Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation, supplemented by biopsy confirmation. At least three issues burden this approach: a) suboptimal sensitivity and ...suboptimal positive predictive power of radiology screening and diagnostic approaches, respectively; b) invasiveness of biopsy with discomfort for women undergoing diagnostic tests; c) long turnaround time for recall tests. In the screening setting, radiology sensitivity is suboptimal, and when a suspicious lesion is detected and a biopsy is recommended, the positive predictive value of radiology is modest. Recent technological advances in medical imaging, especially in the field of artificial intelligence applied to image analysis, hold promise in addressing clinical challenges in cancer detection, assessment of treatment response, and monitoring disease progression. Radiomics include feature extraction from clinical images; these features are related to tumor size, shape, intensity, and texture, collectively providing comprehensive tumor characterization, the so-called radiomics signature of the tumor. Radiomics is based on the hypothesis that extracted quantitative data derives from mechanisms occurring at genetic and molecular levels. In this article we focus on the role and potential of radiomics in breast cancer diagnosis and prognostication.
•In the screening setting, radiology sensitivity is suboptimal.•Artificial intelligence hold promise in cancer diagnosis and prognostication.•Radiomics include feature extraction from clinical images.
Multiple Myeloma (MM) is the second most common type of hematological disease and, although it is rare among patients under 40 years of age, its incidence rises in elderly subjects. MM manifestations ...are usually identified through hyperCalcemia, Renal failure, Anaemia, and lytic Bone lesions (CRAB). In particular, the extent of the bone disease is negatively related to a decreased quality of life in patients and, in general, bone disease in MM increases both morbidity and mortality. The detection of lytic bone lesions on imaging, especially computerized tomography (CT) and Magnetic Resonance Imaging (MRI), is becoming crucial from the clinical viewpoint to separate asymptomatic from symptomatic MM patients and the detection of focal lytic lesions in these imaging data is becoming relevant even when no clinical symptoms are present. Therefore, radiology is pivotal in the staging and accurate management of patients with MM even in early phases of the disease. In this review, we describe the opportunities offered by quantitative imaging and radiomics in multiple myeloma. At the present time there is still high variability in the choice between various imaging methods to study MM patients and high variability in image interpretation with suboptimal agreement among readers even in tertiary centers. Therefore, the potential of medical imaging for patients affected by MM is still to be completely unveiled. In the coming years, new insights to study MM with medical imaging will derive from artificial intelligence (AI) and radiomics usage in different bone lesions and from the wide implementations of quantitative methods to report CT and MRI. Eventually, medical imaging data can be integrated with the patient's outcomes with the purpose of finding radiological biomarkers for predicting the prognostic flow and therapeutic response of the disease.
Objective
Androgen deprivation therapy alters body composition promoting a significant loss in skeletal muscle (SM) mass through inflammation and oxidative damage. We verified whether SM ...anthropometric composition and metabolism are associated with unfavourable overall survival (OS) in a retrospective cohort of metastatic castration-resistant prostate cancer (mCRPC) patients submitted to 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) imaging before receiving Radium-223.
Patients and methods
Low-dose CT were opportunistically analysed using a cross-sectional approach to calculate SM and adipose tissue areas at the third lumbar vertebra level. Moreover, a 3D computational method was used to extract psoas muscles to evaluate their volume, Hounsfield Units (HU) and FDG retention estimated by the standardized uptake value (SUV). Baseline established clinical, lab and imaging prognosticators were also recorded.
Results
SM area predicted OS at univariate analysis. However, this capability was not additive to the power of mean HU and maximum SUV of psoas muscles volume. These factors were thus combined in the Attenuation Metabolic Index (AMI) whose power was tested in a novel uni- and multivariable model. While Prostate-Specific Antigen (PSA), Alkaline Phosphatase (ALP), Lactate Dehydrogenase and Hemoglobin, Metabolic Tumor Volume, Total Lesion Glycolysis and AMI were associated with long-term OS at the univariate analyses, only PSA, ALP and AMI resulted in independent prognosticator at the multivariate analysis.
Conclusion
The present data suggest that assessing individual 'patients' SM metrics through an opportunistic operator-independent computational analysis of FDG PET/CT imaging provides prognostic insights in mCRPC patients candidates to receive Radium-223.
