PET in bladder cancer imaging.

PURPOSE OF REVIEW: The aim of this study was to summarize the available evidence on different PET imaging modalities for the staging of patients diagnosed with bladder cancer (BCa). We further discuss the use of PET/computed tomography (CT) and PET/MRI with different radiopharmaceuticals to characterize tumour biology for treatment guidance. RECENT FINDINGS: Available evidence supports the benefits of PET/CT in BCa staging due to its higher accuracy in the detection of nodal metastases compared with CT alone. The use of PET/MRI is of major future interest due to the higher soft tissue contrast of MRI, which might enable the early detection of the tumour in the bladder. For the time being, the sensitivity of PET/MRI is still too low, when it comes to the diagnosis of early-stage BCa. This is mainly due to the renal excretion of the commonly used [ 18 F]FDG PET tracer, wherefore small lesions in the wall of the bladder can be missed. Novel studies using PET radiopharmaceuticals to target immune checkpoints or other immune cell targets (immunoPET) demonstrated high uptake in tumour lesions with high PD-L1 expression. The use of immunoPET could therefore help identify BCa patients who exhibit PD-L1 positive tumours for systemic immune-therapy. SUMMARY: PET/CT and PET/MRI seem to be promising imaging tools in BCa staging, especially for the detection of lymph node and distant metastases, as they are more accurate than conventional CT. Future clinical trials with novel radiopharmaceuticals and machine-learning driven PET-technologies bear the potential to help in the early detection, staging, monitoring and precision-medicine approach. Specifically, immunoPET is of high future interest, as it could help develop the concept of precision-medicine in the age of immunotherapy.

The Efficacy of MRI in the diagnostic workup of cystic fibrosis-associated liver disease: A clinical observational cohort study.

PURPOSE: To identify independent imaging features and establish a diagnostic algorithm for diagnosis of cystic fibrosis (CF)-associated liver disease (CFLD) in CF patients compared to controls using gadoxetic acid-enhanced MRI. METHODS: A total of 90 adult patients were enrolled: 50 with CF, 40 controls. The CF group was composed of two subgroups: a retrospective test subgroup (n = 33) and a prospective validation subgroup (n = 17). Controls (patients with normal liver enzymes and only benign focal liver lesions) were divided accordingly (27:13). MRI variables, including quantitative and qualitative parameters, were used to distinguish CFLD from controls using clinical symptoms, laboratory tests and Debray criteria. Disease severity was classified according to Child-Pugh and Albumin-Bilirubin (ALBI) scores. Fifteen qualitative single-lesion CF descriptors were defined. Two readers independently evaluated the images. Univariate statistical analysis was performed to obtain significant imaging features that differentiate CF patients from controls. Through multivariate analysis using chi-squared automatic interaction detector (CHAID) methodology the most important descriptors were identified. Diagnostic performance was assessed by receiver-operating characteristic (ROC) analysis. RESULTS: Three independent imaging descriptors distinguished CFLD from controls: (1) presence of altered gallbladder morphology; (2) periportal tracking; and (3) periportal fat deposition. Prospective validation of the classification algorithm demonstrated a sensitivity of 94.1% and specificity of 84.6% for discriminating CFLD from controls. Disease severity was well associated with the imaging features. CONCLUSIONS: A short unenhanced MRI protocol can identify the three cardinal imaging features of CFLD. The hepatobiliary phase of gadoxetic acid-enhanced MRI can define CFLD progression. KEY POINTS: • Using a multivariate classification analysis, we identified three independent imaging features, altered gallbladder morphology (GBAM), periportal tracking (PPT) and periportal fat deposition (PPFD), that could diagnose CFLD with high sensitivity, 94.1 % (95% CI: 71.3-99.9) and moderate specificity, 84.6 % (95% CI: 54.6-98.1). • Based upon the results of this study, gadoxetic acid-enhanced MRI with DWI is able to diagnose early-stage CFLD, as well as its progression.

