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Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) has emerged as a surgical option for patients with prostatic cancer in high-volume centers. The objective is to assess oncological and functional outcomes when implementing RS-RARP in a medium-volume center without previous experience of robotic surgery. This is a prospective observational single-center study. Patients operated between July 2017 and April 2020 were divided into two consecutive groups, A and B, each with 104 patients. The surgeons had prior experience in laparoscopic surgery and underwent robotic training. Positive surgical margin (PSM) status, urinary continence, and erectile function projected by Kaplan–Meier curves, together with patient reported quality of life outcomes at 12 months post-surgery were documented. Median patient age was 63 years (IQR = 59–67), overall PSM rate were 33%, 28% for pT2 disease. Pre-operative values showed no significant difference between both groups. The rate of urinary continence dropped from 81 to 78% (SE = 5.7) (Group A) and from 90 to 72% (SE = 6.3) (Group B) using the International Consultation on Incontinence Questionnaire-Short Form. Baseline sexual function was regained in 41% (Group A) and 47% (Group B) of patients. The median Expanded Prostate Index Composite-26 total score decreased from 86 to 82. These outcomes relate favorably to prior reports. There was a clinically significant decrease in median operative time in the successive groups with post-operative complications occurring in less than 2% of surgical procedures overall. A 12-month follow-up suggests that RS-RARP may be safely introduced in a medium-volume center without previous experience of robotic surgery.

Figure S1. Raw data from MGE MRI on a representative patient in-vivo at 1.5 T.

Noninvasive characterization of lymph node involvement in cancer is an enduring onerous challenge. In rectal cancer, pathologic lymph node status constitutes the most important determinant of local recurrence and overall survival, and patients with involved lymph nodes may benefit from preoperative chemo and/or radiotherapy. However, knowledge of lymph node status before surgery is currently hampered by limited imaging accuracy. Here, we introduce Susceptibility-Perturbation MRI (SPI) as a novel source of contrast to map malignant infiltration into mesorectal lymph nodes. SPI involves multigradient echo (MGE) signal decays presenting a nonmonoexponential nature, which we show is sensitive to the underlying microstructure via susceptibility perturbations. Using numerical simulations, we predicted that the large cell morphology and the high cellularity of tumor within affected mesorectal lymph nodes would induce signature SPI decays. We validated this prediction in mesorectal lymph nodes excised from total mesorectal excision specimens of patients with rectal cancer using ultrahigh field (16.4 T) MRI. SPI signals distinguished benign from malignant nodal tissue, both qualitatively and quantitatively, and our histologic analyses confirmed cellularity and cell size were the likely underlying sources for the differences observed. SPI was then adapted to a clinical 1.5 T scanner, added to patients' staging protocol, and compared with conventional assessment by two expert radiologists. Nonmonoexponential decays, similar to those observed in the ex vivo study, were demonstrated, and SPI classified lymph nodes more accurately than standard high-resolution T2-weighted imaging assessment. These findings suggest this simple, yet highly informative, method can improve rectal cancer patient selection for neoadjuvant therapy.Significance:These findings introduce an MRI methodology tailored to detect magnetic susceptibility perturbations induced by subtle alterations in tissue microstructure.

In the past nearly 20 years, organ-sparing when no apparent viable tumour is present after neoadjuvant therapy has taken an increasingly relevant role in the therapeutic management of locally-advanced rectal cancer patients. The decision to include a patient or not in a “Watch-and-Wait” program relies mainly on endoscopic assessment by skilled surgeons, and MR imaging by experienced radiologists. Strict surveillance using the same modalities is required, given the chance of a local regrowth is of approximately 25–30%, almost always surgically salvageable if caught early. Local regrowths occur at the endoluminal aspect of the primary tumour bed in almost 90% of patients, but the rest are deep within it or outside the rectal wall, in which case detection relies solely on MR Imaging. In this educational review, we provide a practical guide for radiologists who are, or intend to be, involved in the re-staging and follow-up of rectal cancer patients in institutions with an established “Watch-and-Wait” program. First, we discuss patient preparation and MR imaging acquisition technique. Second, we focus on the re-staging MR imaging examination and review the imaging findings that allow us to assess response. Third, we focus on follow-up assessments of patients who defer surgery and confer about the early signs that may indicate a sustained/non-sustained complete response, a rectal/extra-rectal regrowth, and the particular prognosis of the “near-complete” responders. Finally, we discuss our proposed report template.

Purpose: Bowel motion is a significant source of artifacts in mouse abdominal MRI. Fasting and administration of hyoscine butylbromide (BUSC) have been proposed for bowel motion reduction, but with inconsistent results and limited efficacy assessments. Here, we evaluate these regimes for mouse abdominal MRI at high field. Methods: Thirty-two adult C57BL/6J mice were imaged on a 9.4T scanner with a FLASH sequence, acquired over 90 minutes with ~19s temporal resolution. During MRI acquisition, eight mice were injected with a low-dose and eight mice with a high-dose bolus of BUSC (0.5 and 5 mg/kg, respectively). Eight mice were food deprived for 4.5-6.5h before MRI and another group of 8 mice was injected with saline during MRI acquisition. Two expert readers reviewed the images and classified bowel motion, and quantitative voxel-wise analyses were performed for identification of moving regions. After defining the most effective protocol, high-resolution T2-weighted and diffusion-weighted images were acquired from four mice. Results: High-dose BUSC was the most effective protocol for bowel motion reduction, for up to 45 minutes. Fasting and saline protocols were not effective in suppressing bowel motion. High-resolution abdominal MRI clearly demonstrated improved image quality and ADC quantification with the high-dose BUSC protocol. Conclusion: Our data show that BUSC administration is advantageous for abdominal MRI in the mouse. Specifically, it endows significant bowel motion reduction, with relatively short onset timings after injection (~8.5 minutes) and relatively long duration of the effect (~45 minutes). These features improve the quality of high-resolution images of the mouse abdomen., Carlos Bilreiro and Francisca F. Fernandes contributed equally to this work

