Whole-body Diffusion-weighted Imaging Research Articles

Abstract PO1-06-06: Underestimation of metastatic spread in patients with lobular breast cancer: results from the post-mortem tissue donation program UPTIDER

Abstract Background: Invasive lobular carcinoma (ILC) accounts for 15% of all invasive breast cancers (BC) and has a peculiar metastatic spread in comparison to BC of no-special type. Since ILC is less likely to disrupt normal tissue architecture and is usually non-mass forming, imaging of ILC lesions entails many challenges. Insights into pathologic versus radiological metastatic invasion can lead to better diagnostic and monitoring tools for patients with ILC. Here, we compare microscopical findings during autopsy with clinical findings prior to death in patients with metastatic ILC included in our post-mortem tissue donation program UPTIDER (NCT04531696). Methods: UPTIDER was started in November 2020 in University Hospitals Leuven/KU Leuven with inclusion of patients with stage IV BC who were willing to participate. One of the predefined subgroups consisted of patients with primary pure (i.e. not mixed) ILC. Samples were taken from different macroscopically invaded and non-invaded sites. Clinical data on disease progression, imaging, biochemistry and treatment regimens were extracted from patient files. The number of samples that were preregistered as pathological served as a surrogate for lesions that were seen on imaging performed during the treatment of the patient. These samples are compared to microscopical findings of the autopsy. Results: Since the start of UPTIDER, an autopsy has been performed on 6 patients with pure ILC (26.1% of all autopsies). Median age at initial diagnosis was 52 years (range: 37 – 80 years). Three patients (50.0%) had stage IV disease at diagnosis, the others relapsed on average 162.7 months (range: 55 – 358 months) after initial diagnosis. The average time between clinical occurrence of metastases and death was 44.8 months (range: 15 – 83 months). Median number of treatment lines for stage IV disease was 5 (median endocrine lines 2; median chemotherapy regimens 3.5). To follow disease evolution, computed tomography of thorax and abdomen was used for 4 (66.7%) patients and whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) for the remaining 2 (33.3%). Median time between last premortem imaging and death was 5.9 weeks (range: 1.6 – 16.6 weeks). At autopsy, a median of 26 unique metastases (range: 12-36) were sampled per patient. Table 1 gives an overview on the unique microscopically invaded metastases that were sampled per patient. Only 47.3% of the sampled unique metastases was preregistered. Of all unique metastases, 26.7% appeared macroscopically normal during autopsy. Tissues that appeared normal but turned out to be microscopically infiltrated included liver, stomach, adrenal glands, heart, pericardium, visceral and subcutaneous fat tissue. There were 2 patients with normal appearing, microscopically infiltrated livers. In these patients, elevation of γGT and transanimases was seen in the months prior to death. Conclusions: The disease burden of metastatic ILC reported on premortem imaging does not reflect the microscopical findings at autopsy. One of the priorities of metastatic ILC research should be the development of diagnostic tools to better estimate the extent of the disease. Future analyses of the performed postmortem MRIs in our study can aid in improving the interpretation of WB-DWI/MRI for patients with ILC. For now, clinicians should consider that unexplained clinical and/or biochemical findings might indicate progression of ILC. Table 1: patient overview on performed imaging and unique metastases sampled during autopsy CT = computed tomography; ER = estrogen receptor; HER2 = human epidermal growth factor receptor 2; pt = patient; WB-DWI MRI = whole-body diffusion-weighted magnetic resonance imaging *exclusion of samples of patient 2012 since no preregistration was performed for this patient due to unexpected death Citation Format: Karen Van Baelen, Gitte Zels, Maxim De Schepper, Marion Maetens, Josephine Van Cauwenberge, Tatjana Geukens, Kristien Borremans, François Richard, Amena Mahdami, Ha-Linh Nguyen, Sophia Leduc, Anirudh Pabba, Ann Smeets, Ines Nevelsteen, Patrick Neven, Hans Wildiers, Vincent Vandecaveye, Wouter Van Den Bogaert, Giuseppe Floris, Christine Desmedt. Underestimation of metastatic spread in patients with lobular breast cancer: results from the post-mortem tissue donation program UPTIDER [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-06-06.

Inter- and Intra-Patient Repeatability of Radiomic Features from Multiparametric Whole-Body MRI in Patients with Metastatic Prostate Cancer.

