Positron-emission tomography and assessment of cancer therapy

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning

Objective

Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT).

Materials and methods

Several deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes.

Results

Amongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network.

Conclusion

Deep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism.

Improvement of motion artifacts using dynamic whole-body 18F-FDG PET/CT imaging

PURPOSE

Serial dynamic whole-body PET imaging is valuable for assessing serial changes in tracer uptake. The purpose of this study was to evaluate the improvement of motion artifacts in patients using serial dynamic whole-body 18F-fluorodeoxyglyucose (FDG) PET/CT imaging.

MATERIALS AND METHODS

In 797 consecutive patients, serial 3-min dynamic whole-body FDG PET imaging was performed seven times, at 60 or 90 min after FDG administration. In cases with large body motion during imaging, we tried to improve the images by summing the images before body motion. An image quality study was performed on another 50 patients without obvious body motion using the same acquisition mode.

RESULTS

Obvious body movement was observed in 106 of 797 cases (13.3%), and severe motion artifacts which interfered image interpretation were observed in 18 (2.3%). In these 18 cases, summation of the images before the body movement enabled us to obtain images that excluded the effect of the body motion. In the visual evaluation of the image quality in another 50 patients studied, acceptable image quality was obtained when 2 or more times the serial 3-min image data were added.

CONCLUSION

Serial dynamic whole-body FDG PET imaging can minimize body motion artifacts by summation of the images before the body motion. Such serial dynamic study may be a choice for PET imaging to eliminate motion artifacts.

Evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[18F]FDG PET/CT between 2007 and 2021

OBJECTIVES

To evaluate the evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[18F]fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET/CT between 2007 and 2021.

METHODS AND MATERIALS

Data from all pediatric patients aged 0-18 years who underwent hybrid 2-[18F]FDG PET/CT of the body between January 2007 and May 2021 were reviewed. Demographic and imaging parameters were collected. A board-certified radiologist reviewed all CT scans and measured image noise in the brain, liver, and adductor muscles.

RESULTS

294 scans from 167 children (72 females (43%); median age: 14 (IQR 10-15) years; BMI: median 17.5 (IQR 15-20.4) kg/m2) were included. CT dose index-volume (CTDIvol) and dose length product (DLP) both decreased significantly from 2007 to 2021 (both p < 0.001, Spearman's rho coefficients -0.46 and -0.35, respectively). Specifically, from 2007 to 2009 to 2019-2021 CTDIvol and DLP decreased from 2.94 (2.14-2.99) mGy and 309 (230-371) mGy*cm, respectively, to 0.855 (0.568-1.11) mGy and 108 (65.6-207) mGy*cm, respectively. From 2007 to 2021, image noise in the brain and liver remained constant (p = 0.26 and p = 0.06), while it decreased in the adductor muscles (p = 0.007). Peak tube voltage selection (in kilovolt, kV) of CT scans shifted from high kV imaging (140 or 120kVp) to low kV imaging (100 or 80kVp) (p < 0.001) from 2007 to 2021.

CONCLUSION

CT radiation dose in pediatric patients undergoing hybrid 2-[18F]FDG PET/CT has decreased in recent years equaling approximately one-third of the initial amount.

ADVANCES IN KNOWLEDGE

Over the past 15 years, CT radiation dose decreased considerably in pediatric patients undergoing hybrid imaging, while objective image quality may not have been compromised.

Prognostic role of preoperative fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography with an image-based harmonization technique: A multicenter retrospective study

Objectives

Despite the prognostic impacts of preoperative fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography examination, fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography-based prognosis prediction has not been used clinically because of the disparity in data between institutions. By applying an image-based harmonized approach, we evaluated the prognostic roles of fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters in clinical stage I non-small cell lung cancer.

Methods

We retrospectively examined 495 patients with clinical stage I non-small cell lung cancer who underwent fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography examinations before pulmonary resection between 2013 and 2014 at 4 institutions. Three different harmonization techniques were applied, and an image-based harmonization, which showed the best-fit results, was used in the further analyses to evaluate the prognostic roles of fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters.

Results

Cutoff values of image-based harmonized fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters, maximum standardized uptake, metabolic tumor volume, and total lesion glycolysis were determined using receiver operating characteristic curves that distinguish pathologic high invasiveness of tumors. Among these parameters, only the maximum standardized uptake was an independent prognostic factor in recurrence-free and overall survivals in univariate and multivariate analyses. High image-based maximum standardized uptake value was associated with squamous histology or lung adenocarcinomas with higher pathologic grades. In subgroup analyses defined by ground-glass opacity status and histology or by clinical stages, the prognostic impact of image-based maximum standardized uptake value was always the highest compared with other fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters.

