Variability of Manual Segmentation of the Prostate in Axial T2-weighted MRI: A Multi-Reader Study

Purpose To evaluate the interreader variability in prostate and seminal vesicle (SV) segmentation on T2w MRI. Methods Six readers segmented the peripheral zone (PZ), transitional zone (TZ) and SV slice-wise on axial T2w prostate MRI examinations of n = 80 patients. Twenty different similarity scores, including dice score (DS), Hausdorff distance (HD) and volumetric similarity coefficient (VS), were computed with the VISCERAL EvaluateSegmentation software for all structures combined and separately for the whole gland (WG = PZ + TZ), TZ and SV. Differences between base, midgland and apex were evaluated with DS slice-wise. Descriptive statistics for similarity scores were computed. Wilcoxon testing to evaluate differences of DS, HD and VS was performed. Results Overall segmentation variability was good with a mean DS of 0.859 (±SD = 0.0542), HD of 36.6 (±34.9 voxels) and VS of 0.926 (±0.065). The WG showed a DS, HD and VS of 0.738 (±0.144), 36.2 (±35.6 vx) and 0.853 (±0.143), respectively. The TZ showed generally lower variability with a DS of 0.738 (±0.144), HD of 24.8 (±16 vx) and VS of 0.908 (±0.126). The lowest variability was found for the SV with DS of 0.884 (±0.0407), HD of 17 (±10.9 vx) and VS of 0.936 (±0.0509). We found a markedly lower DS of the segmentations in the apex (0.85 ± 0.12) compared to the base (0.87 ± 0.10, p < 0.01) and the midgland (0.89 ± 0.10, p < 0.001). Conclusions We report baseline values for interreader variability of prostate and SV segmentation on T2w MRI. Variability was highest in the apex, lower in the base, and lowest in the midgland

Diagnosis of cardiac metastasis from cervical cancer in a 33-year-old patient using multimodal imaging studies: a case report and literature review.

We report a case of a 33-year-old woman with emergency admission due to dyspnoea and fever. History included squamous cell carcinoma of the cervix in complete remission. Contrast-enhanced computed tomography (CT) scanning of the chest, which was indicated to rule out pneumonia, revealed an infiltrative cardiac mass. Further assessment of the tumour by echocardiography and cardiac magnetic resonance imaging (MRI) showed transmural infiltration of the apical interventricular septum with a mass extending into the left and right ventricle cavities. The mass was highly suspicious for a cardiac metastasis. Cardiac metastases from cervical cancer are extremely rare. Recurrence of cervical carcinoma involving the heart should be considered even after a curative therapy approach. Non-invasive imaging plays a paramount role in investigating cardiac masses. Echocardiography, CT and MRI are complementary imaging modalities for complete work-up of intracardiac lesions

Loss of Nogo-A-expressing neurons in a rat model of Parkinson's disease

The myelin-associated protein Nogo-A is among the most potent neurite growth inhibitors in the adult CNS. Recently, Nogo-A expression was demonstrated in a number of neuronal subpopulations of the adult and developing CNS but at present, little is known about the expression of Nogo-A in the nigrostriatal system, a brain structure severely affected in Parkinson's disease (PD). The present study sought to characterize the expression pattern of Nogo-A immunoreactive (ir) cells in the adult ventral mesencephalon of control rats and in the 6-hydroxydopamine (6-OHDA) rat model of PD. Immunohistochemical analyses of normal adult rat brain showed a distinct expression of Nogo-A in the ventral mesencephalon, with the highest level in the substantia nigra pars compacta (SNc) where it co-localized with dopaminergic neurons. Analyses conducted 1week and 1 month after unilateral striatal injections of 6-OHDA disclosed a severe loss of the number of Nogo-A-ir cells in the SNc. Notably, at 1week after treatment, more dopaminergic neurons expressing Nogo-A were affected by the 6-OHDA toxicity than Nogo-A-negative dopaminergic neurons. However, at later time points more of the surviving dopaminergic neurons expressed Nogo-A. In the striatum, both small and large Nogo-A-positive cells were detected. The large cells were identified as cholinergic interneurons. Our results suggest yet unidentified functions of Nogo-A in the CNS beyond the inhibition of axonal regeneration and plasticity, and may indicate a role for Nogo-A in PD

Diagnostic Value and Interreader Agreement of the Pancreaticolienal Gap in Pancreatic Cancer on MDCT.

