Computed tomography-based skeletal segmentation for quantitative PET metrics of bone involvement in multiple myeloma

Recent advances in imaging and artificial intelligence (AI) for quantitative assessment of multiple myeloma

Multiple myeloma (MM) is a malignant blood disease, but there have been significant improvements in the prognosis due to advancements in quantitative assessment and targeted therapy in recent years. The quantitative assessment of MM bone marrow infiltration and prognosis prediction is influenced by imaging and artificial intelligence (AI) quantitative parameters. At present, the primary imaging methods include computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). These methods are now crucial for diagnosing MM and evaluating myeloma cell infiltration, extramedullary disease, treatment effectiveness, and prognosis. Furthermore, the utilization of AI, specifically incorporating machine learning and radiomics, shows great potential in the field of diagnosing MM and distinguishing between MM and lytic metastases. This review discusses the advancements in imaging methods, including CT, MRI, and PET/CT, as well as AI for quantitatively assessing MM. We have summarized the key concepts, advantages, limitations, and diagnostic performance of each technology. Finally, we discussed the challenges related to clinical implementation and presented our views on advancing this field, with the aim of providing guidance for future research.

The role of conventional and novel PET radiotracers in assessment of myeloma bone disease

Over 80 % of patients with multiple myeloma (MM) experience osteolytic bone lesions, primarily due to an imbalanced interaction between osteoclasts and osteoblasts. This imbalance can lead to several adverse outcomes such as pain, fractures, limited mobility, and neurological impairments. Myeloma bone disease (MBD) raises the expense of management in addition to being a major source of disability and morbidity in myeloma patients. Whole-body x-ray radiography was the gold standard imaging modality for detecting lytic lesions. Osteolytic lesions are difficult to identify at an earlier stage on X-ray since the lesions do not manifest themselves on conventional radiographs until at least 30 % to 50 % of the bone mass has been destroyed. Hence, early diagnosis of osteolytic lesions necessitates the utilization of more complex and advanced imaging modalities, such as PET. One of the PET radiotracers that has been frequently investigated in MM is 18F-FDG, which has demonstrated a high level of sensitivity and specificity in detecting myeloma lesions. However, 18F-FDG PET/CT has several restrictions, and therefore the novel PET tracers that can overcome the limitations of 18F-FDG PET/CT should be further examined in assessment of MBD. The objective of this review article is to thoroughly examine the significance of both conventional and novel PET radiotracers in the assessment of MBD. The intention is to present the information in a manner that would be easily understood by healthcare professionals from diverse backgrounds, while minimizing the use of complex nuclear medicine terminology.

Current Status and Future of Artificial Intelligence in MM Imaging: A Systematic Review

Artificial intelligence (AI) has attracted increasing attention as a tool for the detection and management of several medical conditions. Multiple myeloma (MM), a malignancy characterized by uncontrolled proliferation of plasma cells, is one of the most common hematologic malignancies, which relies on imaging for diagnosis and management. We aimed to review the current literature and trends in AI research of MM imaging. This study was performed according to the PRISMA guidelines. Three main concepts were used in the search algorithm, including "artificial intelligence" in "radiologic examinations" of patients with "multiple myeloma". The algorithm was used to search the PubMed, Embase, and Web of Science databases. Articles were screened based on the inclusion and exclusion criteria. In the end, we used the checklist for Artificial Intelligence in Medical Imaging (CLAIM) criteria to evaluate the manuscripts. We provided the percentage of studies that were compliant with each criterion as a measure of the quality of AI research on MM. The initial search yielded 977 results. After reviewing them, 14 final studies were selected. The studies used a wide array of imaging modalities. Radiomics analysis and segmentation tasks were the most popular studies (10/14 studies). The common purposes of radiomics studies included the differentiation of MM bone lesions from other lesions and the prediction of relapse. The goal of the segmentation studies was to develop algorithms for the automatic segmentation of important structures in MM. Dice score was the most common assessment tool in segmentation studies, which ranged from 0.80 to 0.97. These studies show that imaging is a valuable data source for medical AI models and plays an even greater role in the management of MM.