Multiparametric MRI represents the primary imaging modality to assess diffuse liver disease, both in a qualitative and in a quantitative manner. Diffusion-weighted imaging (DWI) is among the imaging techniques that can be used to assess fibrosis due to its unique capability to assess microstructural changes at the tissue level. DWI is based on water mobility patterns and has the potential to become a non-invasive and non-destructive virtual biopsy to assess diffuse liver disease, overcoming sampling bias errors due to its three-dimensional imaging capabilities. Parallel to DWI, another quantitative method called texture analysis may be used to assess early and advanced diffused liver disease through quantifying spatial relationships in a global and local level, applying to any type of digital imaging technique like MRI or CT. Initial results using texture analysis hold great promise. In the current paper, we will review the role of DWI and texture analysis using MR images in assessing diffuse liver disease.

Rectal cancer has the eighth highest cancer incidence worldwide, and it is increasing in young individuals. However, in countries with a high human development index, mortality is decreasing, which may reflect better patient management, imaging being key. We rely on imaging to establish the great majority of clinical tumour features for therapeutic decision-making, namely tumour location, depth of invasion, lymph node involvement, circumferential resection margin status and extramural venous invasion. Despite major improvements in technique resulting in better image quality, and notwithstanding the dissemination of guidelines and examples of standardised reports, rectal cancer staging is still challenging on the day-to-day practice, and we believe there are three reasons. First, the normal posterior pelvic compartment anatomy and variants are not common knowledge to radiologists; second, not all rectal cancers fit in review paper models, namely the very early, the very low and the mucinous; and third, the key clinical tumour features may be tricky to analyse. In this review, we discuss the normal anatomy of the rectum and posterior compartment of the pelvis, systematise all rectal cancer staging key points and elaborate on the particularities of early, low and mucinous tumours. We also include our suggested reporting templates and a discussion of its comparison to the reporting templates provided by ESGAR and SAR.

Simple Summary The use of radiomics has been studied to predict Gleason Score from bi-parametric prostate MRI examinations. However, different combinations of type of input data (whole prostate gland/lesion features), sampling strategy, feature selection method and machine learning algorithm can be used. The impact of such choices was investigated and it was found that features extracted from the whole prostate gland were more stable to segmentation differences and produced better models (higher performance and less overfitting). This result suggests that the areas surrounding the tumour lesions offer relevant information regarding the Gleason Score that is ultimately attributed to that lesion. Abstract Prostate cancer is one of the most prevalent cancers in the male population. Its diagnosis and classification rely on unspecific measures such as PSA levels and DRE, followed by biopsy, where an aggressiveness level is assigned in the form of Gleason Score. Efforts have been made in the past to use radiomics coupled with machine learning to predict prostate cancer aggressiveness from clinical images, showing promising results. Thus, the main goal of this work was to develop supervised machine learning models exploiting radiomic features extracted from bpMRI examinations, to predict biological aggressiveness; 288 classifiers were developed, corresponding to different combinations of pipeline aspects, namely, type of input data, sampling strategy, feature selection method and machine learning algorithm. On a cohort of 281 lesions from 183 patients, it was found that (1) radiomic features extracted from the lesion volume of interest were less stable to segmentation than the equivalent extraction from the whole gland volume of interest; and (2) radiomic features extracted from the whole gland volume of interest produced higher performance and less overfitted classifiers than radiomic features extracted from the lesions volumes of interest. This result suggests that the areas surrounding the tumour lesions offer relevant information regarding the Gleason Score that is ultimately attributed to that lesion.

To measure the diagnostic performance of a new radiologic pattern on restaging magnetic resonance (MR) high-resolution T2-weighted imaging (T2-WI)—the split scar sign—for the identification of sustained complete response (SCR) after neoadjuvant therapy in rectal cancer. Institutional review board approval was obtained for this retrospective study and the informed consent requirement was waived. Fifty-eight consecutive patients with rectal cancer who underwent neoadjuvant therapy were enrolled. Two radiologists blindly and independently reviewed restaging pelvic MR imaging and recorded the presence/absence of the split scar sign (mrSSS). On a second round, they also assessed the relative proportion of intermediate signal intensity on T2-WI (mrT2) and of high signal intensity on high b-value diffusion-weighted imaging (mrDWI). Endoscopic response grading records were retrieved. Qui-square test was employed in search for associations between SCR, defined as pathologic complete response or long-term recurrence-free clinical follow-up, and mrSSS, mrT2, mrDWI and endoscopy. Interobserver agreement for imaging parameters was estimated using Cohen’s kappa (k). mrSSS was significantly associated with SCR, with specificity = 0.97/0.97, sensitivity = 0.52/0.64, PPV = 0.93/0.94, NPV = 0.73/0.78, and AuROC = 0.78/0.83, for observers 1/2, respectively. mrDWI was significantly associated with SCR for observer 2, with specificity = 0.76, sensitivity = 0.60, PPV = 0.65, NPV = 0.71, and AuROC = 0.69. mrT2 and endoscopy were not discriminative. Interobserver agreement was substantial for mrSSS (k = 0.69), moderate for mrDWI (k = 0.46), and poor for mrT2 (k = 0.17). The split scar sign is a simple morphologic pattern visible on restaging T2-WI which, although not sensitive, is very specific for the identification of sustained complete responders after neoadjuvant therapy in rectal cancer. • The split scar sign is a morphologic pattern visible on high-resolution T2-weighted MR imaging in rectal cancer patients after neoadjuvant therapy. It therefore does not require any changes to standard protocol. • At first restaging pelvic MR imaging (mean: 9.1 weeks after the end of radiotherapy), the split scar sign identified patients who sustained a complete response with very high specificity (0.97) and positive predictive value (0.93–0.94). • The split scar sign has the potential to improve patient selection for “watch-and-wait” after neoadjuvant therapy in rectal cancer.