(1) Background: We assessed the test-re-test repeatability of radiomics in metastatic castration-resistant prostate cancer (mCPRC) bone disease on whole-body diffusion-weighted (DWI) and T1-weighted Dixon MRI. (2) Methods: In 10 mCRPC patients, 1.5 T MRI, including DWI and T1-weighted gradient-echo Dixon sequences, was performed twice on the same day. Apparent diffusion coefficient (ADC) and relative fat-fraction-percentage (rFF%) maps were calculated. Per study, up to 10 target bone metastases were manually delineated on DWI and Dixon images. All 106 radiomic features included in the Pyradiomics toolbox were derived for each target volume from the ADC and rFF% maps. To account for inter- and intra-patient measurement repeatability, the log-transformed individual target measurements were fitted to a hierarchical model, represented as a Bayesian network. Repeatability measurements, including the intraclass correlation coefficient (ICC), were derived. Feature ICCs were compared with mean ADC and rFF ICCs. (3) Results: A total of 65 DWI and 47 rFF% targets were analysed. There was no significant bias for any features. Pairwise correlation revealed fifteen ADC and fourteen rFF% feature sub-groups, without specific patterns between feature classes. The median intra-patient ICC was generally higher than the inter-patient ICC. Features that describe extremes in voxel values (minimum, maximum, range, skewness, and kurtosis) showed generally lower ICCs. Several mostly shape-based texture features were identified, which showed high inter- and intra-patient ICCs when compared with the mean ADC or mean rFF%, respectively. (4) Conclusions: Pyradiomics texture features of mCRPC bone metastases varied greatly in inter- and intra-patient repeatability. Several features demonstrated good repeatability, allowing for further exploration as diagnostic parameters in mCRPC bone disease.

Patient satisfaction with ultrasound, whole-body CT and whole-body diffusion-weighted MRI for pre-operative ovarian cancer staging: a multicenter prospective cross-sectional survey

BackgroundIn addition to the diagnostic accuracy of imaging methods, patient-reported satisfaction with imaging methods is important.ObjectiveTo report a secondary outcome of the prospective international multicenter Imaging Study in Advanced ovArian...

3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients with Multiple Myeloma using Whole-body MRI.

Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted MRI data using three-dimensional (3D) convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable AI, to predict prognosis and explore the factors involved in prediction. We retrospectively analyzed the MRI data of a total of 142 patients with MM obtained from two medical centers. We defined the occurrence of progressive disease after MRI evaluation within 12 months as a poor prognosis and constructed a 3D CNN-based deep learning model to predict prognosis. Images from 111 cases were used as the training and internal validation data; images from 31 cases were used as the external validation data. Internal validation of the AI model with stratified 5-fold cross-validation resulted in a significant difference in progression-free survival (PFS) between good and poor prognostic cases (2-year PFS, 91.2% versus [vs.] 61.1%, P = 0.0002). The AI model clearly stratified good and poor prognostic cases in the external validation cohort (2-year PFS, 92.9% vs. 55.6%, P = 0.004), with an area under the receiver operating characteristic curve of 0.804. According to Grad-CAM, the MRI signals of the spleen and bones of the vertebrae and pelvis contributed to prognosis prediction. This study is the first to show that image analysis of whole-body MRI using a 3D CNN without any other clinical data is effective in predicting the prognosis of patients with MM.

Normal bone marrow signal characteristics in whole-body diffusion-weighted images of amateur marathon runners.

Marathon training can reverse bone marrow conversion; however, little is known about the normal bone marrow whole-body diffusion-weighted imaging (WB-DWI) signal characteristics of amateur marathon runners. If marathon training can cause diffuse hyperintensity of bone marrow on WB-DWI is essential for correctly interpreting the diffusion-weighted (DW) images. This study sought to evaluate the WB-DWI signal characteristics of normal bone marrow in amateur marathon runners. In this prospective cross-sectional study, 30 amateur marathon runners who had trained for over 3 years for regular or half-marathon races and had a running frequency of more than 20 days a month at a distance of more than 100 km per month from the Chengde Marathon Outdoor Sports Association in Hebei, China, and 30 age- and gender-matched, healthy volunteers (the control group) who had no long-term heavy-load sports history were recruited between April 2021 to September 2021. All the subjects underwent WB-DWI (b-value: 0, 800 s/mm2) and lumbar vertebral transverse relaxation time (T2) mapping. The bone marrow WB-DWI signal characteristics were analyzed visually and statistically by chi-square (χ2) tests. The apparent diffusion coefficient (ADC), DWI signal intensity, and T2 values of the bone marrow were quantitatively and statistically analyzed by the independent sample t-test and Mann-Whitney U test. No subjects were excluded from the study. The bone marrow of 30 of the 60 subjects (aged 30-50 years) showed diffuse hyperintensity in the DW images. However, in all 60 subjects, the humeral heads, femoral heads, and great trochanters had low signals. The frequency of diffuse bone marrow DWI hyperintensity was significantly higher in the male amateur marathon runners (50%) than the male controls (5%, P=0.003), but no such significant difference was found between the female amateur marathon runners (100%) and female controls (90%, P>0.99). The DW signal intensity ratios of bone marrow to muscle (SIRBM-muscle) were significantly higher in the male amateur marathon runners than the male controls in the thoracic vertebrae (4.68 vs. 3.57, P=0.021), lumbar vertebrae (4.49 vs. 3.01, P<0.001), sacrum (3.67 vs. 2.62, P=0.002), and hip (3.45 vs. 2.50, P=0.002), but were only significantly higher in the female amateur marathon runners than the female controls in the thoracic vertebrae (7.69 vs. 5.87, P=0.029) and hip (4.76 vs. 3.92, P=0.004). The mean T2 values of the lumbar vertebrae were significantly higher in the male amateur marathon runners than the male controls (116.76 vs. 97.63 ms, P=0.001), but no such significant difference was observed between the female amateur marathon runners and the corresponding controls (118.58 vs. 124.10 ms, P=0.386). Marathon training resulted in diffuse hyperintensity in the bone marrow based on WB-DWI in 50% of the male amateur marathon runners aged 30-50 years. Thus, when WB-DWI is used for bone marrow disease screening, marathon training history should be considered to avoid false-positive diagnoses.

