Fig 1: Summary of findings in contractions, sorted by ascending gestational age at scan (ND, no data for gestational age). In cases where placental volumes have currently been measured, contractions were defined as placental pump, PP, if contraction was accompanied by a reduction in placental volume, Braxton-Hicks, BH, if there was no change. In subject 5, changes at the start of the contraction could not be assessed because they had already occurred at the start of the scan (‘cut off’).

Fig 5: Typical progression of hypointense signal during a contraction. A) before the contraction, B) shape has started changing, thin dark lines across placenta (37 seconds after A), C) placenta is fully contracted, almost completely dark besides some area near basal plate (72 s after A), D) dark pattern remains longest on side of chorionic plate (82 s after A), E) pattern has faded except for thin lines outlining cotyledons (118 s after A), F) returned to relaxed state (179 s after A).

Tracking inferior vena cava (IVC) and ductus venosus (DV) blood flow across the fetal heart. (A1) Dynamic coronal view. (A2-A4) Particle traces, released from the IVC (blue) and DV (red), at different phases of the cardiac cycle. Parallel streams from the IVC and DV enter the right atrium (A2), with oxygenated blood from the DV preferential shunted into the left ventricle (A3) to supply the coronary and cerebral circulations (A4). (A5) Corresponding flow map, colored by hypothetical oxygenation.

Fetal reconstructions and flow comparisons. (A) Axial, coronal, and sagittal slices. (B) 3D rendering of slice-to-volume reconstruction (SVR). (C) Oblique slices from reconstructed volume using SVR. (D) Coronal view of systolic particle tracking from SVR flow. Comparison between mean flow measurements from SVR and 2D Cartesian flow: (E) Linear regression with red line depicting the best fit to the data and (F) Bland-Altman plot comparing the mean flows.

Figure 2. Representative FBV distribution for a control rhesus macaque. FBV ranges from 0 to 1, with 1 being 100% blood in certain placental regions. FBV exhibits regional heterogeneity, similar to heterogeneous perfusion [7].

Figure 3. Measurements of maternal placental blood volume (MPBV) and fractional blood volume (FBV) as a function of gestational age. MPBV shows constant increase throughout pregnancy; FBV exhibits a more heterogeneous trend, with higher relative change from first to second gestational age time point.

Figure 2. Placental perfusion maps overlaid onto the reference M0 scans for two subjects, illustrating the difference between high perfusion with high BMI (top, 397.83 mL/100 mg/min, BMI = 31.16 kg/m²) and low perfusion with low BMI (bottom, 131.49 mL/100 mg/min, BMI = 22.96 kg/m²).

Figure 3. Regression analysis of perfusion and BMI, demonstrating a statistically significant positive relationship. (R² = 0.076, p = 0.020) Adverse maternal outcomes are marked: Gestational diabetes (GD), gestational hypertension (GH), preeclampsia (PrE), preterm labor (preterm), and fetal growth restriction (FGR). If outcome data was not available for a case, the data point is plotted as unknown (Unkn). The relationship between maternal outcomes and perfusion will be investigated in a later work.

Figure 1. (A-B) Diagrams of the FC and NC diffusion-encoding gradients with a diffusion duration of ∆. (C) Definition of the maternal and fetal ROIs of the placenta overlaid on the b0 image. (D-F) Representative f_b and v_b maps of the placenta from a maternal hyperglycemia (MH) patient (D), a fetal growth restriction (FGR) patient (E), and a normal control (F).

Figure 3. (A) The classification accuracy, AUC, sensitivity, and specificity of each IVIM parameter and their combinations (as features in classification), based on a linear SVM with five-fold cross validation. The combination of f_b and v_b from NC-FC model showed the best performance. (B-C) The classification between MH and Control¹ (B) and between FGR and Control² (C) in the two-dimensional feature space of v_b-f_b. The dots represent correctly identified cases, and stars represented mis-classified cases by SVM.

28 week old subject with labeled placenta tissue maps. (Top row: reference label map, Middle row: map generated by model trained on full 2D scheme, Bottom row: map generated by model trained on full 3D scheme.)

19 week old subject with labeled placenta tissue maps. (Top row: reference label map, Middle row: map generated by model trained on full 2D scheme, Bottom row: map generated by model trained on full 3D scheme.)

Figure 1: The proposed pipeline for the automatic placental maturation assessment is depicted consisting of the data acquisition, automatic segmentation used to calculate the placental mean T2* and the Gaussian Process regression fit or prediction, which is used to characterize placental health. All parts are discussed in the methods section.

Figure 5: Top: The placental health Z-scores are strongly related with degree of prematurity measured as GA at birth (right) and extremely low birth weight centile (left). Bottom: Z-scores grouped by histopathological examination results color-coded by GA at birth. Participants with maternal vascular malperfusion (MVM) exhibit lower Z-scores and belong to the group delivered prematurely. Chorioamnionitis does not affect Z-scores in control cases but seems to correlate to normal Z-scores in high-risk participants.

