Computer-aided diagnosis of skeletal metastases in multi-parametric whole-body MRI.

The confident detection of metastatic bone disease is essential to improve patients' comfort and increase life expectancy. Multi-parametric magnetic resonance imaging (MRI) has been successfully used for monitoring of metastatic bone disease, allowing for comprehensive and holistic evaluation of the total tumour volume and treatment response assessment. The major challenges of radiological reading of whole-body MRI come from the amount of data to be reviewed and the scattered distribution of metastases, often of complex shapes. This makes bone lesion detection and quantification demanding for a radiologist and prone to error. Additionally, whole-body MRI are often corrupted with multiple spatial and intensity distortions, which further degrade the performance of image reading and image processing algorithms. In this work we propose a fully automated computer-aided diagnosis system for the detection and segmentation of metastatic bone disease using whole-body multi-parametric MRI. The system consists of an extensive image preprocessing pipeline aiming at enhancing the image quality, followed by a deep learning framework for detection and segmentation of metastatic bone disease. The system outperformed state-of-the-art methodologies, achieving a detection sensitivity of 63% with a mean of 6.44 false positives per image, and an average lesion Dice coefficient of 0.53. A provided ablation study performed to investigate the relative importance of image preprocessing shows that introduction of region of interest mask and spatial registration have a significant impact on detection and segmentation performance in whole-body MRI. The proposed computer-aided diagnosis system allows for automatic quantification of disease infiltration and could provide a valuable tool during radiological examination of whole-body MRI.

Whole-body MRI in oncology: can a single anatomic T2 Dixon sequence replace the combination of T1 and STIR sequences to detect skeletal metastasis and myeloma?

OBJECTIVES: To compare the diagnostic accuracy of a single T2 Dixon sequence to the combination T1+STIR as anatomical sequences used for detecting tumoral bone marrow lesions in whole-body MRI (WB-MRI) examinations. METHODS: Between January 2019 and January 2020, seventy-two consecutive patients (55 men, 17 women, median age = 66 years) with solid (prostate, breast, neuroendocrine) cancers at high risk of metastasis or proven multiple myeloma (MM) prospectively underwent a WB-MRI examination including coronal T1, STIR, T2 Dixon and axial diffusion-weighted imaging sequences. Two radiologists independently assessed the combination of T1+STIR sequences and the fat+water reconstructions from the T2 Dixon sequence. The reference standard was established by consensus reading of WB-MRI and concurrent imaging available at baseline and at 6 months. Repeatability and reproducibility of MRI scores (presence and semi-quantitative count of lesions), image quality (SNR: signal-to-noise, CNR: contrast-to-noise, CRR: contrast-to-reference ratios), and diagnostic characteristics (Se: sensitivity, Sp: specificity, Acc: accuracy) were assessed per-skeletal region and per-patient. RESULTS: Repeatability and reproducibility were at least good regardless of the score, region, and protocol (0.67 ≤ AC1 ≤ 0.98). CRR was higher on T2 Dixon fat compared to T1 (p < 0.0001) and on T2 Dixon water compared to STIR (p = 0.0128). In the per-patient analysis, Acc of the T2 Dixon fat+water was higher than that of T1+STIR for the senior reader (Acc = +0.027 [+0.025; +0.029], p < 0.0001) and lower for the junior reader (Acc = -0.029 [-0.031; -0.027], p < 0.0001). CONCLUSIONS: A single T2 Dixon sequence with fat+water reconstructions offers similar reproducibility and diagnostic accuracy as the recommended combination of T1+STIR sequences and can be used for skeletal screening in oncology, allowing significant time-saving. KEY POINTS: • Replacement of the standard anatomic T1 + STIR WB-MRI protocol by a single T2 Dixon sequence drastically shortens the examination time without loss of diagnostic accuracy. • A protocol based on fat + water reconstructions from a single T2 Dixon sequence offers similar inter-reader agreement and a higher contrast-to-reference ratio for detecting lesions compared to the standard T1 + STIR protocol. • Differences in the accuracy between the two protocols are marginal (+ 3% in favor of the T2 Dixon with the senior reader; -3% against the T2 Dixon with the junior reader).

Acute Pain in Right Iliac Fossa during Pregnancy.

Teaching Point: The diagnosis of epiploic appendagitis in case of pain in the right iliac fossa in pregnant woman shouldn't be forgotten.

Schwannoma: A Rare Cause of Perineal Pain.

Teaching point: Unexplained persistent perineal pain poses a differential diagnosis, including pelvic nerve lesions. The rare occurrence of pelvic schwannoma is easily shown by a MRI as a T2-hyperintense enhancing mass.