Investigation of distress during diffusion-weighted whole-body magnetic resonance imaging among women with breast cancer and the effectiveness of a new technology in alleviating patient's anxiety by approaching the human senses

IntroductionBreast cancer is a common malignant tumor among women, and the effectiveness of diagnosing its metastasis and recurrence has been demonstrated using diffusion-weighted whole-body imaging with background body signal suppression (DWIBS). However, DWIBS causes distress to patients due to the unique circumstances of magnetic resonance imaging (MRI). This study aimed to investigate the various distress factors caused by DWIBS among women with breast cancer and assess the effectiveness of a new MRI system designed with an environment incorporating relaxing technology. MethodsFrom May to September 2022, we conducted a questionnaire survey regarding DWIBS-related distress among women with breast cancer. The questionnaire was administered to participants who underwent DWIBS on a conventional MRI system (19 women) and on a new system (20 women) equipped with relaxing technology equipped features, including projection images, illumination, and sound. Participants rated the degree of various stress factors on a face-scale rating scale (0–10). The scores of both systems were compared using the Mann–Whitney U test. ResultsIn the conventional system, women experienced distress due to MRI-specific situations, such as immobility in a confined space, noise, feeling trapped, and concerns about not moving. These results did not show a specific tendency among women with breast cancer undergoing DWIBS. For almost all distress parameters, the new system had significantly lower distress scores than the conventional system (p > 0.05). ConclusionsA comfortable environment using new and relaxing technology is effective in alleviating patient's anxiety by approaching the human senses. Implications for practiceReducing distress caused by DWIBS among women with breast cancer could provide a comfortable examination environment, potentially assisting them during longer treatment periods.

Deep Learning for Delineation of the Spinal Canal in Whole-Body Diffusion-Weighted Imaging: Normalising Inter- and Intra-Patient Intensity Signal in Multi-Centre Datasets.

Whole-Body Diffusion-Weighted Imaging (WBDWI) is an established technique for staging and evaluating treatment response in patients with multiple myeloma (MM) and advanced prostate cancer (APC). However, WBDWI scans show inter- and intra-patient intensity signal variability. This variability poses challenges in accurately quantifying bone disease, tracking changes over follow-up scans, and developing automated tools for bone lesion delineation. Here, we propose a novel automated pipeline for inter-station, inter-scan image signal standardisation on WBDWI that utilizes robust segmentation of the spinal canal through deep learning. We trained and validated a supervised 2D U-Net model to automatically delineate the spinal canal (both the spinal cord and surrounding cerebrospinal fluid, CSF) in an initial cohort of 40 patients who underwent WBDWI for treatment response evaluation (80 scans in total). Expert-validated contours were used as the target standard. The algorithm was further semi-quantitatively validated on four additional datasets (three internal, one external, 207 scans total) by comparing the distributions of average apparent diffusion coefficient (ADC) and volume of the spinal cord derived from a two-component Gaussian mixture model of segmented regions. Our pipeline subsequently standardises WBDWI signal intensity through two stages: (i) normalisation of signal between imaging stations within each patient through histogram equalisation of slices acquired on either side of the station gap, and (ii) inter-scan normalisation through histogram equalisation of the signal derived within segmented spinal canal regions. This approach was semi-quantitatively validated in all scans available to the study (N = 287). The test dice score, precision, and recall of the spinal canal segmentation model were all above 0.87 when compared to manual delineation. The average ADC for the spinal cord (1.7 × 10-3 mm2/s) showed no significant difference from the manual contours. Furthermore, no significant differences were found between the average ADC values of the spinal cord across the additional four datasets. The signal-normalised, high-b-value images were visualised using a fixed contrast window level and demonstrated qualitatively better signal homogeneity across scans than scans that were not signal-normalised. Our proposed intensity signal WBDWI normalisation pipeline successfully harmonises intensity values across multi-centre cohorts. The computational time required is less than 10 s, preserving contrast-to-noise and signal-to-noise ratios in axial diffusion-weighted images. Importantly, no changes to the clinical MRI protocol are expected, and there is no need for additional reference MRI data or follow-up scans.