Clinical Application of 18F-FDG-PET Quantification in Hematological Malignancies: Emphasizing Multiple Myeloma, Lymphoma and Chronic Lymphocytic Leukemia

Most hematological malignancies display heightened glycolytic activity, leading to their detectability through 18F-FDG-PET imaging. PET quantification enables the extraction of metabolic information from tumors. Among various PET measurements, maximum standardized uptake value (SUVmax), which indicates the highest value of 18F-FDG uptake within the tumor, has emerged as the commonly used parameter in clinical oncology. This is because of SUVmax ease of calculation using most available commercial workstations, as well as its simplicity and independence from observer interpretation. Nonetheless, SUVmax represents the increase in activity within a specific small area, which may not fully capture the overall tumor uptake. Volumetric PET parameters have been identified as a potential solution to overcome certain limitations associated with SUVmax. However, these parameters are influenced by the low spatial resolution of PET when assessing small lesions. Another challenge is the high number of lesions observed in some patients, leading to a time-consuming process for evaluating all focal lesions. Some institutions recently have started advocating for CT-based segmentation as a method for measuring radiotracer uptake in the bone marrow and overall bone of the patients. This review article aims to provide insights into clinical application of PET quantification specifically focusing on 3 major hematologic malignancies: multiple myeloma, lymphoma, and chronic lymphocytic leukemia.

Diagnostic value of WB-DWI versus 18F-FDG PET/CT for the detection of multiple myeloma

Background

Whole-body diffusion-weighted imaging (WB-DWI) is commonly used for the detection of multiple myeloma (MM). Comparative data on the efficiency of WB-DWI compared with F-18 fluoro-2-deoxy-d-glucose positron emission tomography-computed tomography (18F-FDG PET/CT) to detect MM is limited.

Methods

This was a retrospective, single-center study of 22 patients with MM enrolled from January 2018 to December 2019. All patients underwent WB-DWI and 18F-FDG PET/CT. Pathological and clinical manifestations, as well as radiologic follow-up, were used for diagnosis. The overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of both methods were compared. The apparent diffusion coefficient (ADC) values of MM lesions and false-positive lesions were estimated.

Results

A total of 214 MM bone lesions were evaluated. There was no significant difference in the accuracy of WB-DWI and PET/CT (86.92 versus 88.32%). Though WB-DWI had a higher sensitivity (99.26% versus84.56%) and PET-CT had a higher specificity (96.10% versus 64.56%), these differences were not statistically significant. There was a statistically significant difference in PPV (83.33% versus 96.64%) and NPV (98.08% versus 77.89%) of WB-DWI and PET/CT, respectively. The ADC value for MM lesions was significantly lower than that for false-positive lesions (P < 0.001). Receiver operating curve analysis showed that the AUC was 0.846, and when the cut-off value was 0.745 × 10-3 mm2/s, the sensitivity and specificity were 86.3 and 83.4%, respectively, which distinguished MM lesions from non-MM lesions.

Conclusion

WB-DWI and PET-CT scans have similar overall accuracy for detecting MM lesions. The higher PPV of PET-CT and NPV of WB-DWI make them complementary imaging modalities. The ADC value for MM lesions is significantly lower than that for false-positive lesions. An ADC cutoff value of 0.745 × 10-3 mm2/s results in sensitivity and specificity of 86.3 and 83.4%, respectively.

Systematic Review of Tumor Segmentation Strategies for Bone Metastases

Purpose: To investigate the segmentation approaches for bone metastases in differentiating benign from malignant bone lesions and characterizing malignant bone lesions. Method: The literature search was conducted in Scopus, PubMed, IEEE and MedLine, and Web of Science electronic databases following the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A total of 77 original articles, 24 review articles, and 1 comparison paper published between January 2010 and March 2022 were included in the review. Results: The results showed that most studies used neural network-based approaches (58.44%) and CT-based imaging (50.65%) out of 77 original articles. However, the review highlights the lack of a gold standard for tumor boundaries and the need for manual correction of the segmentation output, which largely explains the absence of clinical translation studies. Moreover, only 19 studies (24.67%) specifically mentioned the feasibility of their proposed methods for use in clinical practice. Conclusion: Development of tumor segmentation techniques that combine anatomical information and metabolic activities is encouraging despite not having an optimal tumor segmentation method for all applications or can compensate for all the difficulties built into data limitations.