Conclusions

The image-based fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography harmonization was the best fit, and the image-based maximum standardized uptake was the most important prognostic marker in all patients and in subgroups defined by ground-glass opacity status and histology in surgically resected clinical stage I non-small cell lung cancers.

Four-dimensional quantitative analysis using FDG-PET in clinical oncology

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) has been commonly used in many oncological areas. High-resolution PET permits a three-dimensional analysis of FDG distributions on various lesions in vivo, which can be applied for tissue characterization, risk analysis, and treatment monitoring after chemoradiotherapy and immunotherapy. Metabolic changes can be assessed using the tumor absolute FDG uptake as standardized uptake value (SUV) and metabolic tumor volume (MTV). In addition, tumor heterogeneity assessment can potentially estimate tumor aggressiveness and resistance to chemoradiotherapy. Attempts have been made to quantify intratumoral heterogeneity using radiomics. Recent reports have indicated the clinical feasibility of a dynamic FDG PET-computed tomography (CT) in pilot cohort studies of oncological cases. Dynamic imaging permits the assessment of temporal changes in FDG uptake after administration, which is particularly useful for differentiating pathological from physiological uptakes with high diagnostic accuracy. In addition, several new parameters have been introduced for the in vivo quantitative analysis of FDG metabolic processes. Thus, a four-dimensional FDG PET-CT is available for precise tissue characterization of various lesions. This review introduces various new techniques for the quantitative analysis of FDG distribution and glucose metabolism using a four-dimensional FDG analysis with PET-CT. This elegant study reveals the important role of tissue characterization and treatment strategies in oncology.

18F-fluorodeoxyglucose positron emission tomography findings of peripheral nerve sheath tumour of the nasal cavity in a dog

An 8-year-old Miniature Poodle presented with chronic sneezing and unilateral epistaxis. A left-sided intranasal mass was identified on computed tomography. 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) was performed to evaluate the metabolic activity of the mass. The intranasal mass showed mildly increased 18F-FDG uptake. The maximal and mean standardized uptake values (SUVs) of the mass were 3.4 and 2.6, respectively. The maximal SUV of the mass/mean SUV of the normal liver was 2.5. The 7-cm soft, pink mass was easily removed through rhinoscopy, with subsequent dramatic improvement in clinical signs. Histopathological and immunohistochemical analyses determined that the mass was an intermediate-grade malignant peripheral nerve sheath tumour (PNST). This is the first report of 18F-FDG PET findings in a PNST in dogs.

Tailoring the clinical management of colorectal cancer by 18F-FDG PET/CT

Colorectal cancer (CRC) is among the most commonly diagnosed gastrointestinal malignancies worldwide. It is inadequate to handle in terms of staging and restaging only based on morphological imaging modalities and serum surrogate markers. And the correct and timely staging of CRC is imperative to prognosis and management. When compared to established sequential, multimodal conventional diagnostic methods, the molecular and functional imaging ¹⁸F-FDG PET/CT shows superiorities for tailoring appropriate treatment maneuvers to each patient. This review aims to summarize the utilities of ¹⁸F-FDG PET/CT in CRC, focusing on primary staging, follow-up assessment of tumor responses and diagnostic of recurrence. In addition, we also summarize the technical considerations of PET/CT and the conventional imaging modalities in those patients who are either newly diagnosed with CRC or has already been treated from this cancer.

Novel Chelating Agents for Zirconium-89-Positron Emission Tomography (PET) Imaging: Synthesis, DFT Calculation, Radiolabeling, and In Vitro and In Vivo Complex Stability

We report the synthesis and evaluation of novel chelating agents for zirconium-89 (⁸⁹Zr) with positron emission tomography (PET) imaging applications. New chelating agents NODHA, NOTHA, and NODHA-PY were constructed on 1,4,7-triazacyclononane (TACN) and possess hydroxamic acid or a pyridine ring as an acyclic binding moiety. The new chelating agents were theoretically studied for complexation with Zr(IV). Structures of Zr(IV)-NODHA, Zr(IV)-NOTHA, and Zr(IV)-NODHA-PY were predicted using density functional methods. NODHA was found to form stronger bonds with Zr(IV) when compared to NOTHA and NODHA-PY. The new chelating agents were evaluated for radiolabeling efficiency in binding ⁸⁹Zr. The corresponding [⁸⁹Zr]Zr-labeled chelators were evaluated for complex stability in human serum. All new chelating agents rapidly bound to ⁸⁹Zr in excellent radiolabeling efficiency at room temperature. Among the new [⁸⁹Zr]Zr-labeled chelators evaluated, [⁸⁹Zr]Zr-NODHA showed the highest stability in human serum without losing ⁸⁹Zr, and [⁸⁹Zr]Zr-NODHA-PY released a considerable amount of ⁸⁹Zr in human serum. [⁸⁹Zr]Zr-NODHA, [⁸⁹Zr]Zr-NODHA-PY, and [⁸⁹Zr]Zr-DFO were comparatively evaluated for in vivo complex stability by performing biodistribution studies using normal mice. [⁸⁹Zr]Zr-DFO had the lowest bone uptake at all time points, while [⁸⁹Zr]Zr-NODHA-PY showed poor stability in mice as evidenced by high bone accumulation at the 24 h time point. [⁸⁹Zr]Zr-NODHA exhibited better renal clearance but higher bone uptake than [⁸⁹Zr]Zr-DFO.

