Association of Quality and Quantity of Bone Metastases and Computed Tomography Volumetric Bone Mineral Density With Prevalence of Vertebral Fractures in Breast Cancer Patients

CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71-0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72-0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71-0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66-0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals

Purpose

The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBMD, iodine blood pool, patient age, and sex.

Method

Retrospective analysis of oncological patients without evidence of metastatic disease. DECT examinations were performed on a spectral detector CT scanner in portal venous contrast phase. The thoracic and lumbar spine were segmented by a pre-trained neural network, obtaining volumetric iodine concentration data [mg/ml]. vBMD was assessed using a phantomless, CE-certified software [mg/cm3]. The iodine blood pool was estimated by ROI-based measurements in the great abdominal vessels. A multivariate regression model was fit with the dependent variable "median bone marrow iodine uptake". Standardized regression coefficients (β) were calculated to assess the impact of each covariate.

Results

678 consecutive DECT exams of 189 individuals (93 female, age 61.4 ± 16.0 years) were evaluated. AI-based segmentation provided volumetric data of 97.9% of the included vertebrae (n=11,286). The 95^th percentile of bone marrow iodine uptake, as a surrogate for the upper margin of the physiological distribution, ranged between 4.7-6.4 mg/ml. vBMD (p <0.001, mean β=0.50) and portal vein iodine blood pool (p <0.001, mean β=0.43) mediated the strongest impact. Based thereon, adjusted reference values were calculated.

Conclusion

The bone marrow iodine uptake demonstrates a distinct profile depending on vBMD, iodine blood pool, patient age, and sex. This study is the first to provide the adjusted reference values.

Feasibility of artificial intelligence–supported assessment of bone marrow infiltration using dual-energy computed tomography in patients with evidence of monoclonal protein — a retrospective observational study

Objectives

To demonstrate the feasibility of an automated, non-invasive approach to estimate bone marrow (BM) infiltration of multiple myeloma (MM) by dual-energy computed tomography (DECT) after virtual non-calcium (VNCa) post-processing.

Methods

Individuals with MM and monoclonal gammopathy of unknown significance (MGUS) with concurrent DECT and BM biopsy between May 2018 and July 2020 were included in this retrospective observational study. Two pathologists and three radiologists reported BM infiltration and presence of osteolytic bone lesions, respectively. Bone mineral density (BMD) was quantified CT-based by a CE-certified software. Automated spine segmentation was implemented by a pre-trained convolutional neural network. The non-fatty portion of BM was defined as voxels > 0 HU in VNCa. For statistical assessment, multivariate regression and receiver operating characteristic (ROC) were conducted.

Results

Thirty-five patients (mean age 65 ± 12 years; 18 female) were evaluated. The non-fatty portion of BM significantly predicted BM infiltration after adjusting for the covariable BMD (p = 0.007, r = 0.46). A non-fatty portion of BM > 0.93% could anticipate osteolytic lesions and the clinical diagnosis of MM with an area under the ROC curve of 0.70 [0.49–0.90] and 0.71 [0.54–0.89], respectively. Our approach identified MM-patients without osteolytic lesions on conventional CT with a sensitivity and specificity of 0.63 and 0.71, respectively.

Conclusions

Automated, AI-supported attenuation assessment of the spine in DECT VNCa is feasible to predict BM infiltration in MM. Further, the proposed method might allow for pre-selecting patients with higher pre-test probability of osteolytic bone lesions and support the clinical diagnosis of MM without pathognomonic lesions on conventional CT.

Key Points

• The retrospective study provides an automated approach for quantification of the non-fatty portion of bone marrow, based on AI-supported spine segmentation and virtual non-calcium dual-energy CT data.

• An increasing non-fatty portion of bone marrow is associated with a higher infiltration determined by invasive biopsy after adjusting for bone mineral density as a control variable (p = 0.007, r = 0.46).

• The non-fatty portion of bone marrow might support the clinical diagnosis of multiple myeloma when conventional CT images are negative (sensitivity 0.63, specificity 0.71).

Early extrapulmonary prognostic features in chest computed tomography in COVID-19 pneumonia: Bone mineral density is a relevant predictor for the clinical outcome - A multicenter feasibility study

BACKGROUND

Besides throat-nose swab polymerase chain reaction (PCR), unenhanced chest computed tomography (CT) is a recommended diagnostic tool for early detection and quantification of pulmonary changes in COVID-19 pneumonia caused by the novel corona virus. Demographic factors, especially age and comorbidities, are major determinants of the outcome in COVID-19 infection. This study examines the extra pulmonary parameter of bone mineral density (BMD) from an initial chest computed tomography as an associated variable of pre-existing comorbidities like chronic lung disease or demographic factors to determine the later patient's outcome, in particular whether treatment on an intensive care unit (ICU) was necessary in infected patients.

METHODS

We analyzed 58 PCR-confirmed COVID-19 infections that received an unenhanced CT at admission at one of the included centers. In addition to the extent of pulmonary involvement, we performed a phantomless assessment of bone mineral density of thoracic vertebra 9-12.