Purpose: Radiogenomics offers a potential virtual and noninvasive biopsy. However, radiogenomics models often suffer from generalizability issues, which cause a performance degradation on unseen data. In MRI, differences in the sequence parameters, manufacturers, and scanners make this generalizability issue worse. Such image acquisition information may be used to define different environments and select robust and invariant radiomic features associated with the clinical outcome that should be included in radiomics/radiogenomics models. Approach: We assessed 77 low-grade gliomas and glioblastomas multiform patients publicly available in TCGA and TCIA. Radiomics features were extracted from multiparametric MRI images (T1-weighted, contrast-enhanced T1-weighted, T2-weighted, and fluid-attenuated inversion recovery) and different regions-of-interest (enhancing tumor, nonenhancing tumor/necrosis, and edema). A method developed to find variables that are part of causal structures was used for feature selection and compared with an embedded feature selection approach commonly used in radiomics/radiogenomics studies, across two different scenarios: (1) leaving data from a center as an independent held-out test set and tuning the model with the data from the remaining centers and (2) use stratified partitioning to obtain the training and the held-out test sets. Results: In scenario (1), the performance of the proposed methodology and the traditional embedded method was AUC: 0.75 [0.25; 1.00] versus 0.83 [0.50; 1.00], Sens.: 0.67 [0.20; 0.93] versus 0.67 [0.20; 0.93], Spec.: 0.75 [0.30; 0.95] versus 0.75 [0.30; 0.95], and MCC: 0.42 [0.19; 0.68] versus 0.42 [0.19; 0.68] for center 1 as the held-out test set. The performance of both methods for center 2 as the held-out test set was AUC: 0.64 [0.36; 0.91] versus 0.55 [0.27; 0.82], Sens.: 0.00 [0.00; 0.73] versus 0.00 [0.00; 0.73], Spec.: 0.82 [0.52; 0.94] versus 0.91 [0.62; 0.98], and MCC: −0.13 [ − 0.38 ; − 0.04 ] versus −0.09 [ − 0.38 ; − 0.02 ] , whereas for center 3 was AUC: 0.80 [0.62; 0.95] versus 0.89 [0.56; 0.96], Sens.: 0.86 [0.48; 0.97] versus 0.86 [0.48; 0.97], Spec.: 0.72 [0.54; 0.85] versus 0.79 [0.61; 0.90], and MCC: 0.47 [0.41; 0.53] versus 0.55 [0.48; 0.60]. For center 4, the performance of both methods was AUC: 0.77 [0.51; 1.00] versus 0.75 [0.47; 0.97], Sens.: 0.53 [0.30; 0.75] versus 0.00 [0.00; 0.15], Spec.: 0.71 [0.35; 0.91] versus 0.86 [0.48; 0.97], and MCC: 0.23 [0.16; 0.31] versus. −0.32 [ − 0.46 ; − 0.20 ] . In scenario (2), the performance of these methods was AUC: 0.89 [0.71; 1.00] versus 0.79 [0.58; 0.94], Sens.: 0.86 [0.80; 0.92] versus 0.43 [0.15; 0.74], Spec.: 0.87 [0.62; 0.96] versus 0.87 [0.62; 0.96], and MCC: 0.70 [0.60; 0.77] versus 0.33 [0.24; 0.42]. Conclusions: This proof-of-concept study demonstrated good performance by the proposed feature selection method in the majority of the studied scenarios, as it promotes robustness of features included in the models and the models’ generalizability by making used imaging data of different scanners or with sequence parameters.

Diffusion-weighted MRI has become a staple tool for the diagnosis and follow-up of several abdominal conditions. Many studies have evaluated its value specifically for pancreatic diseases, using both contrast images and apparent diffusion coefficient values. Also, new diffusion-based metrics have more recently been developed and tested in both neoplastic and inflammatory conditions of the pancreas. This chapter reviews the current literature in diffusion-weighted imaging of the pancreas and exemplifies its value with clinical cases.

