RADS v2.1 showed better inter-reader agreement in the peripheral zone (PZ), but poorer inter-reader agreement in the transition zone (TZ) (PZ: κ = 0.63 vs. κ = 0.58; TZ: κ = 0.47 vs. κ = 0.57). When PI-RADS scores 1 and 2 were combined, the use of PI-RADS v2.1 resulted in almost perfect inter-reader agreement in the PZ and substantial agreement in the TZ (PZ: κ = 0.81; TZ: κ = 0.80). CONCLUSION: PI-RADS v2.1 improves inter-reader agreement in the PZ. New differences in inter-reader agreement were mainly the result of the assignment of PI-RADS v2.1 scores 1 and 2 to lesions in the TZ. Combining scores 1 and 2 improved inter-reader agreement both in the TZ and in the PZ, indicating that refined definitions may be warranted for these PI-RADS scores. KEY POINTS: · PI-RADSv2.1 improves inter-reader agreement in the PZ but not in the TZ.. · New differences derived from PI-RADSv2.1 scores 1 and 2 in the TZ.. · Combined PI-RADSv2.1 scores of 1 and 2 yielded better inter-reader agreement.. · PI-RADSv2.1 appears to provide more precise description of lesions in the PZ.. · Improved inter-reader agreement in the PZ stresses the importance of appropriate lexicon description.. CITATION FORMAT: · Beetz N, Haas M, Baur A et al. Inter-Reader Variability Using PI-RADS v2 Versus PI-RADS v2.1: Most New Disagreement Stems from Scores 1 and 2. Fortschr Röntgenstr 2022; 194: 852 - 861.

Effects of Artificial Intelligence-Derived Body Composition on Kidney Graft and Patient Survival in the Eurotransplant Senior Program.

The Eurotransplant Senior Program allocates kidneys to elderly transplant patients. The aim of this retrospective study is to investigate the use of computed tomography (CT) body composition using artificial intelligence (AI)-based tissue segmentation to predict patient and kidney transplant survival. Body composition at the third lumbar vertebra level was analyzed in 42 kidney transplant recipients. Cox regression analysis of 1-year, 3-year and 5-year patient survival, 1-year, 3-year and 5-year censored kidney transplant survival, and 1-year, 3-year and 5-year uncensored kidney transplant survival was performed. First, the body mass index (BMI), psoas muscle index (PMI), skeletal muscle index (SMI), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) served as independent variates. Second, the cut-off values for sarcopenia and obesity served as independent variates. The 1-year uncensored and censored kidney transplant survival was influenced by reduced PMI (p = 0.02 and p = 0.03, respectively) and reduced SMI (p = 0.01 and p = 0.03, respectively); 3-year uncensored kidney transplant survival was influenced by increased VAT (p = 0.04); and 3-year censored kidney transplant survival was influenced by reduced SMI (p = 0.05). Additionally, sarcopenia influenced 1-year uncensored kidney transplant survival (p = 0.05), whereas obesity influenced 3-year and 5-year uncensored kidney transplant survival. In summary, AI-based body composition analysis may aid in predicting short- and long-term kidney transplant survival.

CT Body Composition of Sarcopenia and Sarcopenic Obesity: Predictors of Postoperative Complications and Survival in Patients with Locally Advanced Esophageal Adenocarcinoma.

BACKGROUND: To assess the impact of body composition imaging biomarkers in computed tomography (CT) on the perioperative morbidity and survival after surgery of patients with esophageal cancer (EC). METHODS: Eighty-five patients who underwent esophagectomy for locally advanced EC after neoadjuvant therapy between 2014 and 2019 were retrospectively enrolled. Pre- and postoperative CT scans were used to assess the body composition imaging biomarkers (visceral (VAT) and subcutaneous adipose tissue (SAT) areas, psoas muscle area (PMA) and volume (PMV), total abdominal muscle area (TAMA)). Sarcopenia was defined as lumbar skeletal muscle index (LSMI) ≤38.5 cm2/m2 in women and ≤52.4 cm2/m2 in men. Patients with a body mass index (BMI) of ≥30 were considered obese. These imaging biomarkers were correlated with major complications, anastomotic leakage, postoperative pneumonia, duration of postoperative hospitalization, disease-free survival (DFS), and overall survival (OS). RESULTS: Preoperatively, sarcopenia was identified in 58 patients (68.2%), and sarcopenic obesity was present in 7 patients (8.2%). Sarcopenic patients were found to have an elevated risk for the occurrence of major complications (OR: 2.587, p = 0.048) and prolonged hospitalization (32 d vs. 19 d, p = 0.040). Patients with sarcopenic obesity had a significantly higher risk for postoperative pneumonia (OR: 6.364 p = 0.018) and a longer postoperative hospital stay (71 d vs. 24 d, p = 0.021). Neither sarcopenia nor sarcopenic obesity was an independent risk factor for the occurrence of anastomotic leakage (p > 0.05). Low preoperative muscle biomarkers (PMA and PMV) and their decrease (ΔPMV and ΔTAMA) during the follow-up period significantly correlated with shorter DFS and OS (p = 0.005 to 0.048). CONCLUSION: CT body composition imaging biomarkers can identify high-risk patients with locally advanced esophageal cancer undergoing surgery. Sarcopenic patients have a higher risk of major complications, and patients with sarcopenic obesity are more prone to postoperative pneumonia. Sarcopenia and sarcopenic obesity are both subsequently associated with a prolonged hospitalization. Low preoperative muscle mass and its decrease during the postoperative follow-up are associated with lower DFS and OS.