RESULTS

In a univariate regression analysis BMD was found to be a significant predictor of the necessity for intensive care unit treatment of COVID-19 patients. In the subgroup requiring intensive care treatment within the follow-up period a significantly lower BMD was found. In a multivariate logistic regression model considering gender, age and CT measurements of bone mineral density, BMD was eliminated from the regression analysis as a significant predictor.

CONCLUSION

Phantomless assessed BMD provides prognostic information on the necessity for ICU treatment in course of COVID-19 pneumonia. We recommend using the measurement of BMD in an initial CT image to facilitate a potentially better prediction of severe patient outcomes within the 22 days after an initial CT scan. Consequently, in the present sample, additional bone density analysis did not result in a prognostic advantage over simply considering age. Significantly larger patient cohorts with a more homogenous patient age should be performed in the future to illustrate potential effects.

CLINICAL RELEVANCE

While clinical capacities such as ICU beds and ventilators are more crucial than ever to help manage the current global corona pandemic, this work introduces an approach that can be used in a cost-effective way to help determine the amount of these rare clinical resources required in the near future.

Phantomless assessment of volumetric bone mineral density using virtual non-contrast images from spectral detector computed tomography

OBJECTIVE

To evaluate phantomless assessment of volumetric bone mineral density (vBMD) based on virtual non-contrast images of arterial (VNC_a) and venous phase (VNC_v) derived from spectral detector CT in comparison to true non-contrast (TNC) images and adjusted venous phase conventional images (CI_V(adjusted)).

METHODS

104 consecutive patients who underwent triphasic spectral detector CT between January 2018 and April 2019 were retrospectively included. TNC, VNC_a, VNC_v and venous phase images (CI_V) were reconstructed. vBMD was obtained by two radiologists using an FDA/CE-cleared software. Average vBMD of the first three lumbar vertebrae was determined in each reconstruction; vBMD of CI_V was adjusted for contrast enhancement as suggested earlier.

RESULTS

vBMD values obtained from CI_V(adjusted) are comparable to vBMD values derived from TNC images (91.79 ± 36.52 vs 90.16 ± 41.71 mg/cm³, p = 1.00); however, vBMD values derived from VNC_a and VNC_v (42.20 ± 22.50 and 41.98 ± 23.3 mg/cm³ respectively) were significantly lower as compared to vBMD values from TNC and CI_V(adjusted) (all p ≤ 0.01).

CONCLUSION

Spectral detector CT-derived virtual non-contrast images systematically underestimate vBMD and therefore should not be used without appropriate adjustments. Adjusted venous phase images provide reliable results and may be utilized for an opportunistic BMD screening in CT examinations.

ADVANCES IN KNOWLEDGE

Adjustments of venous phase images facilitate opportunistic assessment of vBMD, while spectral detector CT-derived VNC images systematically underestimate vBMD.

Accuracy of iodine density thresholds for the separation of vertebral bone metastases from healthy-appearing trabecular bone in spectral detector computed tomography

PURPOSE

To evaluate quantitative iodine density mapping (IDM) with spectral detector computed tomography (SDCT) as a quantitative biomarker for separation of vertebral trabecular bone metastases (BM) from healthy-appearing trabecular bone (HTB).

MATERIALS AND METHODS

IRB-approved retrospective single-center-study of portal venous SDCT datasets acquired between June 2016 and March 2017. Inclusion of 43 consecutive cancer patients with BM and 40 without. Target lesions and non-affected control vertebrae were defined using follow-up imaging, MRI, and/or bone scintigraphy. ID and standard deviation were determined with ROI measures by two readers in (a) bone metastases, (b) HTB of BM patients and controls, and (c) ID of various vessels. Volumetric bone mineral density (vBMD) of the lumbar spine and age were recorded. Multivariate ROC analyses und Wilcoxon test were used to determine thresholds for separation of BM and HTB. p < 0.05 was considered significant.

RESULTS

ID measurements of 40 target lesions and 83 reference measurements of HTB were acquired. Age (p < 0.0001) and vBMD (p < 0.05) affected ID measurements independently in multivariate models. There were significant differences of ID between metastases (n = 43) and HTB ID (n = 124; mean 5.5 ± 0.9 vs. 3.5 ± 0.9; p < 0.0001), however, with considerable overlap. In univariate analysis, increased ID discriminated bone lesions (AUC 0.90) with a maximum combined specificity/sensitivity of 77.5%/90.7% when applying a threshold of 4.5 mg/ml. Multivariate regression models improved significantly when considering vBMD, the noise of ID, and vertebral venous ID (AUC 0.98).

CONCLUSION

IDM of SDCT yielded a statistical separation of vertebral bone lesions and HTB. Adjustment for confounders such as age and lumbar vBMD as well as for vertebral venous ID and lesion heterogeneity improved discrimination of trabecular lesions.

KEY POINTS

• SDCT iodine density mapping provides the possibility for quantitative analysis of iodine uptake in tissue, which allows to differentiate bone lesions from healthy bone marrow. • Age and vBMD have a significant impact on iodine density measurements. • Iodine density measured in SDCT yielded highest sensitivity and specificity for the statistical differentiation of vertebral trabecular metastases and healthy trabecular bone using an iodine density threshold of 4.5 mg/ml (most performant)-5.0 mg/ml (optimized for specificity).