Modern imaging techniques for monitoring patients with multiple myeloma

Bone disease is a serious problem for many patients, often causing pathological bone fractures. A spinal collapse is a condition that affects the quality of life. It is the most frequent feature of multiple myeloma (MM), used in establishing the diagnosis and the need to start treatment. Because of these complications, imaging plays a vital role in the diagnosis and workup of myeloma patients. For many years, conventional radiography has been considered the gold standard for detecting bone lesions. The main reasons are the wide availability, low cost, the relatively low radiation dose and the ability of this imaging method to cover the entire bone system. Because of its incapacity to evaluate the response to therapy, more sophisticated techniques such as whole-body low-dose computed tomography (WBLDCT), whole-body magnetic resonance imaging, and 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (PET/CT) are used. In this review, some of the advantages, indications and applications of the three techniques in managing patients with MM will be discussed. The European Myeloma Network guidelines have recommended WBLDCT as the imaging modality of choice for the initial assessment of MM-related lytic bone lesions. Magnetic resonance imaging is the gold-standard imaging modality for the detection of bone marrow involvement. One of the modern imaging methods and PET/CT can provide valuable prognostic data and is the preferred technique for assessing response to therapy.

Bone marrow segmentation and radiomics analysis of [18F]FDG PET/CT images for measurable residual disease assessment in multiple myeloma

BACKGROUND AND OBJECTIVES

The last few years have been crucial in defining the most appropriate way to quantitatively assess [¹⁸F]FDG PET images in Multiple Myeloma (MM) patients to detect persistent tumor burden. The visual evaluation of images complements the assessment of Measurable Residual Disease (MRD) in bone marrow samples by multiparameter flow cytometry (MFC) or next-generation sequencing (NGS). The aim of this study was to quantify MRD by analyzing quantitative and texture [¹⁸F]FDG PET features.

METHODS

Whole body [¹⁸F]FDG PET of 39 patients with newly diagnosed MM were included in the database, and visually evaluated by experts in nuclear medicine. A segmentation methodology of the skeleton from CT images and an additional manual segmentation tool were proposed, implemented in a software solution including a graphical user interface. Both the compact bone and the spinal canal were removed from the segmentation to obtain only the bone marrow mask. SUV metrics, GLCM, GLRLM, and NGTDM parameters were extracted from the PET images and evaluated by Mann-Whitney U-tests and Spearman ρ rank correlation as valuable features differentiating PET+/PET- and MFC+/MFC- groups. Seven machine learning algorithms were applied for evaluating the classification performance of the extracted features.

RESULTS

Quantitative analysis for PET+/PET- differentiating demonstrated to be significant for most of the variables assessed with Mann-Whitney U-test such as Variance, Energy, and Entropy (p-value = 0.001). Moreover, the quantitative analysis with a balanced database evaluated by Mann-Whitney U-test revealed in even better results with 19 features with p-values < 0.001. On the other hand, radiomics analysis for MFC+/MFC- differentiating demonstrated the necessity of combining MFC evaluation with [¹⁸F]FDG PET assessment in the MRD diagnosis. Machine learning algorithms using the image features for the PET+/PET- classification demonstrated high performance metrics but decreasing for the MFC+/MFC- classification.

CONCLUSIONS

A proof-of-concept for the extraction and evaluation of bone marrow radiomics features of [¹⁸F]FDG PET images was proposed and implemented. The validation showed the possible use of these features for the image-based assessment of MRD.

