PET imaging of CXCR4 expression using [18F]AlF-NOTA-QHY-04 for hematologic malignancy and solid tumors.

C-X-C motif chemokine receptor 4 (CXCR4) is an attractive target for the diagnosis and treatment of cancers. Here, we aimed to develop a new CXCR4-targeted PET tracer, and to investigate the translational potential for noninvasive imaging of CXCR4 expression in various cancer entities through preclinical and pilot clinical studies. Methods [18F]AlF-NOTA-QHY-04 was synthesized and evaluated by cellular uptake, blocking and biolayer interferometry studies in vitro. The pharmacokinetics, biodistribution, and imaging specificity were researched in tumor-bearing mice. [18F]AlF-NOTA-QHY-04 PET/CT imaging was performed on 55 patients with different types of cancers. Correlations between ex vivo CXCR4 expression and PET parameters, and CXCR4 expression characteristics in different tumors were analyzed by histopathological staining in patients. Results [18F]AlF-NOTA-QHY-04 was prepared with high radiolabeling yield and radiochemical purity, exhibiting good stability, high binding affinity and specificity for CXCR4. NCI-H69 (small cell lung cancer, SCLC) tumor-bearing mice showed the highest tumor uptake (4.98 ± 0.98%ID/mL, P < 0.0001) on PET imaging except for Daudi lymphoma xenograft model, which was consistent with the results of cellular and histological analyses. Patients with diffuse large B-cell lymphoma showed the highest tumor uptake (SUVmax, 11.10 ± 4.79) followed by SCLC patients (SUVmax, 7.51 ± 3.01), which were both significantly higher than other solid tumors (P < 0.05). The radiotracer uptake of high-grade gliomas is significantly higher than that of low-grade gliomas (3.13 ± 0.58 vs. 1.18 ± 0.51, P = 0.005). Significant higher tumor-to-normal brain ratio of [18F]AlF-NOTA-QHY-04 than [18F]FDG was found in primary brain tumors (62.55 ± 43.24 vs 1.70 ± 0.25, P = 0.027). Positive correlations between ex vivo CXCR4 expression and [18F]AlF-NOTA-QHY-04 uptake (all P < 0.01) were recorded. Multicolor immunofluorescence staining indicated the high tracer uptake in certain patients was mainly due to the high expression of CXCR4 in tumor cells, followed by macrophages. Conclusion The CXCR4-targeted radiotracer [18F]AlF-NOTA-QHY-04 was successfully prepared with favorable yield, high specificity and binding affinity to CXCR4. Preclinical and pilot clinical studies demonstrated its feasibility and potential application in precise diagnosis for not only lymphoma but also SCLC and glioma. [18F]AlF-NOTA-QHY-04 PET/CT can also provide a complementary mapping for brain tumors to [18F]FDG PET/CT.

Haemato-radiology: the role of the radiologist at MDT.

Haemato-radiology represents a relatively newly emerging, vast, and complex area of diagnostic imaging. Its complexity arises from the multimodality nature of patient assessment, the multisystem presentation of haematological malignancies and their complications, and the volume of imaging required for diagnosis and follow-up of the fifth most common malignancy type in the United Kingdom. Decisive and accurate assessment of disease by radiologists is at the heart of the haemato-oncology multidisciplinary team (MDT) and therefore essential for providing optimal patient care. We hope to support radiologists leading the MDT by streamlining the vast information in this field, emphasizing the most recent, evidence-based guidelines, and internationally accepted criteria for reporting imaging of lymphoma and myeloma. We also cover the various disease and treatment complications frequently presented to the MDT.

PET/CT in the Evaluation of CAR-T Cell Immunotherapy in Hematological Malignancies.

