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Diagnostics
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Advances in Multiple Myeloma Imaging
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Advances in Multiple Myeloma Imaging

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 6331

Special Issue Editor

Dr. Majid Chalian

E-Mail Website
Guest Editor
Department of Radiology, Division of Musculoskeletal Imaging and Intervention, University of Washington, Seattle, WA 98195, USA
Interests: radiology; imaging; musculoskeletal radiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Multiple myeloma (MM) remains a debilitating disease despite recent advances in diagnosis and treatment with 1:150 lifetime risk, higher incidence in the elderly and black population, and approximately 10-year life expectancy after diagnosis in the United States. Advances in imaging technology with multi-slice CTs, high-resolution 3T MRIs, and state-of-the-art CT, MRI, and PET/CT techniques have revolutionized the diagnosis of musculoskeletal disorders, including MM, and provided us with new opportunities for improved patient care. New imaging techniques have made it possible to predict disease processes. Modern imaging has created an opportunity for the early diagnosis and treatment of patients with MM.

This field has already changed and will continue changing with novel approaches such as radiomics, machine learning, and quantitative analysis using multiparametric imaging. All these new emerging diagnostic approaches are advocating the idea of precision and personalized medicine. This Special Issue aims to provide updates on novel diagnostic approaches for imaging in patients with MM.

Dr. Majid Chalian
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • PET/CT
  • MRI
  • multiple myeloma
  • diagnosis
  • multiparametric imaging

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Published Papers (3 papers)

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Review

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14 pages, 8969 KiB  
Review
Monoclonal Gammopathy of Clinical Significance (MGCS) and Related Disorders: A Review and the Role of Imaging
by Ahmed O. El Sadaney, Anika Dutta, Joselle Cook and Francis I. Baffour
Diagnostics 2024, 14(17), 1907; https://doi.org/10.3390/diagnostics14171907 - 29 Aug 2024
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Abstract
The term monoclonal gammopathy of clinical significance (MGCS) refers to a group of symptomatic monoclonal gammopathies that do not meet the diagnostic criteria for malignant plasma cell disorders, such as multiple myeloma or Waldenström macroglobulinemia. These symptoms are attributable to the paraneoplastic effects [...] Read more.
The term monoclonal gammopathy of clinical significance (MGCS) refers to a group of symptomatic monoclonal gammopathies that do not meet the diagnostic criteria for malignant plasma cell disorders, such as multiple myeloma or Waldenström macroglobulinemia. These symptoms are attributable to the paraneoplastic effects of monoclonal immunoglobulins that occur through diverse mechanisms. The presence of symptoms distinguishes MGCS from monoclonal gammopathy of undetermined significance, which lacks significant symptomatic presentation. The presentations of MGCS are manifold, adding to the diagnostic challenge. Clinical suspicion is key for accurate and timely diagnosis. Radiologic imaging can provide pivotal information to guide the diagnosis. In this review, we discuss MGCS from a radiology perspective and highlight pertinent imaging features associated with the disorders. Full article
(This article belongs to the Special Issue Advances in Multiple Myeloma Imaging)
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4 pages, 4544 KiB  
Interesting Images
Flower-Shaped Plasma Cells in Multiple Myeloma with Morphological Heterogeneity
by Hiroki Hosoi, Misato Tane, Makiko Sogabe, Ryuta Iwamoto, Naoto Minoura, Shogo Murata, Toshiki Mushino, Akinori Nishikawa, Shin-Ichi Murata and Takashi Sonoki
Diagnostics 2024, 14(20), 2285; https://doi.org/10.3390/diagnostics14202285 - 14 Oct 2024
Viewed by 1095
Abstract
Background: Flower-shaped nuclei in plasma cells are rare in multiple myeloma. Case presentation: We report on an 88-year-old male who presented with a mass lesion in the clavicular region. A biopsy of the mass revealed an increase in mature plasma cells with round [...] Read more.
Background: Flower-shaped nuclei in plasma cells are rare in multiple myeloma. Case presentation: We report on an 88-year-old male who presented with a mass lesion in the clavicular region. A biopsy of the mass revealed an increase in mature plasma cells with round nuclei. In contrast, a bone marrow examination showed increased plasma cells with flower-shaped nuclei. The patient tested negative for human T-lymphotropic virus type-1 and was diagnosed with multiple myeloma. Conclusions: While multiple myeloma is known for intra-tumor heterogeneity, reports of morphological heterogeneity based on the site of tumor sampling are limited. In this case, the presence of plasma cells with flower-shaped nuclei enabled the identification of site-dependent morphological tumor heterogeneity. Full article
(This article belongs to the Special Issue Advances in Multiple Myeloma Imaging)
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17 pages, 686 KiB  
Systematic Review
Current Status and Future of Artificial Intelligence in MM Imaging: A Systematic Review
by Ehsan Alipour, Atefe Pooyan, Firoozeh Shomal Zadeh, Azad Duke Darbandi, Pietro Andrea Bonaffini and Majid Chalian
Diagnostics 2023, 13(21), 3372; https://doi.org/10.3390/diagnostics13213372 - 2 Nov 2023
Viewed by 2583
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Advances in Multiple Myeloma Imaging)
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