A review of different methods used for quantification and assessment of FDG-PET/CT in multiple myeloma

The quantification of positron emission tomography/computed tomography (PET/CT) in multiple myeloma (MM) is challenging. Different methods of PET/CT quantification for assessment of fluorodeoxyglucose (FDG) uptake in myeloma patients have been suggested. This is the first review article that focuses on the advantages and disadvantages of each approach. Use of the maximum standardized uptake value (SUVmax) showed some promise in prognostic stratification of MM patients. However, it is affected by noise and time of flight and is subject to high variability. Volumetric PET metrics such as total lesion glycolysis and metabolic tumor volume are other proposed approaches. The high number of osteolytic lesions in MM patients makes this approach difficult in clinical practice. In addition, evaluation of small focal lesions is subject to partial volume correction. CT-based segmentation for assessment of FDG radiotracer is recently introduced. The methodologies are highly reproducible, but the clinical values of the approaches are unclear and still under investigation. We also discuss the Italian Myeloma criteria for PET Use (IMPeTUs), which is a qualitative approach, as a point of comparison. The reproducibility of IMPeTUs depends heavily on the level of user experience. We recommend further studies for assessing the prognostic significance of CT-threshold approaches in the assessment of MM patients.

Metabolic Volume Measurements in Multiple Myeloma

Multiple myeloma (MM) accounts for 10-15% of all hematologic malignancies, as well as 20% of deaths related to hematologic malignant tumors, predominantly affecting bone and bone marrow. Positron emission tomography/computed tomography with 18F-fluorodeoxyglucose (FDG-PET/CT) is an important method to assess the tumor burden of these patients. It is often challenging to classify the extent of disease involvement in the PET scans for many of these patients because both focal and diffuse bone lesions may coexist, with varying degrees of FDG uptake. Different metrics involving volumetric parameters and texture features have been proposed to objectively assess these images. Here, we review some metabolic parameters that can be extracted from FDG-PET/CT images of MM patients, including technical aspects and predicting MM outcome impact. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are volumetric parameters known to be independent predictors of MM outcome. However, they have not been adopted in clinical practice due to the lack of measuring standards. CT-based segmentation allows automated, and therefore reproducible, calculation of bone metabolic metrics in patients with MM, such as maximum, mean and standard deviation of the standardized uptake values (SUV) for the entire skeleton. Intensity of bone involvement (IBI) is a new parameter that also takes advantage of this approach with promising results. Other indirect parameters obtained from FDG-PET/CT images, such as visceral adipose tissue glucose uptake and subcutaneous adipose tissue radiodensity, may also be useful to evaluate the prognosis of MM patients. Furthermore, the use and quantification of new radiotracers can address different metabolic aspects of MM and may have important prognostic implications.

Intensity of bone involvement: a quantitative 18F-FDG PET/CT evaluation for monitoring outcome of multiple myeloma

PURPOSE

The parameter intensity of bone involvement (IBI) was recently proposed to quantitatively assess patients with multiple myeloma using 18F-fluorodeoxyglucose-PET combined with computed tomography (18F-FDG PET/CT) images. Here, we aimed to calculate IBI variation (ΔIBI) between two consecutive PET/CT of the same patient and verified its relationship with a subjective visual analysis of the images and with clinical outcome.

METHODS

Consecutive whole-body 18F-FDG PET/CT performed to assess the outcomes of 29 patients diagnosed with multiple myeloma were retrospectively evaluated. ΔIBI was calculated after bone segmentation, using liver standardized uptake value as a threshold to determine metabolically active volumes in the skeleton. For each pair of consecutive PET/CTs, two nuclear medicine physicians classified visually the most recent image as PET-remission, PET-progression or PET-stable when compared to the previous examination.

RESULTS

The lowest ΔIBI was -1.27 and the highest was 0.29. PET-remission was related to ΔIBI <0 (median = -0.10; -1.27 to +0.03), while PET-progression was related to ΔIBI >0 (median = 0.02; -0.07 to +0.29). ΔIBI around zero was found in images classified as PET-stable (median = 0.00; -0.08 to +0.06). Significant difference in ΔIBI was found between the three groups. Multivariate stepwise analysis showed that IBI value at diagnostic PET/CT, serum calcium and percentage of plasma cells in the bone marrow are independent prognostic factors.

CONCLUSION

Delta IBI provides quantitative data for variations of 18F-FDG uptake in the bone marrow during the follow-up of the patients. In addition, higher IBI values at diagnosis are associated with a higher risk of patient's death.