Figure 3: Seven-component InSpect run on 13 placenta diffusion-relaxometry scans. The leftmost boxes display the canonical spectral components, shared across all 13 participants. The remaining boxes show the corresponding component weighting maps for 6 of the 13 scans, with each column displaying a single participant’s maps (see Figure 4 for the remaining 7 maps). Two participants had been diagnosed with a pregnancy complication at scan time (red outline). Note that the final columns of this Figure and Figure 4 display maps for the same participant, scanned twice, four weeks apart.

Figure 4: InSpect maps for the 7 participants not shown in figure 3 from the seven-component InSpect run on 13 placenta diffusion-relaxometry scans. Each row displays maps for a single canonical spectral component - see first column of Figure 3 for the corresponding spectra. Columns display the maps for a single scan. Note that the final column in Figures 3 and 4 displays maps for the same participant, scanned twice.

Generated continuous 4D atlas of the fetal thorax development during [22; 32] weeks GA range (0.5mm isotropic resolution).

Lung growth charts for 100 fetuses without reported anomalies scanned during [22; 32] weeks GA period (a). The extracted indices include: (b) total lung volume (TLV) in comparison to the Cannie’s, 2008 [3] Meyers’s, 2018 [4] formulas; (c) liver to lung signal intensity ratio (LLSiR); (d) total fetal volume (TFV); (e) TLV/TFV ratio. There is a clear correlation between TLV, LSSiR and TFV, which the TLV/TFV values are independant. The 3D models of the fetal lungs and hearts segmented from the 4D atlas at 22, 27 and 32 weeks GA time points are shown in (f).

Figure 2: Illustration of the method. The input is fetal T₂ weighted volume. (1) Brain ROI computation using 3D CNN; (2) Segmentation of the orbits for 2D and 3D measurements using 2D U-Net; (3) Segmentation of lens and globe for OD-LA (ocular diameter lens aligned) measurement using 2D U-Net; (4) Ocular measurements using geometric algorithms.

Figure 3: Representative examples of automatic ocular fetal 2D measurements for three fetuses. OD measurements are presented for both eyes (OD 1 and 2). Note that the algorithm may choose a different slice for each measurement (for example, IOD, OD1 and OD2 of fetus 3).

Figure 4 a),b) Raw diffusion data fitted using bi-exponential model for sponge 1 and 2 at the 5 different diffusion times. C),D) Maps of IVIM and Kurtosis parameters measured at a diffusion time of 23 ms separated into the two peaks observed on the flow data.

Figure 2 Phase histograms for both sponges, imaged at a VENC of ± 0.70 mm/s at 5 different diffusion times. Histogram plotted with blue bars, Gaussian fit is plotted with a red curve, peak 1 and 2 means indicated by vertical green and orange lines, respectively.

Figure 4 Histogram of peak positions from ILT fit over all ROI's from a single participant.

Figure 1 A) Example of weightings produced by the ILT for a single voxel, with sections overlaid.

B) The same voxel, with the fits produced by both the IVIM and ILT models

Fig 1. Baseline T2* with gestational age

Images in a 56-year-old woman with biopsy-proven squamous cell carcinoma of the cervix. Diffusion-weighted MR images and ADC maps show a cervical mass with an irregular margin, restricted diffusion and disruption of the cervical stromal rim. Compared with ss-EPI DWI and rs-EPI DWI, rFOV DWI images show the lesion with a clear border and fewer artifacts, and clearly demonstrate the findings of parametrial invasion in the right side (arrow).

Comparison of qualitative analysis scores among the reduced FOV DWI, rs-EPI DWI and ss-EPI DWI

IVIM-DWI measurement, on Fifure# 1A (b = 800 s/mm2), two radiologists drew ROI three times to get the values on the maps of D, D* and f, respectively (Figure#1B-1D). Texture analysis, on Figure#1E, the radiologists drew the ROI at the maximum area of the lesion in IVIM-DWI.

The specificity of the specific-sensitivity curve obtained by logistic regression was 71.2%, the sensitivity was 65.8%, the positive predictive value was 0.762, and the negative predictive value was 0.684. The obtained characteristics were verified by the high, middle and low differentiation groups of the validation group. The area under the ROC was 0.896, 0.700, 0.716, the average AUC was 0.765, and the specificity was 86.4%, 69.2%, 76.1% respectively , sensitivity is 68.6%, 79.5%, 81.2%.

Fig2 A-F A 37-year-old woman has a cervical mass with circum wall involvement.

