Barbed sutures and skin adhesives improve wound closure in hip and knee arthroplasty.

PURPOSE: This study aimed to formulate evidence-based recommendations for optimising wound management in hip and knee arthroplasty by exploring alternative methods such as barbed sutures and skin adhesives. METHODS: A Delphi panel, comprising seven orthopaedic surgeons, one musculoskeletal infectious disease specialist, and one health economics expert, was convened to evaluate the use of barbed sutures and skin adhesives for wound closure in hip and knee arthroplasty. Two systematic reviews informed the development of questionnaires, with panelists ranking their agreement on statements using a 5-point Likert scale. Consensus was achieved if ≥75% agreement. Unresolved statements were revisited in a second round. RESULTS: Consensus was reached on 11 statements, providing evidence-based recommendations. The expert panel advocates for a multilayer watertight technique using barbed sutures to prevent surgical site infections (SSI), reduce complications, shorten surgical times, optimise resources and improve cosmetic appearance. For skin closure, the panel recommends topical adhesives to decrease wound dehiscence, enhance cosmetic appearance, promote patient compliance, prevent SSIs, and optimise resources. CONCLUSION: The Delphi consensus by Italian total joint arthroplasty experts underscores the pivotal role of barbed sutures and skin adhesives in optimising outcomes. While guiding clinical decision-making, these recommendations are not prescriptive and should be adapted to local practices. The study encourages further research to enhance current evidence. LEVEL OF EVIDENCE: Level III.

Hepatobiliary-specific magnetic resonance contrast agents: role in biliary trauma.

Non-iatrogenic traumatic bile duct injuries (NI-TBIs) are a rare complication after abdominal trauma, with an estimated prevalence of 2.8-7.4% in patients underwent blunt liver injuries. They may be overlooked in patients with extensive multi-organ trauma, particularly hepatic, splenic and duodenal injuries, which have a prevalence of 91%, 54% and 54%, respectively. Whole body contrast-enhanced computed tomography (CE-CT) represents the examination of choice in polytraumatized hemodynamically stable patients, as it allows a comprehensive evaluation of vascular, parenchymal, bone and soft tissues injuries, but the diagnosis of any biliary leaks is limited to the evaluation of nonspecific imaging findings and on findings evolution in the follow-up, such as the progressive growth of fluid collections. Furthermore, biliary complications, such as the occurrence of biloma or biliary peritonitis, may become manifest several days after the initial trauma, often with unspecific progressive signs and symptoms. Although CT and ultrasonography can suggest bile leaks based on several nonspecific imaging findings (e.g., fluid collections), magnetic resonance imaging (MRI) using hepatobiliary contrast agents helps to identify the site and entity of post-traumatic biliary disruption. Indeed, MRI allows to obtain cholangiographic sequences that may show post-traumatic active bile leakage and cysto-biliary communications by direct visualisation of contrast material extravasation into fluid collections, increasing the preoperative accuracy of NI-TBIs. Few data are available about MRI use in the follow-up of trauma with NI-TBI management. So, in the present mini review, its role is reviewed and our preliminary experience in this field is reported.

Prediction of placenta accreta spectrum in patients with placenta previa using a clinical, US and MRI combined model: A retrospective study with external validation.

PURPOSE: To build and validate a predictive model of placental accreta spectrum (PAS) in patients with placenta previa (PP) combining clinical risk factors (CRF) with US and MRI signs. METHOD: Our retrospective study included patients with PP from two institutions. All patients underwent US and MRI examinations for suspicion of PAS. CRF consisting of maternal age, cesarean section number, smoking and hypertension were retrieved. US and MRI signs suggestive of PAS were evaluated. Logistic regression analysis was performed to identify CRF and/or US and MRI signs associated with PAS considering histology as the reference standard. A nomogram was created using significant CRF and imaging signs at multivariate analysis, and its diagnostic accuracy was measured using the area under the binomial ROC curve (AUC), and the cut-off point was determined by Youden's J statistic. RESULTS: A total of 171 patients were enrolled from two institutions. Independent predictors of PAS included in the nomogram were: 1) smoking and number of previous CS among CRF; 2) loss of the retroplacental clear space at US; 3) intraplacental dark bands, focal interruption of the myometrial border and placental bulging at MRI. A PAS-prediction nomogram was built including these parameters and an optimal cut-off of 14.5 points was identified, showing the highest sensitivity (91%) and specificity (88%) with an AUC value of 0.95 (AUC of 0.80 in the external validation cohort). CONCLUSION: A nomogram-based model combining CRF with US and MRI signs might help to predict PAS in PP patients, with MRI contributing more than US as imaging evaluation.