Solid-State NMR 19F-1H-15N Correlation Experiments for Resonance Assignment and Distance Measurements of Multifluorinated Proteins

Several solid-state NMR techniques have been introduced recently to measure nanometer distances involving 19F, whose high gyromagnetic ratio makes it a potent nuclear spin for structural investigation. These solid-state NMR techniques either use 19F correlation with 1H or 13C to obtain qualitative interatomic contacts or use the rotational-echo double-resonance (REDOR) pulse sequence to measure quantitative distances. However, no NMR technique is yet available for disambiguating 1H-19F distances in multiply fluorinated proteins and protein-ligand complexes. Here, we introduce a three-dimensional (3D) 19F-15N-1H correlation experiment that resolves the distances of multiple fluorines to their adjacent amide protons. We show that optimal polarization transfer between 1H and 19F spins is achieved using an out-and-back 1H-19F REDOR sequence. We demonstrate this 3D correlation experiment on the model protein GB1 and apply it to the multidrug-resistance transporter, EmrE, complexed to a tetrafluorinated substrate. This technique should be useful for resolving and assigning distance constraints in multiply fluorinated proteins, leading to significant savings of time and precious samples compared to producing several singly fluorinated samples. Moreover, the method enables structural determination of protein-ligand complexes for ligands that contain multiple fluorines.

Can Dynamic Whole-Body FDG PET Imaging Differentiate between Malignant and Inflammatory Lesions?

Background: Investigation of the clinical feasibility of dynamic whole-body (WB) [18F]FDG PET, including standardized uptake value (SUV), rate of irreversible uptake (Ki), and apparent distribution volume (Vd) in physiologic tissues, and comparison between inflammatory/infectious and cancer lesions. Methods: Twenty-four patients were prospectively included to undergo dynamic WB [18F]FDG PET/CT for clinically indicated re-/staging of oncological diseases. Parametric maps of Ki and Vd were generated using Patlak analysis alongside SUV images. Maximum parameter values (SUVmax, Kimax, and Vdmax) were measured in liver parenchyma and in malignant or inflammatory/infectious lesions. Lesion-to-background ratios (LBRs) were calculated by dividing the measurements by their respective mean in the liver tissue. Results: Seventy-seven clinical target lesions were identified, 60 malignant and 17 inflammatory/infectious. Kimax was significantly higher in cancer than in inflammatory/infections lesions (3.0 vs. 2.0, p = 0.002) while LBRs of SUVmax, Kimax, and Vdmax did not differ significantly between the etiologies: LBR (SUVmax) 3.3 vs. 2.9, p = 0.06; LBR (Kimax) 5.0 vs. 4.4, p = 0.05, LBR (Vdmax) 1.1 vs. 1.0, p = 0.18). LBR of inflammatory/infectious and cancer lesions was higher in Kimax than in SUVmax (4.5 vs. 3.2, p < 0.001). LBRs of Kimax and SUVmax showed a strong correlation (Spearman’s rho = 0.83, p < 0.001). Conclusions: Dynamic WB [18F]FDG PET/CT is feasible in a clinical setting. LBRs of Kimax were higher than SUVmax. Kimax was higher in malignant than in inflammatory/infectious lesions but demonstrated a large overlap between the etiologies.

Prognostic Evaluation Based on Dual-Time 18F-FDG PET/CT Radiomics Features in Patients with Locally Advanced Pancreatic Cancer Treated by Stereotactic Body Radiation Therapy

Background

¹⁸F-FDG PET/CT is widely used in the prognosis evaluation of tumor patients. The radiomics features can provide additional information for clinical prognostic assessment.

Purpose

Purpose is to explore the prognostic value of radiomics features from dual-time ¹⁸F-FDG PET/CT images for locally advanced pancreatic cancer (LAPC) patients treated with stereotactic body radiation therapy (SBRT).

Materials and Methods

This retrospective study included 70 LAPC patients who received early and delayed ¹⁸F-FDG PET/CT scans before SBRT treatment. A total of 1188 quantitative imaging features were extracted from dual-time PET/CT images. To avoid overfitting, the univariate analysis and elastic net were used to obtain a sparse set of image features that were applied to develop a radiomics score (Rad-score). Then, the Harrell consistency index (C-index) was used to evaluate the prognosis model.