Sequential Imaging with Diffusion-Weighted Whole-Body MRI (DW-MRI) and PET-CT Identifies Patients at High Risk of Relapse in Multiple Myeloma

Introduction: Although the vast majority of patients with newly diagnosed multiple myeloma (NDMM) achieve deep responses during first-line therapy, most of them face relapse over time. Focal lesions, which are seen in up to 80% of NDMM, play a crucial role in MM evolution and can act as reservoirs for relapse disease. As a consequence, the combination of imaging- and minimal residual disease (MRD) negativity has been defined as a new response category. However, the dynamics and location of focal lesions during the treatment course remains poorly characterized and the answer to what imaging modality should be used to visualize focal residual disease remains elusive. In this study, we employed two techniques, PET-CT and DW-MRI, at multiple pre-defined time points to longitudinally track resistant lesions and investigate the combined prognostic value of these imaging modalities with other prognostic markers. Methods: We included 170 NDMM patients who were diagnosed between the years of 2010-2015 to ensure sufficient median follow-up time, which was 10 years. Median age of the study cohort was 60 years (range: 34-76), 104 were male (61%), and 31 patients (18%) had high-risk according to gene-expression profiles. All patients underwent PET-CT and DW-MRI evaluation at three pre-defined timepoints: baseline, post autologous stem-cell transplantation (ASCT) and at relapse. Minimal residual disease testing (MRD) by 8 color flow cytometry at a sensitivity level of 10 -5 post ASCT was available for 70 patients. Results: At baseline, 144/170 patients (85%) presented with focal lesions. Both imaging modalities, PET-CT and DW-MRI, showed positive results in 116 patients (68%). However, 21 patients (12%) had focal lesions detectable only by DW-MRI, while 7 patients (4%) showed focal lesions solely in PET-CT. After ASCT, only 12 patients had PET-CT positive lesions, whereas DW-MRI detected focal lesions in 53 patients, indicating a much higher detection rate with DW-MRI. Overall, 55 out of 170 patients (32%) showed residual lesions at this time point. The 26 patients w/o focal lesions in both PET-CT and DW-MRI at baseline remained negative post ASCT. Except for one patient, focal lesions after ASCT were persistent from initial diagnosis. Of note, two-thirds of the patients had residual focal lesions in the humeri and/or femora, which is surprising given that myeloma is considered a disease of the axial skeleton. Next, we correlated the presence of residual lesions with baseline patient characteristics, including age, gender, stage, and cytogenetic risk factors. Compared to patients w/o residual lesions, PET-positive patients showed an enrichment of rISS stage III (7 vs 50%, p&amp;lt;0.001) and deletion 17p (10 vs 33%, p=0.04). In contrast, patients who were DW-MRI positive only showed no significant association with any of the investigated variables. Both PET- and DW-MRI positive lesions post ASCT were associated with poor PFS (median 1.5 and 2.4 years, respectively vs. 9.4 years in imaging-negative patients, p&amp;lt;0.001) and OS (median 3.7 and 5.7 years, respectively vs. 11.3 years, p&amp;lt;0.001). Importantly, in a multivariate model the adverse prognostic effect of residual lesions was independent of baseline risk factors. To increase the power of the following combined imaging/MRD analysis, we defined an “Imaging+” group, which included the patients with PET+ and/or DW-MRI+ focal lesions. Among the 20 patients who achieved MRD-negative and imaging-negative status, an excellent PFS was observed, with only three events occurring in an 8-year follow-up. Residual lesions despite MRD negativity were only seen in two patients, and one of them progressed after 1.5 years. Dismal PFS was seen for double-positive patients (median 1.4 years), significantly worse compared to patients with MRD positivity only (8.9 years). Conclusion: Taken together, DW-MRI captures more patients with prognostically relevant residual focal lesions compared to PET-CT and should therefore be considered as a preferable imaging modality post ASCT. The high number of residual lesions in the extremities suggests a role of humeri and femora as reservoirs for treatment-resistant cells, deserving further investigation. For patients with MRD and imaging double positivity post ASCT, prognosis is dismal and alternate therapeutic approaches should be considered.