Chimeric antigen receptor (CAR)-T cell-based immunotherapy has emerged as a path-breaking strategy for certain hematological malignancies. Assessment of the response to CAR-T therapy using quantitative imaging techniques such as positron emission tomography/computed tomography (PET/CT) has been broadly investigated. However, the definitive role of PET/CT in CAR-T therapy remains to be established. [18F]FDG PET/CT has demonstrated high sensitivity and specificity for differentiating patients with a partial and complete response after CAR-T therapy in lymphoma. The early therapeutic response and immune-related adverse effects such as cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome can also be detected on [18F]FDG PET images. In otherwise asymptomatic lymphoma patients with partial response following CAR-T therapy, the only positive findings could be abnormal PET/CT results. In multiple myeloma, a negative [18F]FDG PET/CT after receiving B-cell maturation antigen-directed CAR-T therapy has been associated with a favorable prognosis. In leukemia, [18F]FDG PET/CT can detect extramedullary metastases and treatment responses after therapy. Hence, PET/CT is a valuable imaging tool for patients undergoing CAR-T therapy for pretreatment evaluation, monitoring treatment response, assessing safety, and guiding therapeutic strategies. Developing guidelines with standardized cutoff values for various PET parameters and tumor cell-specific tracers may improve the efficacy and safety of CAR-T therapy.

Role of Novel Quantitative Imaging Techniques in Hematological Malignancies.

Hematological malignancies exhibit a widespread distribution, necessitating evaluation of disease activity over the entire body. In clinical practice, visual analysis and semiquantitative parameters are used to assess 18F-FDGPET/CT imaging, which solely represents measurements of disease activity from limited area and may not adequately reflect global disease assessment. An efficient method for assessing the global disease burden of hematological malignancies is to employ PET/computed tomography based novel quantitative parameters. In this article, we explored novel quantitative parameters on PET/CT imaging for assessing global disease burden and the potential role of artificial intelligence (AI) to determine these parameters in evaluation of hematological malignancies.

Multi-organ abnormalities assessed by a single MRI scan in individuals with blood cancer.

BACKGROUND: During the COVID-19 pandemic individuals with all blood cancers were classified as clinically vulnerable and at high risk of complications and death. Our study sought to determine if individuals with specific blood cancers were at a heightened risk of longer term organ impairment, secondary to SARS-CoV-2 infection. METHODS: We set up a prospective observational study, utilising quantitative multi-parametric MRI to determine organ health over time in patients with specific blood cancers who had recovered from COVID-19. RESULTS: Multi-organ abnormality was more prevalent in blood cancer patients than in healthy controls (42 % vs 6 % p < 0.001) but comparable to the long COVID controls (42 % vs 33 %, p > 0.05). At 6 month follow up scans, organ abnormalities persisted in most individuals with blood cancer (71 % ≥1 organ and 52 % multi-organ). CONCLUSION: A multi-organ MRI platform offers the capacity to accurately evaluate organ health dynamically in blood cancers and detect asymptomatic organ impairment. The application of multi-organ MRI could aid early detection and longitudinal monitoring of organ impairment, potentially guiding more personalised treatment strategies and improving clinical outcomes in many rare diseases.

Chest CT at X-Ray Dose Using a Noise-Mitigating Weighted Projection: The Thoracic Tomogram. Diagnostic Performance for Pneumonia Detection in Hemato-Oncology Patients.