Figure 1. A-H 36 years old patients with moderately-highly differentiated endometrioid adenocarcinoma. A.T2WI image; B. ADC diagram of DWI sequence, ADC value was 1.014×10-3mm²/s; C. DC avg image, DC avg value was 1.025×10-9mm²/s; D. FA image, FA value was 0.134; E. Iso image, Iso value was 114.61; F. VRA image, VRA value was 0.020; G. Exat image, the Exat value was 0.541; H. T2-WT image, T2-WT value was 114.615;

Figure 2. A-H 64 years old patients with endometrial polyp. A.T2WI image; B. ADC diagram of DWI sequence, ADC value was 1.84×10-3mm²/s; C. DC avg image, DC avg value was 1.73×10-9mm²/s; D. FA image, FA value was 0.119; E. Iso image, Iso value was 254.755; F. VRA image, VRA value was 0.016; G. Exat image, the Exat value was 0.355; H. T2-WT image, T2-WT value was 254.76;

A 63 years old patient with poorly differentiated endometrioid adenocarcinoma. 1a was the original image of DTI sequence, location of lesions was shown by the yellow arrow on; 1B was the DC avg map, DC avg value was 0.718×10-9mm2/s; 1c was the FA map, FA value was 0.260; 1d was the Iso map, Iso value was 229.340; 1e was the VRA map, VRA value was 0.051; 1f was the Exat map, Exat value was 0.652; 1g was the T2-wt map, T2-wt value was 229.340; 1h was the ADC map of DWI sequence, ADC value was 0.740×10-3mm2/s

Tabel 1：Comparison of quantitative parameters DTI between MSI group and MSS group

Table 1 The performance of logistic model identified Endometrioid Endometrial Adenocarcinoma (EEA) with different pathological grades

Testing set: ROC curve of the logistic model (3A), and the AUC is 0.840. Calibration curve of the radiomics model (3B). Decision curve analysis for the logistic model (3C).

Figure 1. Representative ADC₁ map of the ovaries overlaid on T₂ FSE images in a single participant through each week (A-D) of the menstrual cycle. Asterisks in C and D indicate locations where distortion artifacts were severe due to the proximity of the ovary to the colon resulting in incomplete distortion correction of the ovary.

Figure 2. The diffusion properties of ovaries were described using a bi-exponential model S_i(b) = S₀[(1-β)e^-bADC₁+βe^-bADC₂]. Estimated A) ADC₁, B) ADC₂, and C) β throughout the menstrual cycle for six participants (colors) are shown.

Table

FIG1

Figure 1. (1a-1b) images for a 70-year-old female with right ovarian serous cystadenoma: T2WI(1a) and R2*(1b) images. (2a-2b) images for a 58- year- old female with right ovarian borderline serous papillary cystadenoma: T2WI(2a) and R2*(2b) images. (3a-3b) images for a 63- year- old female with left ovarian serous cystadenocarcinoma: T2WI(3a) and R2*(3b) images.

Table 3. Area under curve (AUC), sensitivities, specificities and cut-off values of R2* in detection of ovarian tumor aggressiveness.

Table 2. The statistical results of univariate analysis of the main CT and MRI features of the recurrence and no recurrence groups

Table 1. The statistical results of univariate analysis of the clinical characteristics of the recurrence and no recurrence groups

Figure 2 Vertical displacement (V) in millimeters on the contour of pelvic organs at rest, during the second contraction and during the second time straining. The white line represents the initial contours, the colors represent the amount of displacement. During the second time straining in upright position there is a mismatch between the displacement contour and the bladder, indicated with the white arrow. This is probably caused by in and out of plane movement of the organs during contraction and straining, but also by the extreme mobility of the bladder in patients with POP.

Figure 1 Displacement analysis of the cervix. a) Point at which displacement analysis is performed (green) b) Vertical displacement in supine (black) and upright position (red). In supine position, both contraction and strain are clearly visible. In upright position the displacement during contraction is larger than in supine position, and displacement during straining is not visible. V: vertical displacement, U: horizontal displacement

Figure 1 Sagittal FSE images of one subject at different moments during the day in supine and upright position, on which the measured distances of the bladder and cervix to the pubococcygeal line (d_bladder and d_cervix respectively) are visualized. d_bladder is comparable over different measurements during the day in both supine and upright position. d_cervix is also comparable during the day in supine position, but in upright position a descent is visible, mainly between the morning and midday measurements.

Figure 2 Measured distances of the bladder and cervix to the pubococcygeal line (d_bladder and d_cervix respectively) at different moments during the day in supine and upright position. a) There seems to be a small descent of the bladder during the day. This descent is comparable between supine and upright position. b) The cervix descends during the day. This descent is larger in upright position than in supine.

the degree of pubic injury

The correlation between the score of pubic injury and the score of levator anal muscle injury