Characteristics of incidentally found thyroid nodules in computed tomography: comparison with thyroid scintigraphy.

BACKGROUND: In our daily experience, the differentiation between a cold and hot nodule is a very important factor for further clinical management of the patient. In this study, we compared the characteristics of incidentally found thyroid nodules detected on computed tomography (CT) to thyroid scintigraphy (TS). METHODS: Diagnostic reports from chest CT with intravenous contrast and TS examinations performed from January 2013 to January 2016 were analyzed retrospectively. We identified 70 subjects: 50 with thyroid nodules and 20 control subjects without thyroid nodules. The examination time of the TS was a minimum of two to four months after a chest CT. Chest CTs were performed in the arterial phase after the application of contrast media. RESULTS: Patients with a cold nodule had a significantly lower Hounsfield Unit (HU) Nodule(N)/Parenchyma (P) ratio values than the patients with a hot or warm nodule (P < 0.05). The cut-off HU N/P ratio value with the highest sum of sensitivity and specificity for the prediction of a functioning nodule was 69 (95% CI: 0.79-0.95). CONCLUSIONS: Our results imply that the HU N/P ratio of the thyroid nodule on the chest CT should be taken into account to assess the functionality of the nodule. A lower HU N/P ratio should alert the radiologist or nuclear medicine physician to the possibility that the nodule might be cold and thus more prone to malignancy.

Radiological diagnosis of dialysis-associated complications.

In daily clinical practice, the radiologist in the context of diagnosis often faces dialysis-associated complications. The complications are numerous and range from infections, catheter dysfunctions, haematomas, cardiovascular diseases, digital ischaemia, and pseudoaneurysms to shunt stenosis. In this pictorial essay, we take a close look at the imaging diagnostics of the most common complications in dialysis patients. Teaching Points • The occurrence of venous stenosis in haemodialysis patients is up to 41 %. • Catheters usually have a fibrin sheath that can be rinsed but not aspirated. • The steal phenomenon occurs in 75-90 % of patients with a shunt system. • Arterial pseudoaneurysms can cause a number of complications.

Texture-based classification of different gastric tumors at contrast-enhanced CT.

PURPOSE: To determine the feasibility of texture analysis for the classification of gastric adenocarcinoma, lymphoma, and gastrointestinal stromal tumors on contrast-enhanced hydrodynamic-MDCT images. MATERIALS AND METHODS: The arterial phase scans of 47 patients with adenocarcinoma (AC) and a histologic tumor grade of [AC-G1, n=4, G1, n=4; AC-G2, n=7; AC-G3, n=16]; GIST, n=15; and lymphoma, n=5, and the venous phase scans of 48 patients with AC-G1, n=3; AC-G2, n=6; AC-G3, n=14; GIST, n=17; lymphoma, n=8, were retrospectively reviewed. Based on regions of interest, texture analysis was performed, and features derived from the gray-level histogram, run-length and co-occurrence matrix, absolute gradient, autoregressive model, and wavelet transform were calculated. Fisher coefficients, probability of classification error, average correlation coefficients, and mutual information coefficients were used to create combinations of texture features that were optimized for tumor differentiation. Linear discriminant analysis in combination with a k-nearest neighbor classifier was used for tumor classification. RESULTS: On arterial-phase scans, texture-based lesion classification was highly successful in differentiating between AC and lymphoma, and GIST and lymphoma, with misclassification rates of 3.1% and 0%, respectively. On venous-phase scans, texture-based classification was slightly less successful for AC vs. lymphoma (9.7% misclassification) and GIST vs. lymphoma (8% misclassification), but enabled the differentiation between AC and GIST (10% misclassification), and between the different grades of AC (4.4% misclassification). No texture feature combination was able to adequately distinguish between all three tumor types. CONCLUSION: Classification of different gastric tumors based on textural information may aid radiologists in establishing the correct diagnosis, at least in cases where the differential diagnosis can be narrowed down to two histological subtypes.