PURPOSE: To compare the diagnostic performance of a thick-slab reconstruction obtained from an ultra-low-dose CT (termed thoracic tomogram) with standard-of-care low-dose CT (SOC-CT) for rapid interpretation and detection of pneumonia in hemato-oncology patients. METHODS: Hemato-oncology patients with a working diagnosis of pneumonia underwent an SOC-CT followed by an ultra-low-dose CT, from which the thoracic tomogram (TT) was reconstructed. Three radiologists evaluated the TT and SOC-CT in the following categories: (I) infectious/inflammatory opacities, (II) small airways infectious/inflammatory changes, (III) atelectasis, (IV) pleural effusions, and (V) interstitial abnormalities. The TT interpretation time and radiation dose were recorded. Sensitivity, specificity, diagnostic accuracy, ROC, and AUC were calculated with the corresponding power analyses. The agreement between TT and SOC-CT was calculated by Correlation Coefficient for Repeated Measures (CCRM), and the Shrout-Fleiss intra-class correlations test was used to calculate interrater agreement. RESULTS: Forty-seven patients (mean age 58.7 ± 14.9 years; 29 male) were prospectively enrolled. Sensitivity, specificity, accuracy, AUC, and Power for categories I/II/III/IV/V were: 94.9/99/97.9/0.971/100, 78/91.2/86.5/0.906/100, 88.6/100/97.2/0.941/100, 100/99.2/99.3/0.995/100, and 47.6/100/92.2/0.746/87.3. CCRM between TT and SOC-CT for the same categories were .97/.81/.92/.96/.62 with an interobserver agreement of .93/.88/.82/.96/.61. Mean interpretation time was 18.6 ± 5.4 seconds. The average effective radiation dose of TT was similar to a frontal and lateral chest X-ray (0.27 ± 0.08 vs 1.46 ± 0.64 mSv for SOC-CT; P < .01). CONCLUSION: Thoracic tomograms provide comparable diagnostic information to SOC-CT for the detection of pneumonia in immunocompromised patients at one-fifth of the radiation dose with high interobserver agreement.

Morphological diagnosis of hematologic malignancy using feature fusion-based deep convolutional neural network.

Leukemia is a cancer of white blood cells characterized by immature lymphocytes. Due to blood cancer, many people die every year. Hence, the early detection of these blast cells is necessary for avoiding blood cancer. A novel deep convolutional neural network (CNN) 3SNet that has depth-wise convolution blocks to reduce the computation costs has been developed to aid the diagnosis of leukemia cells. The proposed method includes three inputs to the deep CNN model. These inputs are grayscale and their corresponding histogram of gradient (HOG) and local binary pattern (LBP) images. The HOG image finds the local shape, and the LBP image describes the leukaemia cell's texture pattern. The suggested model was trained and tested with images from the AML-Cytomorphology_LMU dataset. The mean average precision (MAP) for the cell with less than 100 images in the dataset was 84%, whereas for cells with more than 100 images in the dataset was 93.83%. In addition, the ROC curve area for these cells is more than 98%. This confirmed proposed model could be an adjunct tool to provide a second opinion to a doctor.

European Association of Nuclear Medicine (EANM) Focus 4 consensus recommendations: molecular imaging and therapy in haematological tumours.

Given the paucity of high-certainty evidence, and differences in opinion on the use of nuclear medicine for hematological malignancies, we embarked on a consensus process involving key experts in this area. We aimed to assess consensus within a panel of experts on issues related to patient eligibility, imaging techniques, staging and response assessment, follow-up, and treatment decision-making, and to provide interim guidance by our expert consensus. We used a three-stage consensus process. First, we systematically reviewed and appraised the quality of existing evidence. Second, we generated a list of 153 statements based on the literature review to be agreed or disagreed with, with an additional statement added after the first round. Third, the 154 statements were scored by a panel of 26 experts purposively sampled from authors of published research on haematological tumours on a 1 (strongly disagree) to 9 (strongly agree) Likert scale in a two-round electronic Delphi review. The RAND and University of California Los Angeles appropriateness method was used for analysis. Between one and 14 systematic reviews were identified on each topic. All were rated as low to moderate quality. After two rounds of voting, there was consensus on 139 (90%) of 154 of the statements. There was consensus on most statements concerning the use of PET in non-Hodgkin and Hodgkin lymphoma. In multiple myeloma, more studies are required to define the optimal sequence for treatment assessment. Furthermore, nuclear medicine physicians and haematologists are awaiting consistent literature to introduce volumetric parameters, artificial intelligence, machine learning, and radiomics into routine practice.

Efficient diagnosis of hematologic malignancies using bone marrow microscopic images: A method based on MultiPathGAN and MobileViTv2.