Graphical abstract
In clinical practice, there is the need to optimize imaging usage in MM patients. Accordingly, the aim of this paper was to develop a simple computed tomography (CT) scoring method for MM, able to ...shorten and simplify the interpretation time with good intra- and inter-reader reliability. This method, named MSBDS (Myeloma Spine and Bone Damage Score) was developed with the final aim to use standard total-body CT in the routine practice of MM centres as a complement of standard evaluations in patients undergoing stem cells transplantation.
We used a widely accepted consensus formation method and literature research during three structured face-to-face meetings specifically designed to combine opinions from a group of experts with proven experience in multiple myeloma care and/or musculoskeletal CT to facilitate the consensus on the field of study topics and the contents of the MSBDS score. Seven practical requisites for the MSBDS score were agreed. A total of 70 MM patients (mean age, 60 years ±9.2 standard deviation; range, 35-70 years) undergoing total-body CT was included to develop MSBDS scores. Patients data were already stored in the Radiological database for other Research studies IRB approved (054/2019). Readers to test the MSDMS were radiologists and clinicians involved in MM care or expert in bone damage scores with different level of experience in musculoskeletal and total body CT. Readers were blinded to the clinical data of the patients.
The MSBDS scores based on the consensus work described above and literature analysis was finalized. MSBDS is based on an additive scale with assessment of a total body CT with the bone window one time and includes indicators of structural bone damage and instability or fracture risk. The total score is given by the sum of item scores for abnormalities detected. Its values range from 0 (minimum) to values > 10 where 10 is represented by high-risk patients. In high-risk patients immediate surgical or radiation oncologist consultation is suggested.
The MSBDS descriptive criteria are easy, highly reproducible and can be considered as a strong base for harmonizing total body CT interpretation in multiple myeloma patients undergoing stem cell transplantation.
Edge detection is a widely used tool in signal/image processing with the aim of identifying abrupt changes or discontinuities in a signal/digital image. For the detection of jump discontinuities in ...1D problems, we present an iterative method based on interpolation with Variably Scaled Kernels (VSKs). This is shown to outperform an existing iterative edge detection method based on multiquadric (MQ) radial basis function interpolation.
To extend our purely one-dimensional edge detector to any dimension, we then introduce an innovative non iterative technique that detects jumps/edges by identifying the local maxima of the normalized absolute values of the RBF interpolant coefficients. The RBF interpolant is built-upon the compactly supported C2 Wendland function and exploits its advantageous properties to provide a robust and low-cost method. Numerical examples in 1D and 2D are included to illustrate its effectiveness and efficiency. In the context of edge detection for digital images, comparisons with Canny method are also presented.
Multiple myeloma is a plasma cell dyscrasia characterized by focal and non-focal bone lesions. Radiomic techniques extract morphological information from computerized tomography images and exploit ...them for stratification and risk prediction purposes. However, few papers so far have applied radiomics to multiple myeloma. A retrospective study approved by the institutional review board: n = 51 transplanted patients and n = 33 (64%) with focal lesion analyzed via an open-source toolbox that extracted 109 radiomics features. We also applied a dedicated tool for computing 24 features describing the whole skeleton asset. The redundancy reduction was realized via correlation and principal component analysis. Fuzzy clustering (FC) and Hough transform filtering (HTF) allowed for patient stratification, with effectiveness assessed by four skill scores. The highest sensitivity and critical success index (CSI) were obtained representing each patient, with 17 focal features selected via correlation with the 24 features describing the overall skeletal asset. These scores were higher than the ones associated with a standard cytogenetic classification. The Mann–Whitney U-test showed that three among the 17 imaging descriptors passed the null hypothesis. This AI-based interpretation of radiomics features stratified relapsed and non-relapsed MM patients, showing some potentiality for the determination of the prognostic image-based biomarkers in disease follow-up.
Purpose
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease leading to neuromuscular palsy and death. We propose a computational approach to 18F-fluorodeoxyglucose (FDG) PET/CT images ...to analyze the structure and metabolic pattern of skeletal muscle in ALS and its relationship with disease aggressiveness.
Materials and methods
A computational 3D method was used to extract whole psoas muscle’s volumes and average attenuation coefficient (AAC) from CT images obtained by FDG PET/CT performed in 62 ALS patients and healthy controls. Psoas average standardized uptake value (normalized on the liver, N-SUV) and its distribution heterogeneity (defined as N-SUV variation coefficient, VC-SUV) were also extracted. Spinal cord and brain motor cortex FDG uptake were also estimated.