Abdominal compartment syndrome: what radiologist needs to know.

The intra-abdominal hypertension (IAH) and the abdominal compartment syndrome (ACS) are life-threatening conditions with a significant rate of mortality; therefore, early detection is paramount in their optimal management. IAH is diagnosed when the intra-abdominal pressure (IAP) is more than 12 mmHg. It can occur when the intra-abdominal volume increases (ileus, ascites, trauma, pancreatitis, etc.) and/or the abdominal wall compliance decreases. IAH can cause decreased venous flow, low cardiac output, renal impairment, and decreased respiratory compliance. Consequently, these complications can lead to multiple organ failure and induce the abdominal compartment syndrome (ACS) when IAP rises above 20 mmHg. The diagnosis is usually made with intravesical pressure measurement. However, this measurement was not always possible to obtain; therefore, alternative diagnostic techniques should be considered. In this setting, computed tomography (CT) may play a crucial role, allowing the detection and characterization of pathological conditions that may lead to IAH. This review is focused on the pathogenesis, clinical features, and radiological findings of ACS, because their presence allows radiologists to raise the suspicion of IAH/ACS in critically ill patients, guiding the most appropriate treatment.

An update on pyelonephritis: role of contrast enhancement ultrasound (CEUS).

Acute pyelonephritis (APN) is a bacterial infection causing inflammation of the kidneys. Diagnosis is usually based on clinical and laboratory findings. Imaging is required if a complication is suspected in acute pyelonephritis to assess the nature and extent of the lesions and to detect underlying causes. CT represents the current imaging modality of choice in clinical practice. CEUS is an alternative that has been proven to be equally accurate in the detection of acute pyelonephritis renal lesions. CEUS allows us to distinguish small simple nephritic involvement from abscess complications and to follow their evolution over time during antibiotic therapy. The absence of ionizing radiation and the lack of nephrotoxicity make CEUS an ideal tool in the study of pyelonephritis.

Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges.

Imaging plays a crucial role in the management of oncologic patients, from the initial diagnosis to staging and treatment response monitoring. Recently, it has been suggested that its importance could be further increased by accessing a new layer of previously hidden quantitative data at the pixel level. Using a multi-step process, radiomics extracts potential biomarkers from medical images that could power decision support tools. Despite the growing interest and rising number of research articles being published, radiomics is still far from fulfilling its promise of guiding oncologic imaging toward personalized medicine. This is, at least partly, due to the heterogeneous methodological quality in radiomic research, caused by the complexity of the analysis pipelines. In this review, we aim to disentangle this complexity with a stepwise approach. Specifically, we focus on challenges to face during image preprocessing and segmentation, how to handle imbalanced classes and avoid information leaks, as well as strategies for the proper validation of findings.

Hybrid Cementation Technique Using the New Modular System for Aseptic Knee Arthroplasty Revision Surgery.

Background: To evaluate the clinical and radiological outcomes of aseptic revision of total knee arthroplasty (TKA) using the Vanguard 360 Revision Knee System with the hybrid cementation technique. Methods: Between January 2014 and October 2016, nineteen aseptic revision TKAs were carried out with the Vanguard 360 Revision Knee System (Zimmer-Biomet, Warsaw, IN, USA) performed by two different surgeons. The patients were evaluated clinically and radiographically at one, six, and twelve months after surgery and yearly thereafter. Functional outcomes were assessed according to the range of motion (ROM), knee society knee score (KSKS) and knee society function score (KSFS). Radiological evaluations were performed using the hip-knee-ankle angle (HKA), weight-bearing anteroposterior view, latero-lateral view, Rosenberg x-rays of the knee and skyline patellar x-rays. A triple-phase technetium bone scan was performed on all the patients complaining of knee pain after one year from surgery. Results: Clinical and radiological results including KSKS, KSFS, ROM and HKA angle improved after revision of TKA with a statistically significant difference (p <0.05). There were seven revisions of the CCK prosthesis due to persistent pain. Conclusion: Patients who underwent revision of TKA using the Vanguard 360 with the hybrid cementation technique had a failure rate of 36.8% at a mean time of 29 months due to aseptic loosening. Further studies are required to analyse the role of cementation in detail to prevent this complication.