BACKGROUND AND OBJECTIVES: Hematologic malignancies, including the associated multiple subtypes, are critically threatening to human health. The timely detection of malignancies is crucial for their effective treatment. In this regard, the examination of bone marrow smears constitutes a crucial step. Nonetheless, the conventional approach to cell identification and enumeration is laborious and time-intensive. Therefore, the present study aimed to develop a method for the efficient diagnosis of these malignancies directly from bone marrow microscopic images. METHODS: A deep learning-based framework was developed to facilitate the diagnosis of common hematologic malignancies. First, a total of 2033 microscopic images of bone marrow analysis, including the images for 6 disease types and 1 healthy control, were collected from two Chinese medical websites. Next, the collected images were classified into the training, validation, and test datasets in the ratio of 7:1:2. Subsequently, a method of stain normalization to multi-domains (stain domain augmentation) based on the MultiPathGAN model was developed to equalize the stain styles and expand the image datasets. Afterward, a lightweight hybrid model named MobileViTv2, which integrates the strengths of both CNNs and ViTs, was developed for disease classification. The resulting model was trained and utilized to diagnose patients based on multiple microscopic images of their bone marrow smears, obtained from a cohort of 61 individuals. RESULTS: MobileViTv2 exhibited an average accuracy of 94.28% when applied to the test set, with multiple myeloma, acute lymphocytic leukemia, and lymphoma revealed as the three diseases diagnosed with the highest accuracy values of 98%, 96%, and 96%, respectively. Regarding patient-level prediction, the average accuracy of MobileViTv2 was 96.72%. This model outperformed both CNN and ViT models in terms of accuracy, despite utilizing only 9.8 million parameters. When applied to two public datasets, MobileViTv2 exhibited accuracy values of 99.75% and 99.72%, respectively, and outperformed previous methods. CONCLUSIONS: The proposed framework could be applied directly to bone marrow microscopic images with different stain styles to efficiently establish the diagnosis of common hematologic malignancies.

Differential diagnosis of infectious diseases, drug-induced lung injury, and pulmonary infiltration due to underlying malignancy in patients with hematological malignancy using HRCT.

PURPOSE: To differentiate among infectious diseases, drug-induced lung injury (DILI) and pulmonary infiltration due to underlying malignancy (PIUM) based on high-resolution computed tomographic (HRCT) findings from patients with hematological malignancies who underwent chemotherapy or hematopoietic stem cell transplantation. MATERIALS AND METHODS: A total of 221 immunocompromised patients with hematological malignancies who had proven chest complications (141 patients with infectious diseases, 24 with DILI and 56 with PIUM) were included. Two chest radiologists evaluated the HRCT findings, including ground-glass opacity, consolidation, nodules, and thickening of bronchovascular bundles (BVBs) and interlobular septa (ILS). After comparing these CT findings among the three groups using the χ2test, multiple logistic regression analyses (infectious vs noninfectious diseases, DILI vs non-DILI, and PIUM vs non-PIUM) were performed to detect useful indicators for differentiation. RESULTS: Significant differences were detected in many HRCT findings by the χ2 test. The results from the multiple logistic regression analyses identified several indicators: nodules without a perilymphatic distribution [p = 0.012, odds ratio (95% confidence interval): 4.464 (1.355-11.904)], nodules with a tree-in-bud pattern [p = 0.011, 8.364 (1.637-42.741)], and the absence of ILS thickening[p = 0.003, 3.621 (1.565-8.381)] for infectious diseases, the presence of ILS thickening [p = 0.001, 7.166 (2.343-21.915)] for DILI, and nodules with a perilymphatic distribution [p = 0.011, 4.256 (1.397-12.961)] and lymph node enlargement (p = 0.008, 3.420 (1.385-8.441)] for PIUM. CONCLUSION: ILS thickening, nodules with a perilymphatic distribution, tree-in-bud pattern, and lymph node enlargement could be useful indicators for differentiating among infectious diseases, DILI, and PIUM in patients with hematological malignancies.

Sonographic features of secondary involvement of skin and subcutaneous tissues by hematologic malignancies.