A Case of Postthoracic Endovascular Aortic Repair Stent-Graft Infection Caused by Campylobacter insulaenigrae.

An 81-year-old Japanese man who had distal aortic arch dilatation at age 77 had thoracic endovascular aortic surgery. The patient developed a fever and was taken to the hospital. Reduced diffusion in the descending aortic wall along the stent graft was discovered using whole-body diffusion-weighted imaging with background body signal suppression, and stent-graft infection was identified. The 16S ribosomal RNA gene analysis and blood culture results identified Campylobacter insulaenigrae as the etiological bacterial species. The patient was released from the hospital after 6 weeks of antibiotic treatment since the swelling and inflammatory response had decreased.

A whole-body diffusion MRI normal atlas: development, evaluation and initial use

BackgroundStatistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task.MethodsMulti-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture.ResultsSex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4–48% at 1.5T, 6–70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision.ConclusionsWhole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.

The value of baseline 18F-sodium fluoride and 18F-choline PET activity for identifying responders to radium-223 treatment in castration-resistant prostate cancer bone metastases

ObjectivesTo investigate whether baseline 18F-sodium fluoride (NaF) and 18F-choline PET activity is associated with metastatic castration-resistant prostate cancer (mCRPC) global and individual bone metastases’ DWI MR imaging response to radium-223 treatment.MethodsThirty-six bone-only mCRPC patients were prospectively recruited from three centers. Whole-body (WB)-MRI with DWI and 18F-NaF and 18F-choline PET/CT were performed at therapy baseline and 8-week intervals. In each patient, bone disease median global (g)ADC change between baseline and follow-up was calculated. Additionally, up to five bone target lesions per patient were delineated and individual median ADC change recorded. An ADC increase > 30% defined response per-patient and per-lesion. For the same targets, baseline 18F-NaF and 18F-choline PET SUVmax were recorded. Mean SUVmax across patient targets was correlated with gADC change and lesion SUVmax with per-lesion ADC change.ResultsA total of 133 lesions in 36 patients (14 responders) were analyzed. 18F-NaF PET per-patient mean SUVmax was significantly higher in responders (median = 56.0 versus 38.7 in non-responders; p = 0.008), with positive correlation between SUVmax and gADC increase (rho = 0.42; p = 0.015). A 48.7 SUVmax threshold identified responders with 77% sensitivity and 75% specificity. Baseline 18F-NaF PET per-lesion SUVmax was higher in responding metastases (median = 51.6 versus 31.8 in non-responding metastases; p = 0.001), with positive correlation between baseline lesion SUVmax and ADC increase (rho = 0.39; p < 0.001). A 36.8 SUVmax threshold yielded 72% sensitivity and 63% specificity. No significant association was found between baseline 18F-choline PET SUVmax and ADC response on a per-patient (p = 0.164) or per-lesion basis (p = 0.921).Conclusion18F-NaF PET baseline SUVmax of target mCRPC bone disease showed significant association with response to radium-223 defined by ADC change.Clinical relevance statement18F-sodium fluoride PET/CT baseline maximum SUV of castration-resistant prostate cancer bone metastases could be used as a predictive biomarker for response to radium-223 therapy.Key Points• 18F-sodium fluoride PET baseline SUVmax of castration-resistant prostate cancer bone metastases showed significant association with response to radium-223.• Baseline 18F-sodium fluoride PET can improve patient selection for radium-223 therapy.• Change in whole-body DWI parameters can be used for response correlation with baseline 18F-sodium fluoride PET SUVmax in castration-resistant prostate cancer bone metastases.

Predicting resectable disease in relapsed epithelial ovarian cancer by using whole-body diffusion-weighted MRI

ObjectiveTo determine the diagnostic value of whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) to predict resectable disease at the time of secondary cytoreductive surgery for relapsed epithelial ovarian cancer with a...