Qualitative Heterogeneous Signal Drop on Chemical Shift (CS) MR Imaging: Correlative Quantitative Analysis between CS Signal Intensity Index and Contrast Washout Parameters Using T1-Weighted Sequences.

The aim of this study was to calculate MRI quantitative parameters extracted from chemical-shift (CS) and dynamic contrast-enhanced (DCE) T1-weighted (T1-WS) images of adrenal lesions (AL) with qualitative heterogeneous signal drop on CS T1-WS and compare them to those of AL with homogeneous or no signal drop on CS T1-WS. On 3 T MRI, 65 patients with a total of 72 AL were studied. CS images were qualitatively assessed for grouping AL as showing homogeneous (Group 1, n = 19), heterogeneous (Group 2, n = 23), and no (Group 3, n = 30) signal drop. Histopathology or follow-up data served as reference standard to classify AL. ROIs were drawn both on CS and DCE images to obtain adrenal CS signal intensity index (ASII), absolute (AWO), and relative washout (RWO) values. Quantitative parameters (QP) were compared with ANOVA analysis and post hoc Dunn's test. The performance of QP to classify AL was assessed with receiver operating characteristic analysis. CS ASII values were significantly different among the three groups (p < 0.001) with median values of 71%, 53%, and 3%, respectively. AWO/RWO values were similar in Groups 1 (adenomas) and 2 (benign AL) but significantly (p < 0.001) lower in Group 3 (20 benign AL and 10 malignant AL). With cut-offs, respectively, of 60% (Group 1 vs. 2), 20% (Group 2 vs. 3), and 37% (Group 1 vs. 3), CS ASII showed areas under the curve of 0.85, 0.96, and 0.93 for the classification of AL, overall higher than AWO/RWO. In conclusion, AL with qualitative heterogeneous signal drop at CS represent benign AL with QP by DCE sequence similar to those of AL with homogeneous signal drop at CS, but different to those of AL with no signal drop at CS; ASII seems to be the only quantitative parameter able to differentiate AL among the three different groups.

Radiomics and machine learning applications in rectal cancer: Current update and future perspectives.

The high incidence of rectal cancer in both sexes makes it one of the most common tumors, with significant morbidity and mortality rates. To define the best treatment option and optimize patient outcome, several rectal cancer biological variables must be evaluated. Currently, medical imaging plays a crucial role in the characterization of this disease, and it often requires a multimodal approach. Magnetic resonance imaging is the first-choice imaging modality for local staging and restaging and can be used to detect high-risk prognostic factors. Computed tomography is widely adopted for the detection of distant metastases. However, conventional imaging has recognized limitations, and many rectal cancer characteristics remain assessable only after surgery and histopathology evaluation. There is a growing interest in artificial intelligence applications in medicine, and imaging is by no means an exception. The introduction of radiomics, which allows the extraction of quantitative features that reflect tumor heterogeneity, allows the mining of data in medical images and paved the way for the identification of potential new imaging biomarkers. To manage such a huge amount of data, the use of machine learning algorithms has been proposed. Indeed, without prior explicit programming, they can be employed to build prediction models to support clinical decision making. In this review, current applications and future perspectives of artificial intelligence in medical imaging of rectal cancer are presented, with an imaging modality-based approach and a keen eye on unsolved issues. The results are promising, but the road ahead for translation in clinical practice is rather long.

Prediction of placenta accreta spectrum in patients with placenta previa using clinical risk factors, ultrasound and magnetic resonance imaging findings.

OBJECTIVES: To predict placental accreta spectrum (PAS) in patients with placenta previa (PP) evaluating clinical risk factors (CRF), ultrasound (US) and magnetic resonance imaging (MRI) findings. METHODS: Seventy patients with PP were retrospectively selected. CRF were retrieved from medical records. US and MRI images were evaluated to detect imaging signs suggestive of PAS. Univariable analysis was performed to identify CRF, US and MRI signs associated with PAS considering histology as standard of reference. Receiver operating characteristic curve (ROC) analysis was performed, and the area under the curve (AUC) was calculated. Multivariable analysis was also performed. RESULTS: At univariable analysis, the number of previous cesarean section, smoking, loss of the retroplacental clear space, myometrial thinning < 1 mm, placental lacunae, intraplacental dark bands (IDB), focal interruption of myometrial border (FIMB) and abnormal vascularity were statistically significant. The AUC in predicting PAS progressively increased using CRF, US and MRI signs (0.69, 0.79 and 0.94, respectively; p < 0.05); the accuracy of MRI alone was similar to that obtained combining CRF, US and MRI variables (AUC = 0.97) and was significantly higher (p < 0.05) than that combining CRF and US (AUC = 0.83). Multivariable analysis showed that only IDB (p = 0.012) and FIMB (p = 0.029) were independently associated with PAS. CONCLUSIONS: MRI is the best modality to predict PAS in patients with PP independently from CRF and/or US finding. It is reasonable to propose the combined assessment of CRF and US as the first diagnostic level to predict PAS, sparing MRI for selected cases in which US findings are uncertain for PAS.

Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions.

OBJECTIVES: We aimed to assess the performance of radiomics and machine learning (ML) for classification of non-cystic benign and malignant breast lesions on ultrasound images, compare ML's accuracy with that of a breast radiologist, and verify if the radiologist's performance is improved by using ML. METHODS: Our retrospective study included patients from two institutions. A total of 135 lesions from Institution 1 were used to train and test the ML model with cross-validation. Radiomic features were extracted from manually annotated images and underwent a multistep feature selection process. Not reproducible, low variance, and highly intercorrelated features were removed from the dataset. Then, 66 lesions from Institution 2 were used as an external test set for ML and to assess the performance of a radiologist without and with the aid of ML, using McNemar's test. RESULTS: After feature selection, 10 of the 520 features extracted were employed to train a random forest algorithm. Its accuracy in the training set was 82% (standard deviation, SD, ± 6%), with an AUC of 0.90 (SD ± 0.06), while the performance on the test set was 82% (95% confidence intervals (CI) = 70-90%) with an AUC of 0.82 (95% CI = 0.70-0.93). It resulted in being significantly better than the baseline reference (p = 0.0098), but not different from the radiologist (79.4%, p = 0.815). The radiologist's performance improved when using ML (80.2%), but not significantly (p = 0.508). CONCLUSIONS: A radiomic analysis combined with ML showed promising results to differentiate benign from malignant breast lesions on ultrasound images. KEY POINTS: • Machine learning showed good accuracy in discriminating benign from malignant breast lesions • The machine learning classifier's performance was comparable to that of a breast radiologist • The radiologist's accuracy improved with machine learning, but not significantly.

Handcrafted MRI radiomics and machine learning: Classification of indeterminate solid adrenal lesions.

PURPOSE: To assess a radiomic machine learning (ML) model in classifying solid adrenal lesions (ALs) without fat signal drop on chemical shift (CS) as benign or malignant. METHOD: 55 indeterminate ALs (21 lipid poor adenomas, 15 benign pheocromocytomas, 1 oncocytoma, 12 metastases, 6 primary tumors) showing no fat signal drop on CS were retrospectively included. Manual 3D segmentation on T2-weighted and CS images was performed for subsequent radiomic feature extraction. After feature stability testing and an 80-20% train-test split, the train set was balanced via oversampling. Following a multi-step feature selection, an Extra Trees model was tuned with 5-fold stratified cross-validation in the train set and then tested on the hold-out test set. RESULTS: A total of 3396 features were extracted from each AL, of which 133 resulted unstable while none had low variance (< 0.01). Highly correlated (r > 0.8) features were also excluded, leaving 440 parameters. Among these, Support Vector Machine 5-fold stratified cross-validated recursive feature elimination selected a subset of 6 features. ML obtained a cross-validation accuracy of 0.94 on the train and 0.91 on the test sets. Precision, recall and F1 score were respectively 0.92, 0.91 and 0.91. CONCLUSIONS: Our MRI handcrafted radiomics and ML pipeline proved useful to characterize benign and malignant solid indeterminate adrenal lesions.

Clinically Significant Prostate Cancer Detection With Biparametric MRI: A Systematic Review and Meta-Analysis.

