Osteolytica: An automated image analysis software package that rapidly measures cancer-induced osteolytic lesions in in vivo models with greater reproducibility compared to other commonly used methods

Osteolysis: A Literature Review of Basic Science and Potential Computer-Based Image Processing Detection Methods

Osteolysis is one of the most prominent reasons of revision surgeries in total joint arthroplasty. This biological phenomenon is induced by wear particles and corrosion products that stimulate inflammatory biological response of surrounding tissues. The eventual responses of osteolysis are the activation of macrophages leading to bone resorption and prosthesis failure. Various factors are involved in the initiation of osteolysis from biological issues, design, material specifications, and model of the prosthesis to the health condition of the patient. Nevertheless, the factors leading to osteolysis are sometimes preventable. Changes in implant design and polyethylene manufacturing are striving to improve overall wear. Osteolysis is clinically asymptomatic and can be diagnosed and analyzed during follow-up sessions through various imaging modalities and methods, such as serial radiographic, CT scan, MRI, and image processing-based methods, especially with the use of artificial neural network algorithms. Deep learning algorithms with a variety of neural network structures such as CNN, U-Net, and Seg-UNet have proved to be efficient algorithms for medical image processing specifically in the field of orthopedics for the detection and segmentation of tumors. These deep learning algorithms can effectively detect and analyze osteolytic lesions well in advance during follow-up sessions in order to administer proper treatments before reaching a critical point. Osteolysis can be treated surgically or nonsurgically with medications. However, revision surgeries are the only solution for the progressive osteolysis. In this literature review, the underlying causes, mechanisms, and treatments of osteolysis are discussed with the main focus on the possible computer-based methods and algorithms that can be effectively employed for the detection of osteolysis.

Animal Models of Multiple Myeloma Bone Disease

Multiple myeloma (MM) is a clonal B-cell disorder characterized by the proliferation of malignant plasma cells (PCs) in the bone marrow, the presence of monoclonal serum immunoglobulin, and osteolytic lesions. It is the second most common hematological malignancy and considered an incurable disease despite significant treatment improvements. MM bone disease (MMBD) is defined as the presence of one or more osteolytic bone lesions or diffused osteoporosis with compression fracture attributable to the underlying clonal PC disorder. MMBD causes severe morbidity and increases mortality. Cumulative evidence shows that the interaction of MM cells and bone microenvironment plays a significant role in MM progression, suggesting that these interactions may be good targets for therapy. MM animal models have been developed and studied in various aspects of MM tumorigenesis. In particular, MMBD has been studied in various models, and each model has unique features. As the general features of MM animal models have been reviewed elsewhere, the current review will focus on the features of MMBD animal models.

TGFβ Inhibition Stimulates Collagen Maturation to Enhance Bone Repair and Fracture Resistance in a Murine Myeloma Model

Multiple myeloma is a plasma cell malignancy that causes debilitating bone disease and fractures, in which TGFβ plays a central role. Current treatments do not repair existing damage and fractures remain a common occurrence. We developed a novel low tumor phase murine model mimicking the plateau phase in patients as we hypothesized this would be an ideal time to treat with a bone anabolic. Using in vivo μCT we show substantial and rapid bone lesion repair (and prevention) driven by SD-208 (TGFβ receptor I kinase inhibitor) and chemotherapy (bortezomib and lenalidomide) in mice with human U266-GFP-luc myeloma. We discovered that lesion repair occurred via an intramembranous fracture repair-like mechanism and that SD-208 enhanced collagen matrix maturation to significantly improve fracture resistance. Lesion healing was associated with VEGFA expression in woven bone, reduced osteocyte-derived PTHrP, increased osteoblasts, decreased osteoclasts, and lower serum tartrate-resistant acid phosphatase 5b (TRACP-5b). SD-208 also completely prevented bone lesion development in mice with aggressive JJN3 tumors, and was more effective than an anti-TGFβ neutralizing antibody (1D11). We also discovered that SD-208 promoted osteoblastic differentiation (and overcame the TGFβ-induced block in osteoblastogenesis) in myeloma patient bone marrow stromal cells in vitro, comparable to normal donors. The improved bone quality and fracture-resistance with SD-208 provides incentive for clinical translation to improve myeloma patient quality of life by reducing fracture risk and fatality. © 2019 American Society for Bone and Mineral Research.