Diffusion-weighted whole-body magnetic resonance imaging with background body signal suppression was useful in a patient with isolated myocardial abscess confined to the right atrial wall: a case report

BackgroundMyocardial abscess is often associated with infective endocarditis (IE), and isolated myocardial abscess without IE is rare. Echocardiography and computed tomography (CT) are often used to diagnose myocardial abscess; however, to the best of our knowledge, diffusion-weighted whole-body magnetic resonance imaging with background body signal suppression (DWIBS) has not been used. Here, we present a case of myocardial abscess without IE that was diagnosed using DWIBS.Case presentation: A 72-year-old Japanese man with a history of hypertension, dyslipidemia, and retinitis pigmentosa presented to our hospital with malaise and a fever lasting 10 days. Blood test results showed elevated inflammatory marker levels (white blood cell count 18,700/µL and C-reactive protein level 23.0 mg/dL). Infection was suspected; however, the source of the infection could not be identified. DWIBS, which was performed on day 7 of admission to determine the source of infection, showed a high signal surrounding the right wall, suggesting inflammation. Contrast-enhanced CT performed on day 1 of hospitalization revealed a low-density area in the same region; however, the pathological implications of this finding could not be determined. Based on DWIBS findings, we concluded that the condition presented as a myocardial abscess that was confined specifically to the right atrial wall. Three sets of blood cultures revealed negative findings, and echocardiography showed no vegetation or valve regurgitation. Therefore, the patient was diagnosed with an isolated myocardial abscess uncomplicated with IE. An electrocardiogram on admission showed no P waves, and the patient had a junctional rhythm. However, on day 20 of hospitalization, he developed a complete atrioventricular block. After complete myocardial abscess healing following antibiotic treatment was confirmed, the patient underwent pacemaker implantation. Ten months after surgery, the patient had no signs of infection recurrence.ConclusionsBased on history and physical examination alone, diagnosis of an isolated myocardial abscess can be challenging. In addition to CT and echocardiography, DWIBS might be helpful for the diagnosis of myocardial abscesses.

Diagnostic value of whole -body diffusion weighted imaging added to bone scan in early diagnosis of bone metastases in breast cancer patients

BackgroundMetastases to the bones are a frequent location of metastasis in advanced breast cancer and are responsible for substantial morbidity and healthcare expenses. Imaging has been crucial in directing patient therapy for decades, contributing to the staging and response evaluation of the skeleton. This research aimed to assess the diagnostic value of whole-body magnetic resonance imaging with diffusion-weighted imaging added to radionuclide bone scans for early diagnosis of bone metastases in breast cancer patients.ResultsThe study was a prospective observational cohort study performed on 20 patients with breast cancer and suspected bone metastases. The patients were evaluated first by obtaining a detailed personal history. Laboratory tests, including CBC, liver, and kidney function tests were assessed. All patients were examined by diffusion-weighted whole-body MRI (DWIBS; diffusion-weighted imaging with background body signal suppression) images and bone scintigraphy after intravenous injection of 20 mci of technetium-99m (99mTc) methylene diphosphonate using a dual head gamma camera. The total number of lesions detected by bone scan was 74, and 75 lesions were seen by DWIBS. Twenty-four lesions were missed by bone scan and detected by DWIBS. Fourteen lesions were detected by bone scan and found free by DWIBS examination in the spine and pelvic bones.ConclusionsWhole body DWIBS seems to be a promising method of imaging in detecting bone metastases from breast cancer that could be used complementary to the traditional bone scan for more accurate diagnosis and staging of the tumor, helping to determine the most appropriate protocol of management.

QUANTITATIVE WHOLE‐BODY MRI FOR PREDICTING TREATMENT OUTCOME IN PEDIATRIC PATIENTS WITH AGGRESSIVE NON‐HODGKIN LYMPHOMA UNDERGOING CHIMERIC ANTIGEN RECEPTOR T CELL THERAPY

Introduction: Chimeric antigen receptor (CAR) T cell therapy has shown great promise in treating pediatric patients with aggressive non-Hodgkin lymphoma (NHL), but its effectiveness can vary greatly among individuals. Accurate prediction of treatment response can aid in patient selection and treatment planning. Quantitative whole-body diffusion-weighted MRI (WB-DW MRI) has emerged as a potential tool for predicting treatment response in various types of cancer, but its predictive value for CAR-T cell therapy in pediatric patients with aggressive NHL has not been fully explored. This prospective multicenter study aimed to investigate the predictive value of quantitative whole-body diffusion-weighted MRI in this patient population. Methods: Thirty-six pediatric patients with aggressive NHL who underwent CAR T cell therapy were enrolled from three participating centers. All patients underwent WB-DW MRI before and after CAR T cell therapy. T2 values, apparent diffusion coefficient (ADC) values, and the ADC change between baseline and within 15 days after infusion were calculated. Patients were categorized into good outcome (complete remission) and poor outcome (progressive or recurrent disease) groups based on their treatment response. Receiver operating characteristic (ROC) curve analysis was used to evaluate the correlation between ADC values and treatment outcome. Results: The mean age of patients was 11 years, with 31 males. The mean change in ADC value between baseline and within 15 days after infusion was significantly higher in the good outcome group compared to the poor outcome group (p < 0.01). The change in ADC value was an independent predictor of treatment outcome on logistic regression analysis after adjusting for age, gender, and disease stage (odds ratio: 1.017; 95% confidence interval: 1.003–1.030; p < 0.01). The area under the ROC curve for ADC change was 0.794 (95% confidence interval: 0.649–0.939). Keywords: cellular therapies, immunotherapy, Imaging and Early Detection - Other No conflicts of interests pertinent to the abstract.