OBJECTIVE. The purpose of this study was to perform a systematic review and a meta-analysis of diagnostic accuracy studies that used biparametric MRI (bpMRI) for the detection of clinically significant prostate cancer (csPCa). MATERIALS AND METHODS. Multiple medical databases were systematically searched to identify articles using bpMRI for csPCa detection. Sensitivity, specificity, PPV, and NPV were calculated for each study after enough data were extracted to create a 2 × 2 contingency table. Risk of bias was assessed using the QUADAS-2 tool. Meta-analyses based on bivariate random-effects methods were used to calculate pooled sensitivity, specificity, and summary ROC (SROC) curves. A meta-regression analysis was performed to assess heterogeneity sources. RESULTS. A total of 17 studies (3964 patients) that adopted PI-RADS or other scoring systems were included. Sensitivity, specificity, positive likelihood ratio (LR), negative LR, and diagnostic odds ratio of bpMRI in the detection of csPCa were 0.83 (95% CI, 0.76-0.88), 0.71 (95% CI, 0.63-0.79), 2.9 (95% CI, 2.3-3.7), 0.24 (95% CI, 0.17-0.33), and 12 (95% CI, 8-19), respectively, with an area under the SROC curve of 0.84 (95% CI, 0.81-0.87). The overall quality of the included studies was heterogeneous. CONCLUSION. Our results confirm the feasibility of bpMRI for the detection of csPCa and for reducing acquisition time, patient discomfort, and costs. Nevertheless, the available studies proved to be heterogeneous, indicating a need for a more robust validation of this imaging protocol and a standardization of prostate bpMRI acquisition and reporting.

Prostate Volume Estimation on MRI: Accuracy and Effects of Ellipsoid and Bullet-Shaped Measurements on PSA Density.

RATIONALE AND OBJECTIVES: PSA density (PSAd), an important decision-making parameter for patients with suspected prostate cancer (PCa), is dependent on magnetic resonance imaging prostate volume (PV) estimation. We aimed to compare the accuracy of the ellipsoid and bullet-shaped formulas with manual whole-gland segmentation as reference standard and to evaluate the corresponding PSAd diagnostic accuracy in predicting clinically significant PCa. MATERIALS AND METHODS: We retrospectively analysed 195 patients with suspected PCa who underwent magnetic resonance imaging and prostate biopsy. Patients with PCa were categorized according to ISUP score. PV and corresponding PSAd were calculated with manual segmentation (mPV and mPSAd) as well as with ellipsoid (ePV and ePSAd) and bullet-shaped (bPV and bPSAd) formulas. Inter and intra-reader reproducibility were assessed with Lin's concordance correlation coefficient and the intraclass correlation coefficient (ICC). A 2-way analysis of variance with post-hoc Bonferroni test was used for assessing PV differences. Predictive values of PSAd calculated with different methods for detecting clinically significant PCa were evaluated by receiver operating characteristic curve analysis and Youden's index. RESULTS: Both intra (ρ = 0.99, ICC = 0.99) and inter-reader (ρ = 0.98, ICC = 0.98) reproducibility were excellent. No significant difference was found between ePV and reference standard (p = 1.00). bPV was significantly different from both (p = 0.00). PSAd (mPSAd/ePSAd cut-off ≥ 0.15, bPSAd cut-off ≥ 0.12) had sensitivity = 69-70%, specificity = 72-75%, areas under the curve = 0.757-0.760 (p = 0.70-0.88). CONCLUSIONS: Our work shows that when using bullet-shaped formula, a different PSAd cut-off must be considered to avoid PCa under-diagnosis and inaccurate risk-stratification.

Dual energy computed tomography evaluation of skeletal traumas.

Skeletal traumas are among the most common routine challenges faced by Emergency Radiologists, in particular in case of radiographically occult nondisplaced fractures or in case of soft tissue injuries. With the development of Dual Energy Computed Tomography (DECT) technology, new post-processing applications have gained a useful diagnostic role in many fields of musculoskeletal imaging including acute skeletal trauma imaging. In addition to conventional CT images, DECT allows for the generation of virtual calcium-suppressed images subtracting calcium from unenhanced CT images based on the fact that material attenuation varies at different energy levels. In this way, virtual-non-calcium (VNC) images can precisely characterize traumatic bone marrow edema in both axial and appendicular skeleton, facilitating prompt clinical decision, especially when magnetic resonance method is contraindicated or unavailable. Other DECT emerging applications in the trauma setting include metal artifact reduction and collagen mapping for the evaluation of injuries affecting ligament, tendon, and intervertebral disk. This review focuses on the basic principles of DECT and related post-processing algorithms, highlighting the current advantages and limitations of these new imaging advances in the Emergency Department related to skeletal traumas.

Early results with a bicruciate-retaining total knee arthroplasty: a match-paired study.