Loss of the Vitamin D Receptor in Human Breast Cancer Cells Promotes Epithelial to Mesenchymal Cell Transition and Skeletal Colonization

Expression of the vitamin D receptor (VDR) is thought to be associated with neoplastic progression. However, the role of the VDR in breast cancer metastasis to bone and the molecular mechanisms underlying this process are unknown. Employing a rodent model (female Balb/c nu/nu mice) of systemic metastasis, we here demonstrate that knockdown of the VDR strongly increases the metastatic potential of MDA-MB-231 human breast cancer cells to bone, resulting in significantly greater skeletal tumor burden. Ablation of VDR expression promotes cancer cell mobility (migration) and invasiveness, thereby facilitating skeletal colonization. Mechanistically, these changes in tumor cell behavior are attributable to shifts in the expression of proteins involved in cell adhesion, proliferation, and cytoskeletal organization, patterns characteristic for epithelial-to-mesenchymal cell transition (EMT). In keeping with these experimental findings, analyses of human breast cancer specimens corroborated the association between VDR expression, EMT-typical changes in protein expression patterns, and clinical prognosis. Loss of the VDR in human breast cancer cells marks a critical point in oncogenesis by inducing EMT, promoting the dissemination of cancer cells, and facilitating the formation of tumor colonies in bone. © 2019 American Society for Bone and Mineral Research.

ARQ-197, a small-molecule inhibitor of c-Met, reduces tumour burden and prevents myeloma-induced bone disease in vivo

The receptor tyrosine kinase c-Met, its ligand HGF, and components of the downstream signalling pathway, have all been implicated in the pathogenesis of myeloma, both as modulators of plasma cell proliferation and as agents driving osteoclast differentiation and osteoblast inhibition thus, all these contribute substantially to the bone destruction typically caused by myeloma. Patients with elevated levels of HGF have a poor prognosis, therefore, targeting these entities in such patients may be of substantial benefit. We hypothesized that ARQ-197 (Tivantinib), a small molecule c-Met inhibitor, would reduce myeloma cell growth and prevent myeloma-associated bone disease in a murine model. In vitro we assessed the effects of ARQ-197 on myeloma cell proliferation, cytotoxicity and c-Met protein expression in human myeloma cell lines. In vivo we injected NOD/SCID-γ mice with PBS (non-tumour bearing) or JJN3 cells and treated them with either ARQ-197 or vehicle. In vitro exposure of JJN3, U266 or NCI-H929 cells to ARQ-197 resulted in a significant inhibition of cell proliferation and an induction of cell death by necrosis, probably caused by significantly reduced levels of phosphorylated c-Met. In vivo ARQ-197 treatment of JJN3 tumour-bearing mice resulted in a significant reduction in tumour burden, tumour cell proliferation, bone lesion number, trabecular bone loss and prevented significant decreases in the bone formation rate on the cortico-endosteal bone surface compared to the vehicle group. However, no significant differences on bone parameters were observed in non-tumour mice treated with ARQ-197 compared to vehicle, implying that in tumour-bearing mice the effects of ARQ-197 on bone cells was indirect. In summary, these res ults suggest that ARQ-197 could be a promising therapeutic in myeloma patients, leading to both a reduction in tumour burden and an inhibition of myeloma-induced bone disease.

Automated "Bone Subtraction" Image Analysis Software Package for Improved and Faster CT Monitoring of Longitudinal Spine Involvement in Patients with Multiple Myeloma

RATIONALE AND OBJECTIVES

The study aimed to assess the diagnostic benefit of a novel computed tomography (CT) post-processing software generating subtraction maps of longitudinal non-enhanced CT examinations for monitoring the course of myeloma bone disease in the spine.