Radiomics model of diffusion-weighted whole-body imaging with background signal suppression (DWIBS) for predicting axillary lymph node status in breast cancer.

In breast cancer diagnosis and treatment, non-invasive prediction of axillary lymph node (ALN) metastasis can help avoid complications related to sentinel lymph node biopsy. This study aims to develop and evaluate machine learning models using radiomics features extracted from diffusion-weighted whole-body imaging with background signal suppression (DWIBS) examination for predicting the ALN status. A total of 100 patients with histologically proven, invasive, clinically N0 breast cancer who underwent DWIBS examination consisting of short tau inversion recovery (STIR) and DWIBS sequences before surgery were enrolled. Radiomic features were calculated using segmented primary lesions in DWIBS and STIR sequences and were divided into training (n = 75) and test (n = 25) datasets based on the examination date. Using the training dataset, optimal feature selection was performed using the least absolute shrinkage and selection operator algorithm, and the logistic regression model and support vector machine (SVM) classifier model were constructed with DWIBS, STIR, or a combination of DWIBS and STIR sequences to predict ALN status. Receiver operating characteristic curves were used to assess the prediction performance of radiomics models. For the test dataset, the logistic regression model using DWIBS, STIR, and a combination of both sequences yielded an area under the curve (AUC) of 0.765 (95% confidence interval: 0.548-0.982), 0.801 (0.597-1.000), and 0.779 (0.567-0.992), respectively, whereas the SVM classifier model using DWIBS, STIR, and a combination of both sequences yielded an AUC of 0.765 (0.548-0.982), 0.757 (0.538-0.977), and 0.779 (0.567-0.992), respectively. Use of machine learning models incorporating with the quantitative radiomic features derived from the DWIBS and STIR sequences can potentially predict ALN status.

Patient-Centered Care in the Management of Cancer During Pregnancy.

The management of cancer during pregnancy requires a patient-centered, multidisciplinary approach to balance maternal and fetal well-being given the rarity of this clinical scenario and lack of substantial data. Involvement of oncology and nononcology medical specialists and ethical, legal, and psychosocial supports, as needed, is instrumental in navigating the complexities of care for this patient population. Critical periods of fetal development and physiological changes in pregnancy must be considered when planning diagnostic and therapeutic approaches during pregnancy. The complexity of symptom recognition and interventional approaches contributes to diagnostic delays of cancers during pregnancy. Ultrasound and whole-body diffusion-weighted magnetic resonance imaging are safe throughout pregnancy. Surgery can be safely performed throughout pregnancy, with the early second trimester preferred for intra-abdominal surgery. Chemotherapy can be safely administered after 12-14 weeks of gestation until 1-3 weeks before the anticipated delivery. Most targeted and immunotherapeutic agents are contraindicated during pregnancy because of limited data. Pelvic radiation during pregnancy is absolutely contraindicated, while if radiation to the upper body is needed, administration should only be considered early in pregnancy. To ensure that the total cumulative fetal exposure to ionizing radiation does not exceed 100 mGy, early inclusion of the radiology team in the care plan is required. Closer prenatal monitoring is recommended for maternal and fetal treatment-related toxicities. Delivery before 37 weeks of gestation should be avoided if possible, and vaginal delivery is preferred unless obstetrically indicated or specific clinical scenarios. Postpartum, breastfeeding should be discussed, and the neonate should receive blood work to assess for acute toxicities with follow-up arranged for long-term monitoring.

Smoking History and Increasing Pack Years Predict Brain Volume Loss in 8831 Healthy Participants (P6-12.003)