BACKGROUND: The aim of this study is to compare 2 groups of total knee arthroplasties (TKAs): the bicruciate-retaining (BCR-group) and cruciate-retaining total knee arthroplasty (CR-group), evaluating the functional results in the short-term follow-up. METHODS: 24 BCR were included in the study and were compared with a group of 24 TKAs performed with the same implant, but with sacrifice of the ACL and retention of the posterior cruciate ligament. For preoperative and postoperative clinical evaluation, the visual analogue score (VAS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were used. Radiological evaluation included weight-bearing long-leg view, a Rosemberg view, lateral view of the knee and tangential view of the patella. Hip-knee-ankle angle (HKA) was recorded pre and postoperatively. Radiolucent lines (RLLs) were evaluated according the Knee Society Roentgenographic Evaluation System (KSRES). RESULTS: At last follow-up the mean VAS score was 1.81 for BCR group and 1.43 for CR group (p = 0.61). The mean WOMAC score was 8.68 for BCR group and 12.81 for CR group (p = 0.33). As for the radiological evaluation, preoperative HKA angle was 0.53° varus for BCR group and 3.14° varus for CR group (p = 0.24); postoperative HKA was 0.72° valgus for BCR group and 0.38° valgus for CR group (p = 0.75). The percentage of RLLs was similar between the two groups (12% versus 15%). CONCLUSIONS: BCR-TKA has showed to give similar functional and radiographic outcomes compared to conventional CR-TKA in a similar cohort of patients. An higher operative times and higher number of complications respect were found in BCR group. These results can be explained by the early learning curve experiences. Future randomized controlled trials should be performed to support new implant designs such as BCR. LEVEL OF EVIDENCE: Level of evidence Case-control study, level III.

Pancreatic Neuroendocrine Tumors in Patients with Multiple Endocrine Neoplasia Type 1: Diagnostic Value of Different MRI Sequences.

BACKGROUND: MRI is a useful imaging modality to assess the presence of pancreatic neuroendocrine tumors (PNETs), allowing repeat monitoring examinations in multiple endocrine neoplasia type 1 (MEN-1) patients. OBJECTIVES: We aimed to compare the diagnostic accuracy of conventional MRI sequences to identify which sequence better depicts the presence of PNETs in MEN-1 patients. METHOD: We performed a retrospective analysis of consecutive MEN-1 patients who underwent a conventional MRI protocol to monitor previously proven PNETs. MRI sequences T1-w chemical shift (CS), T2-w HASTE, fat-suppressed (FS) T2-w HASTE, diffusion-weighted imaging (DWI), and pre- and post-contrast FS T1-w sequences were independently analyzed by 2 experienced radiologists using a 3-grade score (no lesion, uncertain lesion, and certain lesion); lesion size and signal intensity were recorded. A Friedman ANOVA and a Wilcoxon pairwise test for the post hoc analysis were used. The sensitivity of each sequence was measured, and the results were analyzed with the χ2 test. RESULTS: We included 21 patients with a total of 45 PNETs proven by histology, endoscopic ultrasonography-guided fine-needle aspiration, CT, and nuclear medicine studies. A statistically significant (p < 0.01) difference was observed in the detection performance of each MRI sequence, particularly between DWI (91%) and T2-w FS (85%) sequences in comparison to the others (T1-w CS, T2-w, and pre- and post-contrast FS T1-w, ≤56% for all); no significant (p = 0.5) difference was found between the detection performance of DWI and T2-w FS sequences. No correlation was observed between the qualitative score of each sequence and lesion tumor size. CONCLUSIONS: DWI and T2-w FS sequences proved to be the most accurate in the detection of PNETs, thus suggesting a role for an abbreviated MRI protocol without contrast medium administration for monitoring MEN-1 patients.

Breast implant associated anaplastic large cell lymphoma (BIA-ALCL): a challenging cytological diagnosis with hybrid PET/MRI staging and follow-up.

We report a case of a 55-year-old woman with left breast cosmetic augmentation performed 5 years earlier, showing at ultrasound a left small amount of peri-implant effusion suspicious for an anaplastic large cell lymphoma localization. The final diagnosis was obtained by cytology using a small amount of fluid (6 ml). Subsequently, hybrid 18F-FDG PET/MRI was used for pre-operative staging and follow-up. An appropriate management of BIA-ALCL could be obtained even in cases of a small amount of peri-implant effusion, using a comprehensive approach of clinical and imaging evaluation, including PET/MRI as useful and innovative staging imaging technique.