MATERIALS AND METHODS

The local institutional review board approved the retrospective data evaluation. Included were 82 consecutive myeloma patients (46 male; mean age, 65.08 ± 9.76) who underwent 188 repeated whole-body reduced-dose Multislice Detector Computed Tomography (MDCT) at our institution between December 2013 and January 2016. Lytic bone lesions were categorized as new or enlarging versus stable. Bone subtraction maps were read in combination with corresponding 1-mm source images comparing results to those of standard image reading of 5-mm axial and 2-mm multiplanar reformat reconstructions (MPR) scans and hematologic markers, and classified as either progressive disease (PD) or stable disease (SD or remission). The standard of reference was 1-mm axial CT image reading + hematologic response both confirmed at follow-up. For statistical purposes, we subgrouped the hematologic response categories similarly to those applied for CT imaging (progression vs stable/response).

RESULTS

According to the standard of reference, 16 patients experienced PD and 66 SD at follow-up. Th sensitivity, specificity, and accuracy for axial 5 mm + 2 mm MPR image versus bone subtraction maps in a "lesion-by-lesion" reading were 97.6%, 92.3%, and 97.2% versus 97.8%, 96.7%, and 97.7%, respectively. The use of bone subtraction maps resulted in a change of response classification in 9.7% of the patients (n = 8) versus 5 mm + 2 mm MPR image reading from SD to PD. Bone sclerosis lesions were detected in 52 out of 82 patients (63.4%). The reading time was significantly lower with the software bone subtraction compared to standard reading (P < 0.01) and 1-mm image reading (P < 0.001).

CONCLUSION

Accuracy of bone subtraction maps reading for monitoring multiple myeloma is slightly increased over that of conventional axial + MPR image reading and significantly speeds up the reading time.

Improved MDCT monitoring of pelvic myeloma bone disease through the use of a novel longitudinal bone subtraction post-processing algorithm

PURPOSE

To evaluate the diagnostic performance of a novel CT post-processing software that generates subtraction maps of baseline and follow-up CT examinations in the course of myeloma bone lesions.

MATERIALS AND METHODS

This study included 61 consecutive myeloma patients who underwent repeated whole-body reduced-dose MDCT at our institution between November 2013 and June 2015. CT subtraction maps classified a progressive disease (PD) vs. stable disease (SD)/remission. Bone subtraction maps (BSMs) only and in combination with 1-mm (BSM+) source images were compared with 5-mm axial/MPR scans.

RESULTS

Haematological response categories at follow-up were: complete remission (n = 9), very good partial remission (n = 2), partial remission (n = 17) and SDh (n = 19) vs. PDh (n = 14). Five-millimetre CT scan yielded PD (n = 14) and SD/remission (n = 47) whereas bone subtraction + 1-mm axial scans (BSM+) reading resulted in PD (n = 18) and SD/remission (n = 43). Sensitivity/ specificity/accuracy for 5-mm/1-mm/BSM(alone)/BSM + in "lesion-by-lesion" reading was 89.4 %/98.9 %/98.3 %/ 99.5 %; 69.1 %/96.9 %/72 %/92.1 % and 83.8 %/98.4 %/92.1 %/98.3 %, respectively. The use of BSM+ resulted in a change of response classification in 9.8 % patients (n = 6) from SD to PD.

CONCLUSION

BSM reading is more accurate for monitoring myeloma compared to axial scans whereas BSM+ yields similar results with 1-mm reading (gold standard) but by significantly reduced reading time.

KEY POINTS

• CT evaluation of myeloma bone disease using a longitudinal bone subtraction post-processing algorithm. • Bone subtraction post-processing algorithm is more accurate for assessment of therapy. • Bone subtraction allowed improved and more efficient detection of myeloma bone lesions. • Post-processing tool demonstrating a change in response classification in 9.8 % patients (all showing PD). • Reading time could be substantially shortened as compared to regular CT assessment.