Simple Summary The management of intraductal papillary mucinous neoplasms of the pancreas (IPMN) remains controversial due to the relatively high rate of unnecessary surgery for low grade dysplasia (LGD) despite the last international recommendations. The aim of our retrospective study was to assess the performance of radiomic analysis on CT in differentiating benign from malignant IPMN. We confirmed in a training cohort (296 patients) and a validation cohort (112 patients) that a total of 85 radiomics features provided valuable additional and independent information for discriminating benign from malignant tumors in the training cohort with an area under the ROC curve (AUC) of 0.84 and an external validation with an AUC of 0.71 with higher performance when implementing clinical variables leading to the indication to surgery. We have demonstrated the capabilities of radiomics models comprising LGD versus high-grade dysplasia (HGD) versus invasive, LGD and HGD, HGD and invasive. Abstract To assess the performance of CT-based radiomics analysis in differentiating benign from malignant intraductal papillary mucinous neoplasms of the pancreas (IPMN), preoperative scans of 408 resected patients with IPMN were retrospectively analyzed. IPMNs were classified as benign (low-grade dysplasia, n = 181), or malignant (high grade, n = 128, and invasive, n = 99). Clinicobiological data were reported. Patients were divided into a training cohort (TC) of 296 patients and an external validation cohort (EVC) of 112 patients. After semi-automatic tumor segmentation, PyRadiomics was used to extract radiomics features. A multivariate model was developed using a logistic regression approach. In the training cohort, 85/107 radiomics features were significantly different between patients with benign and malignant IPMNs. Unsupervised clustering analysis revealed four distinct clusters of patients with similar radiomics features patterns with malignancy as the most significant association. The multivariate model differentiated benign from malignant tumors in TC with an area under the ROC curve (AUC) of 0.84, sensitivity (Se) of 0.82, specificity (Spe) of 0.74, and in EVC with an AUC of 0.71, Se of 0.69, Spe of 0.57. This large study confirms the high diagnostic performance of preoperative CT-based radiomics analysis to differentiate between benign from malignant IPMNs.

Objectives To study the diffusion tensor-based fiber tracking feasibility to access the male urethral sphincter complex of patients with prostate cancer undergoing Retzius-sparing robot-assisted laparoscopic radical prostatectomy (RS-RARP). Methods Twenty-eight patients (median age of 64.5 years old) underwent 3 T multiparametric-MRI of the prostate, including an additional echo-planar diffusion tensor imaging (DTI) sequence, using 15 diffusion-encoding directions and a b value = 600 s/mm2. Acquisition parameters, together with patient motion and eddy currents corrections, were evaluated. The proximal and distal sphincters, and membranous urethra were reconstructed using the deterministic fiber assignment by continuous tracking (FACT) algorithm, optimizing fiber tracking parameters. Tract length and density, fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) were computed. Regional differences between structures were accessed by ANOVA, or nonparametric Kruskal–Wallis test, and post-hoc tests were employed, respectively, TukeyHSD or Dunn’s. Results The structures of the male urethral sphincter complex were clearly depicted by fiber tractography using optimized acquisition and fiber tracking parameters. The use of eddy currents and subject motion corrections did not yield statistically significant differences on the reported DTI metrics. Regional differences were found between all structures studied among patients, suggesting a quantitative differentiation on the structures based on DTI metrics. Conclusions The current study demonstrates the technical feasibility of the proposed methodology, to study in a preoperative setting the male urethral sphincter complex of prostate cancer patients candidates for surgical treatment. These findings may play a role on a more accurate prediction of the RS-RARP post-surgical urinary continence recovery rate.

Background Whole-body diffusion weighted imaging (WB-DWI) has proven value to detect multiple myeloma (MM) lesions. However, the large volume of imaging data and the presence of numerous lesions makes the reading process challenging. The aim of the current study was to develop a semi-automatic lesion segmentation algorithm for WB-DWI images in MM patients and to evaluate this smart-algorithm (SA) performance by comparing it to the manual segmentations performed by radiologists. Methods An atlas-based segmentation was developed to remove the high-signal intensity normal tissues on WB-DWI and to restrict the lesion area to the skeleton. Then, an outlier threshold-based segmentation was applied to WB-DWI images, and the segmented area’s signal intensity was compared to the average signal intensity of a low-fat muscle on T1-weighted images. This method was validated in 22 whole-body DWI images of patients diagnosed with MM. Dice similarity coefficient (DSC), sensitivity and positive predictive value (PPV) were computed to evaluate the SA performance against the gold standard (GS) and to compare with the radiologists. A non-parametric Wilcoxon test was also performed. Apparent diffusion coefficient (ADC) histogram metrics and lesion volume were extracted for the GS segmentation and for the correctly identified lesions by SA and their correlation was assessed. Results The mean inter-radiologists DSC was 0.323 ± 0.268. The SA vs GS achieved a DSC of 0.274 ± 0.227, sensitivity of 0.764 ± 0.276 and PPV 0.217 ± 0.207. Its distribution was not significantly different from the mean DSC of inter-radiologist segmentation (p = 0.108, Wilcoxon test). ADC and lesion volume intraclass correlation coefficient (ICC) of the GS and of the correctly identified lesions by the SA was 0.996 for the median and 0.894 for the lesion volume (p Conclusions The SA provides equally reproducible segmentation results when compared to the manual segmentation of radiologists. Thus, the proposed method offers robust and efficient segmentation of MM lesions on WB-DWI. This method may aid accurate assessment of tumor burden and therefore provide insights to treatment response assessment.