OBJECTIVES: To evaluate the sonographic features of secondary involvement of skin and subcutaneous tissues by hematologic malignancies. METHODS: A review of the ultrasound and pathology databases yielded 10 cases with 13 skin and subcutaneous tissue lesions secondary to hematologic neoplasms, which were confirmed by pathology. We used ultrasound to assess the number, location, size, depth of involvement, echogenicity, and vascularity of the lesions. RESULTS: The study involved five male and five female patients, including four leukemia, two multiple myeloma, and four lymphoma patients. The average age was 45 years (17-66 years). Three patients presented with one lesion, four with two lesions, and three with more than two lesions. All the lesions were located in the trunk and extremities. The lesions ranged from 1.2 to 8.3 cm in size. A total of 10 lesions involved subcutaneous fat tissue. A total of 10 lesions displayed hypoechoic foci within a hyperechoic background, and three appeared hypoechoic, and most of them exhibited abundant vascularity (12 of 13 lesions). CONCLUSIONS: Secondary involvement of skin and subcutaneous tissues by hematologic malignancies often present with multiple palpable masses showing the following ultrasound features: (1) subcutaneous fat infiltration, (2) hypoechoic foci with a hyperechoic background, and (3) abundant vascularity.

Imaging of C-X-C Motif Chemokine Receptor 4 Expression in 690 Patients with Solid or Hematologic Neoplasms Using 68Ga-Pentixafor PET.

In recent years, molecular imaging addressing the C-X-C motif chemokine receptor 4 (CXCR4) has increasingly been used in various clinical settings. Here, we aimed to assess radiopharmaceutical uptake and image contrast to determine the most relevant clinical applications for CXCR4-directed imaging. We also investigated the impact of specific activity on scan contrast. Methods: Patients (n = 690) with a variety of neoplasms underwent a total of 777 PET/CT scans with 68Ga-Pentixafor, serving as the CXCR4-specific radioligand. A semiquantitative target lesion analysis was conducted (providing SUVmax and target-to-blood pool ratio [TBR], defined as SUVmax [from target lesion] divided by SUVmean [from blood pool]). The applied specific activity (in MBq/µg) was compared with semiquantitative assessments. Results: Of the 777 scans, 242 did not show discernible uptake in disease sites, leaving 535 PET scans (68.9%) for further analysis. Very high tracer uptake (SUVmax > 12) was found in multiple myeloma (n = 113), followed by adrenocortical carcinoma (n = 30), mantle cell lymphoma (n = 20), adrenocortical adenoma (n = 6), and small cell lung cancer (n = 12). Providing information on image contrast, comparable results for TBR were recorded, with TBR (>8) in multiple myeloma, mantle cell lymphoma, and acute lymphoblastoid leukemia (n = 6). When comparing specific activity with semiquantitative parameters, no significant correlation was found for SUVmax or TBR (P ≥ 0.612). Conclusion: In this large cohort, 68Ga-Pentixafor demonstrated high image contrast in a variety of neoplasms, particularly for hematologic malignancies, small cell lung cancer, and adrenocortical neoplasms. The present analysis may provide a roadmap for detecting patients who may benefit from CXCR4-targeted therapies.

High-resolution CT findings of pulmonary infections in patients with hematologic malignancy: comparison between patients with or without hematopoietic stem cell transplantation.

PURPOSE: To evaluate the high-resolution CT (HRCT) findings of pulmonary infections in patients with hematologic malignancy and compare them between patients with or without hematopoietic stem cell transplantation (HSCT). MATERIALS AND METHODS: A total of 128 patients with hematologic malignancy and pulmonary infection were included in this study. The diagnoses of the patients consisted of bacterial pneumonia (37 non-HSCT cases and 14 HSCT cases), pneumocystis pneumonia (PCP) (29 non-HSCT cases and 11 HSCT cases), and fungal infection other than PCP (20 non-HSCT cases and 17 HSCT cases). Two chest radiologists retrospectively evaluated the HRCT criteria and compared them using chi-squared tests and a multiple logistic regression analysis. RESULTS: According to the multiple logistic regression analysis, nodules were an indicator in HSCT patients with PCP (p = 0.025; odds ratio, 5.8; 95% confidence interval, 1.2-26.6). The centrilobular distribution of nodules was the most frequent (n = 4, 36%) in HSCT patients with PCP. A mosaic pattern was an indicator of PCP in both HSCT and non-HSCT patients. There were no significant differences in other infections. CONCLUSION: The mosaic pattern could be an indicator of PCP in both HSCT and non-HSCT patients. Nodules with centrilobular distribution might be relatively frequent HRCT findings of PCP in HSCT patients.

