Imaging is integral to detection and characterization of complications after prostate interventions, including vascular, infectious, urinary, and radiation-related complications, and facilitates timely diagnosis and management.
Although Rosai-Dorfman disease has nonspecific imaging features, imaging remains essential for delineating disease extent, predicting prognosis, and assessing treatment response once the diagnosis is established through integrated clinical, imaging, and histopathologic evaluation.
Optimal Selection of the Effective Echo Time (
TE
eff
) for
T2
‐Weighted Fast
ABSTRACT Background Clinical T 2 ‐weighted (T2W) MRI of prostate cancer (PCa) usually implements a 2D fast‐spin‐echo (FSE) sequence, but understanding the echo‐time‐dependent contrast behavior is not straightforward due to the complicated FSE signal evolution. Consequently, consensus‐based recommendations on the optimal effective echo time (TE eff ) to maximize contrast are lacking. Purpose To investigate the effect of TE eff on PCa lesion contrast in prostate T2W MRI. Study Type Phantom and in vivo prospective study. Subjects A standard MRI phantom and 53 prostate cancer patients (29 for image evaluation and 24 for quantitative lesion analysis). Field Strength and Sequence Multi‐slice T2W FSE sequence at 3 T acquired at multiple TE eff values. Assessment Three readers (13, 25, and 27 years' experience) evaluated TE eff = 100 ms versus 150 ms on diagnostic quality and reader preference. The effective T 2 relaxation rates ( T 2,eff ) were measured using FSE sequences in the phantom and used to predict the optimal TE eff maximizing T2W contrasts. From multi‐TE eff scans of subjects with suspected PCa, T 2,eff values of PCa lesions and healthy tissue were measured and used to calculate the optimal TE eff maximizing the lesion contrast. In vivo contrast metrics were measured as a function of TE eff . Statistical Tests Wilcoxon test of reader scores, with p < 0.05 defining statistical significance. Results No statistically significant difference was found in diagnostic quality between TE eff = 150 ms and 100 ms images, but all three readers significantly favored TE eff = 150 ms. Phantom experiments demonstrated that TE eff ‐dependent FSE signal progression can be characterized by T 2,eff values typically 40% longer than actual T 2 values, allowing accurate prediction of optimal TE eff within 2%–5%. Applied to PCa imaging, in vivo measurements indicated that effective T 2 relaxation times of the prostate are on average 1.5× longer than published T 2 values. Data Conclusion The benefits of TE eff = 150 ms versus 100 ms in prostate T2W FSE were supported by reader preference, phantom experiments, in vivo measurements, and analytic optimizations. Evidence Level 2. Technical Efficacy 2.
Multisystemic Imaging Features of Coccidioidomycosis
An understanding of regions of endemicity and the spectrum of organ system involvement can improve recognition of the imaging features of coccidioidomycosis, which can overlap with those of other diseases.
Imaging Hereditary Cancer Syndromes in the Abdomen and Pelvis
Radiologists are uniquely positioned to play a critical role in the detection, surveillance, and characterization of hereditary abdominal cancer syndromes.
Frequently overlooked yet clinically significant, the urachus can exhibit a diverse range of pathologic conditions, which can pose a diagnostic challenge at imaging for the radiologist and which require a thorough understanding of urachal embryogenesis.
Multifaceted risk stratification is required for management of upper tract urothelial carcinoma, and imaging plays an important integrated role in diagnosis and management.
Fully Automated Deep Learning Model to Detect Clinically Significant Prostate Cancer at MRI
The performance of a deep learning model was not different from that of radiologists in the detection of clinically significant prostate cancer at MRI, and gradient-weighted class activation maps localized the tumor.
MRI in Adult Patients with Active and Inactive Implanted MR-conditional, MR-nonconditional, and Other Devices