Clinicians have shown an increasing interest in quantitative imaging for precision medicine. Imaging features can extract distinct phenotypic differences of tumours, potentially they can be used as a non-invasive prognostic tool and contribute for a better prediction of pathological Complete Response (pCR). However, the high-dimensional nature of the data brings many constraints, for which several approaches have been considered, with regularization techniques in the cutting-edge research front. In this work, classic lasso, ridge and the recently proposed priority-lasso are applied to high-dimensional imaging data, regarding a binary outcome. A breast cancer dataset, with radiomics, clinical and pathological information as features, was used. The application of sparsity techniques to the dataset enabled the selection of relevant features extracted in MRI of breast cancer patients, in order to identify the accuracy of those features and predict the pCR in the breast and the axilla.

During the last decade, there is an increasing usage of quantitative methods in Radiology in an effort to reduce the diagnostic variability associated with a subjective manner of radiological interpretation. Combined approaches where visual assessment made by the radiologist is augmented by quantitative imaging biomarkers are gaining attention. Advances in machine learning resulted in the rise of radiomics that is a new methodology referring to the extraction of quantitative information from medical images. Radiomics are based on the development of computational models, referred to as “Radiomic Signatures”, trying to address either unmet clinical needs, mostly in the field of oncologic imaging, or to compare radiomics performance with that of radiologists. However, to explore this new technology, initial publications did not consider best practices in the field of machine learning resulting in publications with questionable clinical value. In this paper, our effort was concentrated on how to avoid methodological mistakes and consider critical issues in the workflow of the development of clinically meaningful radiomic signatures.

Pancreatic ductal adenocarcinoma (PDA) remains among the most challenging malignancies to treat. At diagnosis, the tumor often already extends beyond the confines of the pancreas, spreading to an extent such that primary surgery with curative intent is very rarely feasible. Considerable momentum is now being given to a treatment strategy involving neoadjuvant chemotherapy or chemotherapy and radiation therapy in patients with nonmetastatic PDA. The main advantage of this strategy is better selection of patients likely to benefit from curative-intent surgery through the achievement of negative resection margins. Patients with rapidly progressive disease are identified and are spared ineffective surgery with its attendant morbidity. Neoadjuvant therapy can downstage tumors classified as locally advanced at initial imaging studies to resectable tumors. However, the imaging study evaluation of the response to neoadjuvant therapy is extremely complex. Thus, the diagnostic performance of imaging studies is not sufficient to ensure the accurate selection of patients in whom negative-margin resection is likely to be achieved. More specifically, standard criteria for predicting vascular invasion, based on the amount of tumor-vessel contact, are not valid after neoadjuvant therapy. ©RSNA, 2018.

Objectives To evaluate how changes in tumour scar depth angle and thickness in the post-neoadjuvant period relate to long-term response in locally-advanced rectal cancer patients. Methods Informed consent was obtained from all patients and institutional review board approved this retrospective study. Sixty-nine consecutive locally-advanced rectal cancer patients who underwent neoadjuvant therapy and were selected for “Watch-and-Wait” were enrolled. Two radiologists, O1 and O2, blindly and independently reviewed the 1st and 2nd post-neoadjuvant therapy pelvic MRI T2-weighted images and recorded depth angle and thickness of the tumour scar. Value changes were calculated by simple subtraction (2nd-1st). Mann-Whitney U test was employed to assess for significant differences between sustained clinical complete responders (SCR), defined as patients with pathologic complete response or clinical complete response with a minimum follow-up of 1 year; and non-sustained complete responders (non-SCR). Interobserver agreement was estimated using intraclass correlation coefficient (ICC). Data on mrTRG, DWI and endoscopy at 1st and 2nd timepoints were retrieved for comparison. Results In SCR, depth angle change between 1st (med = 10 weeks after end of radiotherapy) and 2nd (med = 23 weeks after end of radiotherapy) timepoints was significantly different (O1:p = 0.004; O2:p = 0.010): the SCR group showed a depth angle reduction (O1:med=-4.45; O2:med=-2.35), whereas non-SCRs showed a depth angle increase (O1:med=+2.60; O2:med=+7.40). Also, at 2nd timepoint, SCR scars were significantly thinner both for O1 (p = 0.003; SCR:med = 7.05 mm; non-SCR:med = 9.4 mm) and O2 (p = 0.006; SCR:med = 6.45 mm; non-SCR:med = 8.2 mm). A depth angle increase >21o between 1st and 2nd timepoints and a scar thickness >10 mm at 2nd timepoint were not sensitive but were highly specific for a non-SCR (91/94 %) for both observers. Interobserver agreement was good for scar depth angle change (ICC = 0.65) and excellent for scar thickness at 2nd timepoint (ICC = 0.84). Of the retrieved data, only DWI at 2nd timepoint was discriminative (p = 0.043) providing a similar sensitivity (33 %) and a slightly lower specificity (87.5 %). Conclusion Tumour scar expansion >21° between 1st and 2nd post-neoadjuvancy MRI and a scar thickness >10 mm at 2nd post-neoadjuvancy MRI may consistently indicate a non-SCR with high specificity in locally-advanced rectal cancer patients.

