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High-resolution Reduced Field-of-view Diffusion-weighted Magnetic Resonance Imaging in the Diagnosis of Cervical Cancer

Overview
Specialty Radiology
Date 2023 Jun 7
PMID 37284113
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Abstract

Background: Magnetic resonance imaging (MRI) has now become the best modality for the preoperative staging of cervical cancer. This study was to compare the value of high-resolution reduced field-of-view diffusion-weighted MR imaging (r-FOV DWI) with conventional field-of-view (c-FOV DWI) in the diagnosis of cervical cancer.

Methods: Forty-five patients (25 patients with cervical cancer and 20 patients with normal cervix) received magnetic resonance (MR) scans (3.0T), including both r-FOV DWI and c-FOV DWI sequences. The image quality (IQ) of both sequences was subjectively assessed by two attending radiologists using a double-blind method and quantitatively by the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Moreover, apparent diffusion coefficient (ADC) values for cervical cancer were blindly measured by one technician on the ADC map.

Results: The subjective scores of r-FOV DWI images were higher than those of c-FOV DWI (P<0.0001), and the interrater reliability was in good agreement [Cohen's kappa coefficient (κ) =0.547-0.914]. There was a significant difference in CNR between the two DWI image groups (r-FOV DWI 12.73±5.56 c-FOV DWI 11.21±5.92, P=0.019). The difference in mean ADC values between the two DWI sequences was statistically significant [r-FOV DWI (0.690±0.195)×10 mm/s c-FOV DWI (0.794±0.167)×10 mm/s, P<0.001]. The ADC value of cervical cancer lesions [(0.690±0.195)×10 mm/s] was significantly lower than that of normal cervix ADC value [(1.506±0.188)×10 mm/s].

Conclusions: r-FOV DWI can effectively improve the spatial resolution of the image while reducing distortion and artifacts. Furthermore, it can help to diagnose cervical cancer more accurately for the more realistic ADC values.

Citing Articles

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Zhang K, Yu B, Tang M, Li Y, Wu M, Lv F Quant Imaging Med Surg. 2024; 14(6):3851-3862.

PMID: 38846274 PMC: 11151224. DOI: 10.21037/qims-23-1718.


The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.

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