Intravoxel incoherent motion (IVIM)-derived perfusion fraction mapping for the visual evaluation of MR-guided high intensity focused ultrasound (MR-HIFU) ablation of uterine fibroids

Figures & data

Table 1. Study sample characteristics.

Age (years)		42.4 (± 7.3)
BMI (kg/m^2)		24.8 (± 3.5)
Abdominal fat layer (cm)		2.2 (± 1.19)
Uterine position	AVF	40 (81%)
	RVF	6 (12%)
	Upwards	3 (6%)
Number of fibroids treated	1	36 (73%)
	2	5 (10%)
	3	6 (12%)
	4	1 (2%)
	5	1 (2%)
FIGO class location	Submucosal	21 (27%)
	Intramural	24 (31%)
	Subserosal	21 (27%)
	Hybrid	11 (14%)
Funaki class	1	9 (12%)
	2	58 (76%)
	3	9 (12%)
Maximum diameter (cm)		5.6 (± 3.5)
Fibroid volume pre-HIFU (cm)		137.6 (± 227.7)
Non-Perfused Volume (%)		66.3 (± 34.1)

Clinical characteristics of the participants who had undergone the magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) treatment for symptomatic uterine fibroids and were analyzed in this retrospective study.

Figure 1. Example ROI placement for intensity and CNR analysis between the IVIM-based non-perfused volume (NPV) and surrounding tissue. This example shows an $f$-map calculated with least-squares fitting without T2-correction.

Figure 2. Diffusion weighted imaging (DWI) b-value images (first two rows) and IVIM perfusion fraction maps (lower rows) of a uterine fibroid before and after MR-HIFU treatment, generated using conventional least squares ($f^{\mathit{\text{lq}}}$) and neural net ($f^{\mathit{\text{nn}}}$) fitting techniques, and a T2-uncorrected ($f$) and T2-corrected ($f_c$) IVIM model. Based on the contrast enhanced-T1w (CE-T1w) scan, the fibroid’s perfusion has been successfully eliminated in this patient. This seems to be accurately reflected on the post-HIFU perfusion fraction maps, as perfusion fraction is decreased within the fibroid in comparison to screening. The HIFU-transducer, which is located in an oil tank, is visible in the post-HIFU DWI and perfusion fraction maps and marked in the post-HIFU b0 DWI image. During treatment, the patient lies prone on a membrane on top of the transducer.

Figure 3. Mean perfusion fraction ($f$/$f_c$) in IVIM perfusion fraction maps, between the area with low perfusion fraction in the treated fibroid and surrounding tissue, after an MR-HIFU treatment. All four types of IVIM perfusion fraction maps showed a significant difference in perfusion fraction between low-value area and surrounding tissue.

Figure 4. Contrast-to-noise (CNR) analysis between the low-value area in the treated fibroid and surrounding tissue in IVIM perfusion fraction ($f$/$f_c$) maps. The CNR was not significantly different for any of the perfusion fraction map combinations. $\mathit{\text{lq}}$ = least squares, $\mathit{\text{nn}}$ = neural net, $c$ = T2 corrected.

Figure 5. Bland-Altman plot of areas with low perfusion fraction ($f$/$f_c$) measured on perfusion fraction maps and non-perfused areas on reference contrast enhanced T1-weighted scans, immediately after MR-HIFU treatments of uterine fibroids. $\mathit{\text{lq}}$ = least squares, $\mathit{\text{nn}}$ = neural net, $c$ = T2 corrected.

Table 2. Dice similarity coefficient between perfusion fraction maps and contrast-enhanced T1-weighted MRI.

NPV source	${\mathit{f}}^{\mathit{\text{lq}}}$	${\mathit{f}}_{\mathit{c}}^{\mathit{\text{lq}}}$	${\mathit{f}}^{\mathit{\text{nn}}}$	${\mathit{f}}_{\mathit{c}}^{\mathit{\text{nn}}}$	CE-T1w
$f^{\mathit{\text{lq}}}$	x	0.900	0.878	0.878	0.724
$f_c^{\mathit{\text{lq}}}$	0.900	x	0.886	0.891	0.734
$f^{\mathit{\text{nn}}}$	0.978	0.886	x	0.904	0.714
$f_c^{\mathit{\text{nn}}}$	0.878	0.891	0.904	x	0.722
CE-T1w	0.724	0.734	0.714	0.722	x

Dice similarity coefficient (DSC) of the non-perfused volume (NPV) delineated on the four different types of IVIM perfusion fraction ($f$/$f_c$) maps, and the NPV delineated on paired contrast enhanced (CE)-T1w scans. NPVs delineated on $f_c^{\mathit{\text{lq}}}$-maps show the highest overlap with CE-T1w scans. Bold values represents Dice coefficient, between both groups (f-maps and CE-T1w). $\mathit{\text{lq}}$ = least squares, $\mathit{\text{nn}}$ = neural net, $c$ = T2 corrected.

Data availability statement

The clinical, imaging and treatment data is not publicly available, as the study participants did not give consent to share their data publicly with third parties.