<h3>Objective:</h3> To determine the relationship between smoking history and pack years on brain volume loss. <h3>Background:</h3> Smoking is a risk factor for both Alzheimer and vascular dementia. Understanding this risk requires an investigation of relationship between smoking and brain volume loss on MRI, a biomarker for neurodegeneration. <h3>Design/Methods:</h3> In total, 8831 healthy participants from 4 sites were scanned on 1.5T MR with a short whole-body MR imaging protocol. Sequences included whole body coronal T1, STIR from vertex to feet, whole-body axial DWI from vertex to proximal-thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were T1 MPRAGE and 2D FLAIR. Deep learning volumetric software, FastSurfer, trained over 134 participants aged 27–66, segmented 96 brain volumes. Smokers versus non-smokers were compared by gray and white matter volumes normalized to total intracranial volume using a two tailed t-test. Partial correlation analysis was done between pack years and brain volumes, controlling of age, sex, and total intracranial volume. The Benjamini Hochberg False Discovery Rate of 5% accounted for multiple comparisons. <h3>Results:</h3> This cohort averaged 52.90 ± 13.06 years, between 23 to 84, with 52.5% men and 47.5% women. Overall, 2860 individuals (32.3%) self-reported a history of smoking. Participants who smoked were older than non-smokers (p = .024). Smokers had lower normalized gray and white matter volumes compared to non-smokers (t = 8.95, p = 4.39e-19). Adjusting for co-variates and multiple comparisons, smoking predicted brain volume loss in: gray and white matter volumes (Partial R =−.08, p = 6.84e-12), hippocampus (Partial R = −.06, p = 3.16e-7), frontal cortex (Partial R = −.08, p = 7.91e-13), temporal lobes (Partial R = −.07, 2.12e-9), left posterior cingulate gyrus (Partial R = −.06, p = 1.99e-8). <h3>Conclusions:</h3> Both smoking history and pack years predict both lower whole brain and regional volumes. <b>Disclosure:</b> Dr. Meysami has nothing to disclose. Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Brainreader ApS. Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Apollo Health . Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Neurevolution Medicine. Mr. Hashemi has received personal compensation for serving as an employee of Prenuvo. Mr. Garg has received personal compensation for serving as an employee of Prenuvo. Dr. Nguyen has nothing to disclose. Dr. Chodakiewitz has received personal compensation for serving as an employee of Prenuvo . Dr. Chodakiewitz has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Aidoc. Ms. Akbari has nothing to disclose. Mr. Gouda has received personal compensation for serving as an employee of Prenuvo. Dr. Attariwala has received personal compensation in the range of $100,000-$499,999 for serving as a Radiologist reading cases and helping build in house software tools with Prenuvo.

Suppression of background body signals in whole-body diffusion-weighted imaging for detection of bony metastases: a pilot study

BackgroundWhole-body diffusion-weighted magnetic resonance is being developed as a tool for assessing tumor spread. Patients with known primary tumors require meticulous evaluation to assess metastasis for better staging; we attempted to detect bony metastasis without radiation exposure. Our study's goal was to use whole-body diffusion-weighted imaging with background body signal suppression (WB-DWBIS) to evaluate bony metastasis in confirmed patients who have primary tumors.ResultsOur study included 90 patients with known primary cancer, 10 patients were excluded as they had no bony metastasis, from 80 patients: 36 (45.0%) having one site of metastasis, 36 (45%) having two sites of metastasis, and 8 (10.0%) having three sites of metastasis. 56 (70.0%) of the metastasis sites were bony metastasis, and 76 were mixed both bony and non-bony, including 32(40.0%) lung, 16 (20.0%) liver, and 28 (35%) lymph nodes. Sensitivity of bone scanning in detecting metastasis was as follows: 95.1% sensitivity and 92.0% accuracy, while that of whole-body diffusion-weighted image with background signals suppression was 94.8% sensitivity and 91.7% accuracy, WB-DWBIS inter-observer agreement in the detection of bony metastatic deposits in cancer patients was good (0.7 45, agreement = 93.2%).ConclusionsUsing WB-DWBIS images, bone lesion identification and characterization (site and number) were improved, producing outcomes similar to bone scanning without the use of ionizing radiation.

Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review.

Maximal-effort upfront or interval debulking surgery is the recommended approach for advanced-stage ovarian cancer. The role of diagnostic imaging is to provide a systematic and structured report on tumour dissemination with emphasis on key sites for resectability. Imaging methods, such as pelvic and abdominal ultrasound, contrast-enhanced computed tomography, whole-body diffusion-weighted magnetic resonance imaging and positron emission tomography, yield high diagnostic performance for diagnosing bulky disease, but they are less accurate for depicting small-volume carcinomatosis, which may lead to unnecessary explorative laparotomies. Diagnostic laparoscopy, on the other hand, may directly visualize intraperitoneal involvement but has limitations in detecting tumours beyond the gastrosplenic ligament, in the lesser sac, mesenteric root or in the retroperitoneum. Laparoscopy has its place in combination with imaging in cases where ima-ging results regarding resectability are unclear. Different imaging models predicting tumour resectability have been developed as an adjunctional objective tool. Incorporating results from tumour quantitative analyses (e.g., radiomics), preoperative biopsies and biomarkers into predictive models may allow for more precise selection of patients eligible for extensive surgery. This review will discuss the ability of imaging and laparoscopy to predict non-resectable disease in patients with advanced ovarian cancer.