OBJECTIVE The aim of this retrospective study was to evaluate the diagnostic value and measure interreader agreement of the pancreaticolienal gap (PLG) in the assessment of imaging features of pancreatic carcinoma (PC) on contrast-enhanced multi-detector computed tomography (CE-MDCT). MATERIALS AND METHODS CE-MDCT studies in the portal venous phase were retrospectively reviewed for 66 patients with PC. The age- and gender-matched control group comprised 103 healthy individuals. Three radiologists with different levels of experience independently measured the PLG (the minimum distance of the pancreatic tail to the nearest border of the spleen) in the axial plane. The interreader agreement of the PLG and the receiver operating characteristic (ROC) curve was used to calculate the accuracy of the technique. RESULTS While the control group (n = 103) showed a median PLG of 3 mm (Range: 0 - 39mm) the PC patients had a significantly larger PLG of 15mm (Range: 0 - 53mm)(p 12 mm for PC, with a sensitivity of 58.2% (95% CI = 45.5-70.1), specificity of 84.0% (95% CI = 75.6-90.4) and an area under the ROC curve of 0.714 (95% CI = 0.641 to 0.780). The mean interreader agreement showed correlation coefficient r of 0.9159. The extent of the PLG did not correlate with tumor stage but did correlate with pancreatic density (fatty involution) and age, the density decreased by 4.1 HU and the PLG increased by 0.8 mm within every 10 y. CONCLUSION The significant interreader agreement supports the use of the PLG as a characterizing feature of pancreatic cancer independent of the tumor stage on an axial plane. The increase in the PLG with age may represent physiological atrophy of the pancreatic tail

Dynamic MRI of the pelvic floor: comparison of performance in supine vs left lateral body position

OBJECTIVE To investigate the performance of MR-defecography (MRD) in lateral body position as an alternative to supine position. METHODS 22 consecutive patients (16 females; mean age 51 ± 19.4) with obstructed defecation and 20 healthy volunteers (11 females; mean age 33.4 ± 11.5) underwent MRD in a closed-configuration 3T-MRI in supine and lateral position. MRD included T weighted images at rest and during defecation after filling the rectum with 250 ml water-based gel. Measurements were performed in reference to the pubococcygeal line and grade of evacuation was assessed. Image quality (IQ) was rated on a 5-point-scale (5 = excellent). RESULTS In patients grades of middle and posterior compartment descent were similar in both body positions (p > 0.05). Grades of anterior compartment descent were significantly higher in lateral position (21/22 vs 17/22 patients with normal or small descent, p 0.05). When attempting to defecate in supine position 6/22 (27%) patients showed no evacuation, while in lateral position only 3/22 (14%) were not able to evacuate. IQ in patients was equal at rest (4.4 ± 0.5 and 4.7 ± 0.6, p > 0.05) and slightly better in supine compared to the lateral position during defecation (4.5 ± 0.4 vs 3.9 ± 0.9, p 0.05). CONCLUSION In lateral position, more patients were able to evacuate with similar grades of pelvic floor descent compared to supine position. MRD in lateral position may be a valuable alternative for patients unable to defecate in supine position. Advances in knowledge: In lateral position, more patients were able to evacuate during MRD. MRD in lateral position may be an alternative for patients unable to defecate in supine position

Brown fat does not cause cachexia in cancer patients: A large retrospective longitudinal FDG-PET/CT cohort study