Purpose Mesorectal lymph node staging plays an important role in treatment decision making. Here, we explore the benefit of higher-order diffusion MRI models accounting for non-Gaussian diffusion effects to classify mesorectal lymph nodes both 1) ex vivo at ultrahigh field correlated with histology and 2) in vivo in a clinical scanner upon patient staging. Methods The preclinical investigation included 54 mesorectal lymph nodes, which were scanned at 16.4 T with an extensive diffusion MRI acquisition. Eight diffusion models were compared in terms of goodness of fit, lymph node classification ability, and histology correlation. In the clinical part of this study, 10 rectal cancer patients were scanned with diffusion MRI at 1.5 T, and 72 lymph nodes were analyzed with Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), Kurtosis, and IVIM-Kurtosis. Results Compartment models including restricted and anisotropic diffusion improved the preclinical data fit, as well as the lymph node classification, compared to standard ADC. The comparison with histology revealed only moderate correlations, and the highest values were observed between diffusion anisotropy metrics and cell area fraction. In the clinical study, the diffusivity from IVIM-Kurtosis was the only metric showing significant differences between benign (0.80 ± 0.30 μm2 /ms) and malignant (1.02 ± 0.41 μm2 /ms, P = .03) nodes. IVIM-Kurtosis also yielded the largest area under the receiver operating characteristic curve (0.73) and significantly improved the node differentiation when added to the standard visual analysis by experts based on T2 -weighted imaging. Conclusion Higher-order diffusion MRI models perform better than standard ADC and may be of added value for mesorectal lymph node classification in rectal cancer patients.

To measure the diagnostic performance of a new radiologic pattern on restaging magnetic resonance (MR) high-resolution T2-weighted imaging (T2-WI)-the split scar sign-for the identification of sustained complete response (SCR) after neoadjuvant therapy in rectal cancer.Institutional review board approval was obtained for this retrospective study and the informed consent requirement was waived. Fifty-eight consecutive patients with rectal cancer who underwent neoadjuvant therapy were enrolled. Two radiologists blindly and independently reviewed restaging pelvic MR imaging and recorded the presence/absence of the split scar sign (mrSSS). On a second round, they also assessed the relative proportion of intermediate signal intensity on T2-WI (mrT2) and of high signal intensity on high b-value diffusion-weighted imaging (mrDWI). Endoscopic response grading records were retrieved. Qui-square test was employed in search for associations between SCR, defined as pathologic complete response or long-term recurrence-free clinical follow-up, and mrSSS, mrT2, mrDWI and endoscopy. Interobserver agreement for imaging parameters was estimated using Cohen's kappa (k).mrSSS was significantly associated with SCR, with specificity = 0.97/0.97, sensitivity = 0.52/0.64, PPV = 0.93/0.94, NPV = 0.73/0.78, and AuROC = 0.78/0.83, for observers 1/2, respectively. mrDWI was significantly associated with SCR for observer 2, with specificity = 0.76, sensitivity = 0.60, PPV = 0.65, NPV = 0.71, and AuROC = 0.69. mrT2 and endoscopy were not discriminative. Interobserver agreement was substantial for mrSSS (k = 0.69), moderate for mrDWI (k = 0.46), and poor for mrT2 (k = 0.17).The split scar sign is a simple morphologic pattern visible on restaging T2-WI which, although not sensitive, is very specific for the identification of sustained complete responders after neoadjuvant therapy in rectal cancer.• The split scar sign is a morphologic pattern visible on high-resolution T2-weighted MR imaging in rectal cancer patients after neoadjuvant therapy. It therefore does not require any changes to standard protocol. • At first restaging pelvic MR imaging (mean: 9.1 weeks after the end of radiotherapy), the split scar sign identified patients who sustained a complete response with very high specificity (0.97) and positive predictive value (0.93-0.94). • The split scar sign has the potential to improve patient selection for "watch-and-wait" after neoadjuvant therapy in rectal cancer.

Noninvasive characterization of lymph node involvement in cancer is an enduring onerous challenge. In rectal cancer, pathologic lymph node status constitutes the most important determinant of local recurrence and overall survival, and patients with involved lymph nodes may benefit from preoperative chemo and/or radiotherapy. However, knowledge of lymph node status before surgery is currently hampered by limited imaging accuracy. Here, we introduce Susceptibility-Perturbation MRI (SPI) as a novel source of contrast to map malignant infiltration into mesorectal lymph nodes. SPI involves multigradient echo (MGE) signal decays presenting a nonmonoexponential nature, which we show is sensitive to the underlying microstructure via susceptibility perturbations. Using numerical simulations, we predicted that the large cell morphology and the high cellularity of tumor within affected mesorectal lymph nodes would induce signature SPI decays. We validated this prediction in mesorectal lymph nodes excised from total mesorectal excision specimens of patients with rectal cancer using ultrahigh field (16.4 T) MRI. SPI signals distinguished benign from malignant nodal tissue, both qualitatively and quantitatively, and our histologic analyses confirmed cellularity and cell size were the likely underlying sources for the differences observed. SPI was then adapted to a clinical 1.5 T scanner, added to patients' staging protocol, and compared with conventional assessment by two expert radiologists. Nonmonoexponential decays, similar to those observed in the ex vivo study, were demonstrated, and SPI classified lymph nodes more accurately than standard high-resolution T2-weighted imaging assessment. These findings suggest this simple, yet highly informative, method can improve rectal cancer patient selection for neoadjuvant therapy. Significance: These findings introduce an MRI methodology tailored to detect magnetic susceptibility perturbations induced by subtle alterations in tissue microstructure.