Effects of Contrast Enhancement on In-Body Calibrated Phantomless Bone Mineral Density Measurements in Computed Tomography

We aimed to test the potential of phantomless volumetric bone mineral density (PLvBMD) measurements for the determination of volumetric bone mineral density (vBMD) in routine contrast-enhanced computed tomography (CECT). We evaluated 56 tri-phasic abdominal computed tomography scans, including an unenhanced scan as well as defined CECT scans in the arterial and portalvenous phase. PLvBMD analysis was performed by 4 radiologists using an FDA-approved tool for phantomless evaluation of bone density (IntelliSpace, Philips, The Netherlands). Mean vBMD of the first 3 lumbar vertebrae in each contrast phase was determined and interobserver variance of vBMD independent of contrast phase was analyzed using intraclass correlation, Bland-Altman plots, and Student's t test. CECT scans were associated with a significantly higher PLvBMD compared with unenhanced scans (unenhanced computed tomography: 97.8 mg/cc; arterial CECT: 106.3 mg/cc, portalvenous CECT: 106.3 mg/cc). Overall, there was no significant difference of PLvBMD between data acquisition in arterial and portalvenous phases (increase of 8.6% each, standard deviation ratio 37.7%-38.3%). In Bland-Altman analysis, there was no evidence of a relevant reader-related bias or an increase in standard deviation of PLvBMD measurements in contrast-enhanced scans compared with unenhanced scans. The following conversion formulas for unenhanced PLvBMD were determined: unenhancedPLvBMD=0.89×arterialPLvBMD+3,74mg/cc(r² = 0.94) and unenhancedPLvBMD=0.88×venousPLvBMD+4,56mg/cc(r² = 0.93). Compared with the results of phantom-based quantitative computed tomography measurements reported in the literature, the PLvBMD changes associated with contrast enhancement were relatively moderate with an increase of 8.6% in average. The time-point of the contrast-enhanced PLvBMD measurements after injection of contrast media did not appear to affect the results. With the adjustment formulas provided in this study, the method can improve osteoporosis screening through detection of reduced bone mass of the vertebrae in routinely conducted CECT.

MFAP5 promotes tumor progression and bone metastasis by regulating ERK/MMP signaling pathways in breast cancer

Breast cancer accounts for about 30% of all cancers in women, while approximately 70% breast cancer patients developed bone metastases throughout the course of their disease, highlighting the importance of exploring new therapeutic targets. Microfibrillar-associated protein 5 (MFAP5) is a component of extracellular elastic microfibril which has been confirmed to function in tissue development and cancer progression. But the role of MFAP5 in breast cancer remains unclear. The present study demonstrated that MFAP5 was up-regulated in breast cancers compared with that in normal breast tissues, and further increased in breast cancer bone metastasis. Functionally, MFAP5 overexpression accelerated breast cancer cell proliferation and migration, while an opposite effect was observed when MFAP5 was knocked down. In addition, up-regulation of MFAP5 increased the expression of MMP2 and MMP9 and activated the ERK signaling pathway. Conversely, inhibition of MFAP5 suppressed the expression of MMP2, MMP9, p-FAK, p-Erk1/2 and p-cJun. These findings may provide a better understanding about the mechanism of breast cancer and suggest that MFAP5 may be a potential prognostic biomarker and therapeutic target for breast cancer, especially for bone metastasis of breast cancer.

Magnetic Resonance Spectroscopy-Detected Change in Marrow Adiposity Is Strongly Correlated to Postmenopausal Breast Cancer Risk

PURPOSE

To determine whether marrow fat fraction (FF) is correlated with postmenopausal breast cancer risk and clinicopathological characteristics of breast cancer.

METHODS

Fifty-six patients with newly diagnosed and histologically confirmed postmenopausal breast cancer and 56 healthy controls underwent serologic test and magnetic resonance spectroscopy-based FF measurements. Data were analyzed by logistic multivariate regression models to determine the independent predictors of breast cancer risk and clinicopathological characters of breast cancer.

RESULTS

Patients with breast cancer had higher FF than that of the controls. Marrow FF showed positive association with serum leptin levels (r = 0.607, P < .001) in the cases, but no relationship was found in the controls. In the univariate analysis, both levels of leptin and marrow FF were significantly associated with breast cancer risk and clinicopathological characteristics of breast cancer. In the multivariable model with adjustment for established breast cancer risk factors, serum leptin was a significant predictor of breast cancer risk (OR 1.746; 95% CI, 1.226-2.556) and clinicopathological characteristics of breast cancer including TNM, tumor size, lymph node status, and histological grade (OR 1.461-1.695); but when marrow FF was additionally added to the regression model, marrow FF but not leptin levels was observed to be an independent risk factor for breast cancer risk (OR 1.940; 95% CI, 1.306-2.910) and clinicopathological characteristics of breast cancer (OR 1.770-1.903).

CONCLUSION

Marrow adiposity is a predictor of postmenopausal breast cancer risk and clinicopathological characteristics of breast cancer.