Artificial intelligence-based analysis of body composition in Marfan: skeletal muscle density and psoas muscle index predict aortic enlargement.

BACKGROUND: Patients with Marfan syndrome are at risk for aortic enlargement and are routinely monitored by computed tomography (CT) imaging. The purpose of this study is to analyse body composition using artificial intelligence (AI)-based tissue segmentation in patients with Marfan syndrome in order to identify possible predictors of progressive aortic enlargement. METHODS: In this study, the body composition of 25 patients aged ≤50 years with Marfan syndrome and no prior aortic repair was analysed at the third lumbar vertebra (L3) level from a retrospective dataset using an AI-based software tool (Visage Imaging). All patients underwent electrocardiography-triggered CT of the aorta twice within 2 years for suspected progression of aortic disease, suspected dissection, and/or pre-operative evaluation. Progression of aortic enlargement was defined as an increase in diameter at the aortic sinus or the ascending aorta of at least 2 mm. Patients meeting this definition were assigned to the 'progressive aortic enlargement' group (proAE group) and patients with stable diameters to the 'stable aortic enlargement' group (staAE group). Statistical analysis was performed using the Mann-Whitney U test. Two possible body composition predictors of aortic enlargement-skeletal muscle density (SMD) and psoas muscle index (PMI)-were analysed further using multivariant logistic regression analysis. Aortic enlargement was defined as the dependent variant, whereas PMI, SMD, age, sex, body mass index (BMI), beta blocker medication, and time interval between CT scans were defined as independent variants. RESULTS: There were 13 patients in the proAE group and 12 patients in the staAE group. AI-based automated analysis of body composition at L3 revealed a significantly increased SMD measured in Hounsfield units (HUs) in patients with aortic enlargement (proAE group: 50.0 ± 8.6 HU vs. staAE group: 39.0 ± 15.0 HU; P = 0.03). PMI also trended towards higher values in the proAE group (proAE group: 6.8 ± 2.3 vs. staAE group: 5.6 ± 1.3; P = 0.19). Multivariate logistic regression revealed significant prediction of aortic enlargement for SMD (P = 0.05) and PMI (P = 0.04). CONCLUSIONS: Artificial intelligence-based analysis of body composition at L3 in Marfan patients is feasible and easily available from CT angiography. Analysis of body composition at L3 revealed significantly higher SMD in patients with progressive aortic enlargement. PMI and SMD significantly predicted aortic enlargement in these patients. Using body composition as a predictor of progressive aortic enlargement may contribute information for risk stratification regarding follow-up intervals and the need for aortic repair.

Diagnostic performance of PI-RADS version 2.1 compared to version 2.0 for detection of peripheral and transition zone prostate cancer.

The purpose of this study is to compare diagnostic performance of Prostate Imaging Reporting and Data System (PI-RADS) version (v) 2.1 and 2.0 for detection of Gleason Score (GS) ≥ 7 prostate cancer on MRI. Three experienced radiologists provided PI-RADS v2.0 scores and at least 12 months later v2.1 scores on lesions in 333 prostate MRI examinations acquired between 2012 and 2015. Diagnostic performance was assessed retrospectively by using MRI/transrectal ultrasound fusion biopsy and 10-core systematic biopsy as the reference. From a total of 359 lesions, GS ≥ 7 tumor was present in 135 lesions (37.60%). Area under the ROC curve (AUC) revealed slightly lower values for peripheral zone (PZ) and transition zone (TZ) scoring in v2.1, but these differences did not reach statistical significance. A significant number of score 2 lesions in the TZ were downgraded to score 1 in v2.1 showing 0% GS ≥ 7 tumor (0/11). The newly introduced diffusion-weighted imaging (DWI) upgrading rule in v2.1 was applied in 6 lesions from a total of 143 TZ lesions (4.2%). In summary, PI-RADS v2.1 showed no statistically significant differences in overall diagnostic performance of TZ and PZ scoring compared to v2.0. Downgraded BPH nodules showed favorable cancer frequencies. The new DWI upgrading rule for TZ lesions was applied in only few cases.