To investigate the added value of diffusion-weighted (DW) magnetic resonance (MR) imaging in the detection of infection in pancreatic fluid collections (PFC). Forty-patients with PFC requiring endoscopic-transmural drainage underwent conventional-MR and DW-MR imaging (b = 1000 s/mm2) before endoscopy. MR images were divided into two sets (set1, conventional-MR; set2, conventional-MR, DW-MR and ADC maps) and randomized. Two independent readers performed qualitative and quantitative (apparent diffusion coefficient, ADC) image analysis. Bacteriological analysis of PFC content was the gold standard. Non-parametric tests were used for comparisons. Sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and accuracy were calculated for the two sets for both readers. Receiver operating characteristic curves (ROC) were drawn to assess quantitative DW-MR imaging diagnostic performance. For both readers, sensitivity, specificity, NPV, PPV and accuracy for infected PFCs were higher for set2 (P > .05). ADC were lower in infected versus non-infected PFCs (P ≤ .031). Minimum ADC cut-off: 1,090×10-3 mm2/s for reader 1 and 1,012×10-3 mm2/s for reader 2 (sensitivity and specificity 67 % and 96 % for both readers). Qualitative information provided by DW-MR may help to assess PFCs infection. Infected PFCs show significantly lower ADCs compared to non-infected ones. • DW improves MR diagnostic accuracy to detect infection of PFC • Infected PFCs show lower ADC compared to non-infected ones (P

The significant advances in magnetic resonance imaging (MRI) hardware and software, sequence design, and postprocessing methods have made diffusion-weighted imaging (DWI) an important part of body MRI protocols and have fueled extensive research on quantitative diffusion outside the brain, particularly in the oncologic setting. In this review, we summarize the most up-to-date information on DWI acquisition and clinical applications outside the brain, as discussed in an ISMRM-sponsored symposium held in April 2015. We first introduce recent advances in acquisition, processing, and quality control; then review scientific evidence in major organ systems; and finally describe future directions. J. Magn. Reson. Imaging 2016;44:521-540.

Purpose To prospectively assess liver ADC (apparent diffusion coefficient) repeatability from cardiac-triggered diffusion-weighted images obtained with an individually predetermined optimal cardiac time window minimizing cardiac-related effects and to evaluate a signal filtering method aimed at artifact elimination. Materials and Methods After Institutional Review Board approval and written informed consent, eight healthy volunteers underwent four repetitions of respiratory-triggered diffusion-weighted sequences (3T, b: 0,150,500 s/mm2) without (RTnoCT, 51 sec) and with individually optimized cardiac triggering (RTCT, 306 sec). The optimal cardiac delay was individually predetermined using a 5-second breath-hold sequence. Monoexponential liver ADC and left-to-right-liver ADC ratio were computed from region of interest (ROI) signal measurements (two independent readers). A filtering method, excluding signal intensities lower than the mean intensity at fixed b-value, provided ADC recalculation. Limits-of-agreement (LOAs) from 95% confidence intervals for differences across the four repetitions provided the variability range. Results For Reader 1 (Reader 2), left-to-right-liver ADC ratios were significantly higher in RTnoCT 1.51 (1.52) than in RTCT 1.12 (1.15), P = 0.012 (P = 0.017). Respectively for RTnoCT and RTCT: left liver LOAs were ±835 (±775), ± 315 (±369) 10-6mm2/s; right liver LOAs were ±392 (±445), ± 172 (±140) 10-6mm2/s: LOAs were larger in the left than in the right lobe (both P < 0.001). After filtering, left liver ADC LOAs narrowed to ±650 (±367) 10-6mm2/s, P = 0.17 (P < 0.001); ± 152 (±208) 10-6mm2/s (both P < 0.002) and left-to-right-liver ADC ratio decreased to 1.28 (1.20), P = 0.017 (P = 0.012); 1.09 (1.08), P = 0.106 (P = 0.105). Conclusion Compared to noncardiac-triggered acquisitions, individually optimized cardiac-triggered acquisitions improved ADC repeatability in both liver lobes and reduced ADC differences between left and right liver. Left liver ADC repeatability was further improved after signal filtering. J. Magn. Reson. Imaging 2015.

To compare low b value (10s/mm(2)) spin-echo echo-planar (SE-EP) diffusion-weighted imaging (DWI) acquired with respiratory-triggering (RT), triggering and tracking navigator (TT), tracking only navigator (TRON) techniques for image quality and focal liver lesions (FLL) detection in non-cirrhotic patients.This bi-centric study was approved by the institutional review boards; informed consent was obtained. Eighty-three patients were prospectively included and SE-EP-DWI with RT, TT and TRON techniques were performed. DWI sequences were randomized and independently analyzed by two readers. The qualitative evaluation was based on a 3-point score for axial artifacts (motion, ghost, susceptibility artifacts and distortion) and stair-step artifacts. Sensitivity of FLL detection was calculated for all lesions together and after lesion size stratification (≤ 10 mm,10-20mm and20mm). The standard of reference consisted of a retrospective reading of the conventional MRI, the three DWI sequences and by follow-up (12 months): a total of 409 FLL were detected. Data between sequences was compared with non-parametric tests. Cohen's kappa coefficient was used for inter-observer agreement.Image quality was comparable for RT and TT. TRON showed statistically significantly more axial artifacts for the two readers (p0.05). Stair-step artifacts were not statistically significantly different between DWI sequences. Overall sensitivities for RT, TT, TRON were 85%, 86%, 82% and 86%, 89% 83%, respectively, for readers 1 and 2. The inter-observer agreement was very good.Image quality was better for RT and TT compared to TRON. Overall sensitivities for FLL detection were comparable between techniques and readers.