Results
As previously described, FDG uptake was significantly higher in the spinal cord and lower in the brain motor cortex, in ALS compared to controls. While psoas AAC was similar in patients and controls, in ALS a significant reduction in psoas volume (3.6 ± 1.02 vs 4.12 ± 1.33 mL/kg;
p
< 0.01) and increase in psoas N-SUV (0.45 ± 0.19 vs 0.29 ± 0.09;
p
< 0.001) were observed. Higher heterogeneity of psoas FDG uptake was also documented in ALS (VC-SUV 8 ± 4%, vs 5 ± 2%, respectively,
p
< 0.001) and significantly predicted overall survival at Kaplan–Meier analysis. VC-SUV prognostic power was confirmed by univariate analysis, while the multivariate Cox regression model identified the spinal cord metabolic activation as the only independent prognostic biomarker.
Conclusion
The present data suggest the existence of a common mechanism contributing to disease progression through the metabolic impairment of both second motor neuron and its effector.
Genome sharing between cancer and normal tissues might imply a similar susceptibility to chemotherapy toxicity. The present study aimed to investigate whether curative potential of doxorubicin, ...bleomycin, vinblastine, and dacarbazine (ABVD) is predicted by the metabolic response of normal tissues in patients with Hodgkin lymphoma (HL). METHODS: According to current guidelines, 86 patients with advanced-stage (IIB-IVB) HL, prospectively enrolled in the HD0607 trial (NCT00795613), underwent 18 F-fluorodeoyglucose PET/CT imaging at diagnosis and, at interim, after two ABVD courses, to decide regimen maintenance or its escalation. In both scans, myocardial FDG uptake was binarized according to its median value. Death and disease relapse were recorded to estimate progression-free survival (PFS) during a follow-up with median duration of 43.8 months (range 6.97–60). RESULTS: Four patients (4.6%) died, while six experienced disease relapse (7%). Complete switch-off of cancer lesions and cardiac lighting predicted a favorable outcome at Kaplan–Mayer analyses. The independent nature and additive predictive value of their risk prediction were confirmed by the multivariate Cox regression analysis. CONCLUSION: Susceptibility of HL lesions to chemotherapy is at least partially determined by factors featuring the host who developed it.
•Spline-based algorithm for the semi-automated recognition of planar curvilinear profiles in digital images.•Neither a family of predefined curves nor a look-up table of prototypal shapes required as ...input.•Robustness with respect to background noise guaranteed.•Favorable comparison with existing profile extraction algorithms relying on the Hough transform technique.•Effectiveness tested on real medical images.
We develop a novel method for the recognition of curvilinear profiles in digital images. The proposed method, semi-automatic for both closed and open planar profiles, essentially consists of a preprocessing step exploiting an edge detection algorithm, and a main step involving the Hough transform technique. In the preprocessing step, a Canny edge detection algorithm is applied in order to obtain a reduced point set describing the profile curve to be reconstructed. Also, to identify in the profile possible sharp points like cusps, we additionally use an algorithm to find the approximated tangent vector of every edge point. In the subsequent main step, we then use a piecewisely defined Hough transform to locally recognize from the point set a low-degree piecewise polynomial curve. The final outcome of the algorithm is thus a spline curve approximating the underlined profile image. The output curve consists of polynomial pieces connected G1 continuously, except in correspondence of the identified cusps, where the order of continuity is only C0, as expected. To illustrate effectiveness and efficiency of the new profile detection technique we present several numerical results dealing with detection of open and closed profiles in images of different type, i.e., medical and photographic images.
We present and analyze several prediction strategies in the 2D setting based on multiquadric radial basis function interpolation with either linear or Weighted Essentially Non Oscillatory (WENO) ...shape parameter approximation. When considered within Harten’s framework for Multiresolution, these prediction operators give rise to sparse multi-scale representations of 2D signals, whose compression capabilities are demonstrated through numerical experiments. It is well know that the accuracy of multiquadric interpolation depends on the choice of the shape parameter. In addition, in 6, it was shown that the use of data-dependent strategies in the selection of the shape parameter leads to more accurate reconstructions. We shall show that our local adaptive estimates of the shape parameters lead to non-separable, fully 2D, reconstruction strategies that lead, in turn, to efficient compression algorithms.
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