BACKGROUND Brown adipose tissue (BAT) is a specialized form of adipose tissue, able to increase energy expenditure by heat generation in response to various stimuli. Recently, its pathological activation has been implicated in the pathogenesis of cancer cachexia. To establish a causal relationship, we retrospectively investigated the longitudinal changes in BAT and cancer in a large FDG-PET/CT cohort. METHODS We retrospectively analyzed 13 461 FDG-PET/CT examinations of n = 8 409 patients at our institution from the winter months of 2007-2015. We graded the activation strength of BAT based on the anatomical location of the most caudally activated BAT depot into three tiers, and the stage of the cancer into five general grades. We validated the cancer grading by an interreader analysis and correlation with histopathological stage. Ambient temperature data (seven-day average before the examination) was obtained from a meteorological station close to the hospital. Changes of BAT, cancer, body mass index (BMI) and temperature between the different examinations were examined with Spearman's test and a mixed linear model for correlation, and with a causal inference algorithm for causality. RESULTS We found n = 283 patients with at least two examinations and active BAT in at least one of them. There was no significant interaction between the changes in BAT activation, cancer burden or BMI. Temperature changes exhibited a strong negative correlation with BAT activity (ϱ = -0.57, p<0.00001). These results were confirmed with the mixed linear model. Causal inference revealed a link of Temperature ➜ BAT in all subjects and also of BMI ➜ BAT in subjects who had lost weight and increased cancer burden, but no role of cancer and no causal links of BAT ➜ BMI. CONCLUSIONS Our data did not confirm the hypothesis that BAT plays a major role in cancer-mediated weight loss. Temperature changes are the main driver of incidental BAT activity on FDG-PET scans

Preoperative Evaluation of Pancreatic Fibrosis and Lipomatosis: Correlation of Magnetic Resonance Findings With Histology Using Magnetization Transfer Imaging and Multigradient Echo Magnetic Resonance Imaging

OBJECTIVES The purpose of this study was to evaluate the diagnostic performance of magnetization transfer (MT) imaging and multigradient echo magnetic resonance imaging (MRI) to quantify pancreatic fibrosis and lipomatosis in patients before pancreatoduodenectomy for postoperative risk stratification with histopathology as the reference standard. MATERIALS AND METHODS Twenty-four patients (age, 68 ± 8 years, 16 males) prospectively underwent quantitative MT imaging using a 2-dimensional gradient echo sequence with and without MT prepulse and multigradient echo imaging on a 3 T MRI 1 day before pancreatoduodenectomy due to adenocarcinoma of the pancreatic head region (n = 20), neuroendocrine tumor (n = 3), or intraductal papillary mucinous neoplasm (n = 1). Magnetization transfer ratio (MTR) and proton density fat fraction (PDFF) were measured in pancreatic tail (PT) and at the resection margin (RM). Histopathologically, pancreatic fibrosis was graded as mild, moderate, or severe (F1-F3), lipomatosis was graded as 0% to 10%, 11% to 30%, and greater than 30% fat deposition (L1-L3). In addition, MTR and histopathologic fibrosis was assessed in pancreatic adenocarcinoma. Mann-Whitney U test and Spearman correlation were used. RESULTS Patients with advanced pancreatic fibrosis (F3) showed a significantly higher MTR compared with the F1 group at the RM and PT (38 ± 4 vs 32.3 ± 1.6, P = 0.018 and 39.7 ± 5.5 vs 31.2 ± 1.7, P = 0.001). Spearman correlation coefficient of MTR and fibrosis grade was r = 0.532 (P = 0.011) and 0.554 (P = 0.008), respectively. Pancreatic parenchyma with advanced fat deposition (L2-L3) showed significantly higher PDFF compared with lipomatosis grade L1 (RM: P = 0.002 and PT: P = 0.001). Proton density fat fraction of pancreatic parenchyma exhibited a moderate and significant correlation with histopathologic lipomatosis grade (RM: r = 0.668 and PT: r = 0.707, P < 0.001). Magnetization transfer ratio was significantly higher in pancreatic adenocarcinoma compared with pancreatic parenchyma (44 ± 5.5 vs 36.0 ± 4.4 and 37.4 ± 5.4, P = 0.004). CONCLUSIONS Multiparametric MRI of the pancreas including MTR and PDFF maps may provide quantitative and noninvasive information on pancreatic fibrosis and lipomatosis before surgery

Dynamic non-invasive ASL perfusion imaging of a normal pancreas with secretin augmented MR imaging.