A pancreatite auto-imune é uma patologia incomum e subdiagnosticada. O seu quadro clínico é inespecífico, condicionando dificuldades diagnósticas. Os exames de imagem têm papel crucial no diagnóstico desta doença, assim como no controle da eficácia terapêutica. Com o objetivo de salientar a importância diagnóstica da imagiologia nesta patologia, os autores apresentam o caso de uma paciente com queixas abdominais inespecíficas não recentes, diagnosticado como pancreatite auto-imune após avaliação analítica e imagiológica. Com base neste diagnóstico foi instituída terapêutica com metilprednisolona oral, a qual foi bem-sucedida, com progressiva resolução clínica, laboratorial e imagiológica.

Purpose To prospectively assess chemotherapy-induced changes in pancreatic ductal adenocarcinoma (PDA) with diffusion-weighted (DW)-MR quantitative metrics, including apparent diffusion coefficient (ADC) and histogram-derived parameters, compared with RECIST 1.1. Methods 24 patients underwent DW-MR at baseline, week-2 and week-8 after chemotherapy initiation. Tumour diameter was assessed on T2-weighted images. Regions-of-interest (ROI) were drawn on ADC map for ROI-ADC. Volume segmentation (b = 1000 s/mm2 images) provided DW-volume and histogram-derived diffusion parameters (H-ADC, H-D and H-PF). All variables and their relative change were compared to baseline or between responders and non-responders. Discriminant analysis was performed. Results 15/24 patients were responders. RECIST 1.1 correctly characterized 6/15 responders at week-8. At week-2, in responders DW-volume decreased (P = .002); ROI-ADC mean H-D increased (P = .047; P = .048;). The 25th percentile H-D increased in responders and decreased in non-responders (P = .016; P = .048). At week-8 in responders DW-volume decreased and ROI-ADC mean, 25th, 50th, 75th percentiles of H-ADC and H-D increased (P .05). At week-2, 25th percentile of H-D and H-PF relative change correctly classified 20/24 patients (P = .003); at week-8, DW-volume relative change correctly classified 22/24 patients (P Conclusions ROI-ADC, DW-volume and histogram-derived diffusion parameters are more accurate to categorize responding and non-responding PDA patients treated with chemotherapy compared with RECIST 1.1.

To investigate how normal liver parenchyma visibility on 3 T diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) quantification are influenced by age, gender, and iron content. Between February 2011 and April 2013, 86 patients (52 women) with normal livers who underwent respiratory-triggered abdominal 3 T DWI (b = 0, 150, 600, 1,000 s/mm2) were retrospectively included. Normal liver and spleen parenchyma visibility was scored independently by two readers. Correlations between visibility scores or ADC with age, gender, T2*, or recent serum ferritin (SF) were investigated. Liver visibility scores in b = 1,000 s/mm2 images correlated with the age (Spearman R = -0.56 in women, -0.45 in men), T2* (R = 0.75) and SF (R = -0.64) and were significantly higher in women (P

Background and study aims: Paraduodenal pancreatitis is histologically well defined but its epidemiology, natural history, and connection with chronic pancreatitis are not completely understood. The aim of this study was to review the endoscopic and medical management of paraduodenal pancreatitis. Patients and methods: Medical records of all patients with paraduodenal pancreatitis diagnosed by magnetic resonance cholangiopancreatography (MRCP) or endoscopic ultrasonography (EUS) between 1995 and 2010 were retrospectively reviewed. Clinical features, imaging procedures, and treatments were investigated. The primary end point was the rate of clinical success, and the secondary end points were the radiological or endoscopic improvement, complication rate, and overall survival rate. Results: A total of 51 patients were included in the study (88.2 % alcohol abuse; median age 49 years [range 37 – 70]; 50 men). The most frequent symptoms at presentation were pain (n = 50; 98.0 %) and weight loss (n = 36; 70.6 %). Chronic pancreatitis was present in 36 patients (70.6 %), and 45 patients (88.2 %) had cysts. Other findings included stricture of the pancreatic duct (n = 37; 72.5 %), common bile duct (n = 29; 56.9 %), and duodenum (n = 24; 47.1 %). A total of 39 patients underwent initial endoscopic treatment: cystenterostomy (n = 20), pancreatic and/or biliary duct drainage (n = 19), and/or duodenal dilation (n = 6). For the patients with available follow-up (n = 41), 24 patients required repeat endoscopy and 9 patients required surgery after the initial endoscopic management. After a median follow-up of 54 months (range 6 – 156 months), complete clinical success was achieved in 70.7 % of patients, and the overall survival rate was 94.1 %. Conclusions: This is the largest series concerning the management of paraduodenal pancreatitis using endotherapy as the first-line intervention. Although repeat endoscopic procedures were required in half of the patients, no severe complication was observed and surgical treatment was ultimately needed in less than 25 % of the patients.

The authors report and discuss an exceedingly rare case of a unilocular macrocystic serous cystadenomas diagnosed in a 63-year-old female patient, which was preoperatively misdiagnosed as a mucinous cystic neoplasm, due to the atypical magnetic resonance (MR) imaging features shown at presentation and the misleading results obtained through cystic fluid analysis. This manuscript overviews the typical and atypical manifestations of this entity and highlights the advantages, potential limitations and pitfalls of both MR imaging and cystic fluid analysis.