Central nervous system manifestations of systemic haematological malignancies and key differentials.

Central nervous system (CNS) involvement by haematological malignancies is uncommon, and generally associated with a poor prognosis. Neuroimaging plays a key role in the accurate diagnosis, including in the critical differentiation from other processes such as infection and treatment-related toxicity. This review illustrates a variety of manifestations of CNS involvement by haematological malignancies and relevant differential diagnoses. CNS involvement can be seen in lymphoma (both primary and secondary), Waldenström macroglobulinaemia, multiple myeloma, leukaemia, and the malignant histiocytoses. The typical patterns vary between the different disorders, for example, in the most common sites of involvement and the relative frequency of parenchymal and meningeal involvement. Adjacent structures may also be involved. Nevertheless, there is some overlap in the imaging appearances, with common features including pre-contrast hyperdensity on computed tomography (CT), diffusion restriction, and avid post-contrast enhancement. In the post-treatment context, it is also important to distinguish between disease relapse and post-treatment effects. This includes opportunistic infections and the effects of chemotherapy and/or radiotherapy, including toxic effects and radiotherapy-induced neoplasms.

Mesial Temporal Sclerosis as Late Consequence of Posterior Reversible Encephalopathy Syndrome in Pediatric Hemato-oncologic Patients.

OBJECTIVES: Drug resistant epilepsy has rarely been reported following posterior reversible encephalopathy syndrome (PRES), with few cases of mesial temporal sclerosis (MTS). The aim of this study was to report clinical and neuroimaging features of MTS subsequent to PRES in hemato-oncologic/stem cell transplanted children. MATERIALS AND METHODS: Among 70 children treated in 2 pediatric hemato-oncologic Italian centers between 1994 and 2018 and presenting an episode of PRES, we retrospectively identified and analyzed a subgroup of patients who developed epilepsy and MTS. RESULTS: Nine of 70 patients (12.8%) developed post-PRES persistent seizures with magnetic resonance imaging evidence of MTS. One patient died few months after MTS diagnosis, because of hematologic complications; the remaining 8 patients showed unprovoked seizures over time leading to the diagnosis of epilepsy, focal in all and drug resistant in 4. At PRES diagnosis, all patients with further evidence of epilepsy and MTS suffered of convulsive seizures, evolving into status epilepticus in 3. In 3 patients a borderline cognitive level or intellectual disability were diagnosed after the onset of epilepsy, and 2 had behavioral problems impacting their quality of life. CONCLUSIONS: MTS and long-term focal epilepsy, along with potential cognitive and behavioral disorders, are not uncommon in older pediatric patients following PRES.

ImmunoPET imaging of hematological malignancies: From preclinical promise to clinical reality.

Immuno-positron emission tomography (immunoPET) imaging is a paradigm-shifting imaging technique for whole-body and all-lesion tumor detection, based on the combined specificity of tumor-targeting vectors [e.g., monoclonal antibodies (mAbs), nanobodies, and bispecific antibodies] and the sensitivity of PET imaging. By noninvasively, comprehensively, and serially revealing heterogeneous tumor antigen expression, immunoPET imaging is gradually improving the theranostic prospects for hematological malignancies. In this review, we summarize the available literature regarding immunoPET in imaging hematological malignancies. We also highlight the pros and cons of current conjugation strategies, and modular chemistry that can be leveraged to develop novel immunoPET probes for hematological malignancies. Lastly, we discuss the use of immunoPET imaging in guiding antibody drug development.