OBJECTIVES To investigate prospectively the repeatability of pancreatic perfusion measurements using arterial spin labelling (ASL) and to determine the increase in perfusion due to secretin stimulation. MATERIAL AND METHODS An (FAIR)-TrueFISP ASL sequence was applied to determine the perfusion of the pancreatic head in a 3T MRI scanner. Ten healthy volunteers (four men, six women: mean age 28.5 ± 4.6 years; age range 25-40 years) were investigated twice within 1 week. The inter-individual variability was calculated using the standard deviation. Intra-individual agreement between the first and second scan was estimated using the Pearson correlation coefficient. A paired Wilcoxon rank-sum test was used to compare perfusion at baseline (BL) and during secretin stimulation. RESULTS The mean BL perfusion of the pancreatic head was 285 ± 96 mL/100 g/min with an intra-individual correlation coefficient of 0.67 (strong) for repeated measurements. Secretin stimulation led to a significant increase (by 81%) in perfusion of the pancreatic head to 486 ±156 mL/100 g/min (p=0.002) with an intra-individual correlation of 0.29 (weak). A return to BL values was observed after 239 ± 92 s with a moderate intra-individual correlation coefficient of 0.42 for repeat measurements. CONCLUSION Dynamic non-invasive ASL imaging of the pancreas permitted quantification of pancreatic perfusion in a clinically applicable setting. KEY POINTS • ASL imaging of the pancreas permitted quantification of pancreatic perfusion • Secretin stimulation led to a significant increase in pancreatic perfusion • The intra-individual correlation coefficient for baseline perfusion was strong for repeated measurements

Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology

OBJECTIVES To compare the diagnostic accuracy of texture analysis (TA)-derived parameters combined with machine learning (ML) of non-contrast-enhanced T1w and T2w fat-saturated (fs) images with MR elastography (MRE) for liver fibrosis quantification. METHODS In this IRB-approved prospective study, liver MRIs of participants with suspected chronic liver disease who underwent liver biopsy between August 2015 and May 2018 were analyzed. Two readers blinded to clinical and histopathological findings performed TA. The participants were categorized into no or low-stage (0-2) and high-stage (3-4) fibrosis groups. Confusion matrices were calculated using a support vector machine combined with principal component analysis. The diagnostic accuracy of ML-based TA of liver fibrosis and MRE was assessed by area under the receiver operating characteristic curves (AUC). Histopathology served as reference standard. RESULTS A total of 62 consecutive participants (40 men; mean age ± standard deviation, 48 ± 13 years) were included. The accuracy of TA and ML on T1w was 85.7% (95% confidence interval [CI] 63.7-97.0) and 61.9% (95% CI 38.4-81.9) on T2w fs for classification of liver fibrosis into low-stage and high-stage fibrosis. The AUC for TA on T1w was similar to MRE (0.82 [95% CI 0.59-0.95] vs. 0.92 [95% CI 0.71-0.99], p = 0.41), while the AUC for T2w fs was significantly lower compared to MRE (0.57 [95% CI 0.34-0.78] vs. 0.92 [95% CI 0.71-0.99], p = 0.008). CONCLUSION Our results suggest that liver fibrosis can be quantified with TA-derived parameters of T1w when combined with a ML algorithm with similar accuracy compared to MRE. KEY POINTS • Liver fibrosis can be categorized into low-stage fibrosis (0-2) and high-stage fibrosis (3-4) using texture analysis-derived parameters of T1-weighted images with a machine learning approach. • For the differentiation of low-stage fibrosis and high-stage fibrosis, the diagnostic accuracy of texture analysis on T1-weighted images combined with a machine learning algorithm is similar compared to MR elastography