Radiation Dose Reduction in Preprocedural CT Imaging for TAVI/TAVR Using a Novel 3-Phase Protocol: A Single Institution's Experience.

PURPOSE: To retrospectively investigate the effectiveness of a novel 3-phase protocol for computed tomography (CT) before transcatheter aortic valve implantation/transcatheter aortic valve replacement (TAVI/TAVR) in terms of radiation dose and image quality. MATERIALS AND METHODS: A total of 107 nonrandomized patients (81 ±â€Š7.4 years) scheduled for TAVI/TAVR underwent preprocedural CT on an 80-row CT scanner. 55 patients underwent a combined ECG-synchronized spiral scan of the chest and non-ECG-synchronized spiral scan of the abdomen/pelvis as recommended by the Society of Cardiovascular Computed Tomography (SCCT). 52 patients underwent an updated 3-phase variable helical pitch (vHP3) protocol combining a non-ECG-synchronized spiral scan of the upper thoracic aperture, followed by a prospective ECG-synchronized spiral scan of the heart, and a non-ECG-synchronized abdominal/pelvic spiral scan. The radiation dose was determined from an automatically generated protocol based on the CT dose index (CTDI). Objective image quality in terms of vessel attenuation and image noise was measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Subjective image quality was evaluated using a 4-point scale and compared for interrater agreement using Cohen's weighted kappa coefficient (κw). All data were compared and statistically analyzed. RESULTS: Use of the novel 3-phase vHP3 protocol reduced the dose-length product (DLP) from 1256.58 ±â€Š619.05 mGy*cm to 790.90 ±â€Š238.15 mGy*cm, reducing the effective dose (E) from 21.36 ±â€Š10.52 mSv to 13.44 ±â€Š4.05 mSv and size-specific dose estimates (SSDE) from 20.85 ±â€Š7.29 mGy to 13.84 ± 2.94 mGy (p < 0.001). There were no significant differences in objective and subjective image quality between the two protocols and between the two readers. CONCLUSION: The novel 3-phase vHP3 protocol significantly reduces the radiation dose of preprocedural TAVI/TAVR CT without a loss of image quality. KEY POINTS: · The use of a novel 3-phase protocol for preprocedural TAVI/TAVR CT reduces radiation dose by 37 % compared to a combined ECG-synchronized and non-ECG-synchronized spiral CT protocol.. · Objective image quality remains unaffected as image noise, SNR, and CNR did not differ significantly between the two protocols. The average attenuation of the aortic root and abdominal aorta exceeded 450 HU in both protocols.. · The average subjective image quality ratings were good to excellent for both protocols with almost perfect to substantial interrater agreement.. CITATION FORMAT: · Shnayien S, Bressem KK, Beetz NL et al. Radiation Dose Reduction in Preprocedural CT Imaging for TAVI/TAVR Using a Novel 3-Phase Protocol: A Single Institution's Experience. Fortschr Röntgenstr 2020; 192: 1174 - 1182.

[Artificial intelligence and radiomics in MRI-based prostate diagnostics]. / Künstliche Intelligenz und Radiomics in der MRT-basierten Prostatadiagnostik.

CLINICAL/METHODICAL ISSUE: In view of the diagnostic complexity and the large number of examinations, modern radiology is challenged to identify clinically significant prostate cancer (PCa) with high sensitivity and specificity. Meanwhile overdiagnosis and overtreatment of clinically nonsignificant carcinomas need to be avoided. STANDARD RADIOLOGICAL METHODS: Increasingly, international guidelines recommend multiparametric magnetic resonance imaging (mpMRI) as first-line investigation in patients with suspected PCa. METHODICAL INNOVATIONS: Image interpretation according to the PI-RADS criteria is limited by interobserver variability. Thus, rapid developments in the field of automated image analysis tools, including radiomics and artificial intelligence (AI; machine learning, deep learning), give hope for further improvement in patient care. PERFORMANCE: AI focuses on the automated detection and classification of PCa, but it also attempts to stratify tumor aggressiveness according to the Gleason score. Recent studies present good to very good results in radiomics or AI-supported mpMRI diagnosis. Nevertheless, these systems are not widely used in clinical practice. ACHIEVEMENTS AND PRACTICAL RECOMMENDATIONS: In order to apply these innovative technologies, a growing awareness for the need of structured data acquisition, development of robust systems and an increased acceptance of AI as diagnostic support are needed. If AI overcomes these obstacles, it may play a key role in the quantitative and reproducible image-based diagnosis of ever-increasing prostate MRI examination volumes.