Bone Metastases Are Measurable: The Role of Whole-Body MRI and Positron Emission Tomography

Metastatic tumor deposits in bone marrow elicit differential bone responses that vary with the type of malignancy. This results in either sclerotic, lytic, or mixed bone lesions, which can change in morphology due to treatment effects and/or secondary bone remodeling. Hence, morphological imaging is regarded unsuitable for response assessment of bone metastases and in the current Response Evaluation Criteria In Solid Tumors 1.1 (RECIST1.1) guideline bone metastases are deemed unmeasurable. Nevertheless, the advent of functional and molecular imaging modalities such as whole-body magnetic resonance imaging (WB-MRI) and positron emission tomography (PET) has improved the ability for follow-up of bone metastases, regardless of their morphology. Both these modalities not only have improved sensitivity for visual detection of bone lesions, but also allow for objective measurements of bone lesion characteristics. WB-MRI provides a global assessment of skeletal metastases and for a one-step "all-organ" approach of metastatic disease. Novel MRI techniques include diffusion-weighted imaging (DWI) targeting highly cellular lesions, dynamic contrast-enhanced MRI (DCE-MRI) for quantitative assessment of bone lesion vascularization, and multiparametric MRI (mpMRI) combining anatomical and functional sequences. Recommendations for a homogenization of MRI image acquisitions and generalizable response criteria have been developed. For PET, many metabolic and molecular radiotracers are available, some targeting tumor characteristics not confined to cancer type (e.g. 18F-FDG) while other targeted radiotracers target specific molecular characteristics, such as prostate specific membrane antigen (PSMA) ligands for prostate cancer. Supporting data on quantitative PET analysis regarding repeatability, reproducibility, and harmonization of PET/CT system performance is available. Bone metastases detected on PET and MRI can be quantitatively assessed using validated methodologies, both on a whole-body and individual lesion basis. Both have the advantage of covering not only bone lesions but visceral and nodal lesions as well. Hybrid imaging, combining PET with MRI, may provide complementary parameters on the morphologic, functional, metabolic and molecular level of bone metastases in one examination. For clinical implementation of measuring bone metastases in response assessment using WB-MRI and PET, current RECIST1.1 guidelines need to be adapted. This review summarizes available data and insights into imaging of bone metastases using MRI and PET.

99mTc-sestamibi SPECT/CT and 18F-FDG-PET/CT have similar performance but different imaging patterns in newly diagnosed multiple myeloma

PURPOSE

F-fluorodeoxiglucose (F-FDG)-PET/CT has been widely used to evaluate multiple myeloma. Tc-sestamibi (MIBI) scintigraphy has also been proposed for assessing multiple myeloma, but its use with state-of-the-art single-photon emission computed tomography/computed tomography (SPECT/CT) technology has not been fully evaluated.This study aimed to compare these two imaging modalities in multiple myeloma staging.

MATERIALS AND METHODS

Sixty-two patients with recently diagnosed multiple myeloma were submitted to whole-body F-FDG-PET/CT and whole-body MIBI scans plus SPECT/CT of the chest and abdomen/pelvis. Number of focal lesions, contiguous soft tissue involvement (CSTI), extramedullary lesions (EMLs) and diffuse bone marrow (BM) involvement were recorded.

RESULTS

PET/CT was positive in 59 patients (95%) and MIBI SPECT/CT in 58 (93%) (P = 0.69). MIBI detected more diffuse bone marrow involvement than PET/CT (respectively 78 vs. 58% of the patients), while PET/CT demonstrated more focal lesions than MIBI SPECT/CT (81 vs. 54% of the patients) (P = 0.002). PET/CT detected EMLs in four subjects and MIBI in one subject. CSTI was found in 28 (45%) and 23 (37%) patients on PET/CT and MIBI images, respectively (P = 0.36). Three patients with lytic lesions and no FDG uptake were MIBI positive, and two subjects with lytic lesions without MIBI uptake were FDG positive.

CONCLUSION

MIBI SPECT/CT performs similarly to F-FDG-PET/CT in identifying sites of active disease in multiple myeloma staging. MIBI is more efficient than FDG for detecting the diffuse involvement of bone marrow but less efficient for detecting focal lesions. Some patients presented a 'mismatch' pattern of FDG/MIBI uptake.