Results

The Rad-score from dual-time images contains six features, including intensity histogram, morphological, and texture features. In the validation cohort, the univariate analysis showed that the Rad-score was the independent prognostic factor (p < 0.001, hazard ratio [HR]: 3.2). And in the multivariate analysis, the Rad-score was the only prognostic factor (p < 0.01, HR: 4.1) that was significantly associated with the overall survival (OS) of patients. In addition, according to cross-validation, the C-index of the prognosis model based on the Rad-score from dual-time images is better than the early and delayed images (0.720 vs. 0.683 vs. 0.583).

Conclusion

The Rad-score based on dual-time ¹⁸F-FDG PET/CT images is a promising noninvasive method with better prognostic value.

Computer-aided detection and segmentation of malignant melanoma lesions on whole-body 18F-FDG PET/CT using an interpretable deep learning approach

BACKGROUND AND OBJECTIVE

In oncology, 18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) / computed tomography (CT) is widely used to identify and analyse metabolically-active tumours. The combination of the high sensitivity and specificity from 18F-FDG PET and the high resolution from CT makes accurate assessment of disease status and treatment response possible. Since cancer is a systemic disease, whole-body imaging is of high interest. Moreover, whole-body metabolic tumour burden is emerging as a promising new biomarker predicting outcome for innovative immunotherapy in different tumour types. However, this comes with certain challenges such as the large amount of data for manual reading, different appearance of lesions across the body and cumbersome reporting, hampering its use in clinical routine. Automation of the reading can facilitate the process, maximise the information retrieved from the images and support clinicians in making treatment decisions.

METHODS

This work proposes a fully automated system for lesion detection and segmentation on whole-body 18F-FDG PET/CT. The novelty of the method stems from the fact that the same two-step approach used when manually reading the images was adopted, consisting of an intensity-based thresholding on PET followed by a classification that specifies which regions represent normal physiological uptake and which are malignant tissue. The dataset contained 69 patients treated for malignant melanoma. Baseline and follow-up scans together offered 267 images for training and testing.

RESULTS

On an unseen dataset of 53 PET/CT images, a median F1-score of 0.7500 was achieved with, on average, 1.566 false positive lesions per scan. Metabolically-active tumours were segmented with a median dice score of 0.8493 and absolute volume difference of 0.2986 ml.

CONCLUSIONS

The proposed fully automated method for the segmentation and detection of metabolically-active lesions on whole-body 18F-FDG PET/CT achieved competitive results. Moreover, it was compared to a direct segmentation approach which it outperformed for all metrics.

PET-Based Radiogenomics Supports mTOR Pathway Targeting for Hepatocellular Carcinoma

PURPOSE

This work aimed to explore in depth the genomic and molecular underpinnings of hepatocellular carcinoma (HCC) with increased 2[18F]fluoro-2-deoxy-d-glucose (FDG) uptake in PET and to identify therapeutic targets based on this imaging-genomic surrogate.

EXPERIMENTAL DESIGN

We used RNA sequencing and whole-exome sequencing data obtained from 117 patients with HCC who underwent hepatic resection with preoperative FDG-PET/CT imaging as a discovery cohort. The primary radiogenomic results were validated with transcriptomes from a second cohort of 81 patients with more advanced tumors. All patients were allocated to an FDG-avid or FDG-non-avid group according to the PET findings. We also screened potential drug candidates targeting FDG-avid HCCs in vitro and in vivo.

RESULTS

High FDG avidity conferred worse recurrence-free survival after HCC resection. Whole transcriptome analysis revealed upregulation of mTOR pathway signals in the FDG-avid tumors, together with higher abundance of associated mutations. These clinical and genomic findings were replicated in the validation set. A molecular signature of FDG-avid HCCs identified in the discovery set consistently predicted poor prognoses in the public-access datasets of two cohorts. Treatment with an mTOR inhibitor resulted in decreased FDG uptake followed by effective tumor control in both the hyperglycolytic HCC cell lines and xenograft mouse models.

CONCLUSIONS

Our PET-based radiogenomic analysis indicates that mTOR pathway genes are markedly activated and altered in HCCs with high FDG retention. This nuclear imaging biomarker may stimulate umbrella trials and tailored treatments in precision care of patients with HCC.

Molecular sensors for detection of tumor-stroma crosstalk

In most solid tumors, malignant cells coexist with non-cancerous host tissue comprised of a variety of extracellular matrix components and cell types, notably fibroblasts, immune cells, and endothelial cells. It is becoming increasingly evident that the non-cancerous host tissue, often referred to as the tumor stroma or the tumor microenvironment, wields tremendous influence in the proliferation, survival, and metastatic ability of cancer cells. The tumor stroma has an active biological role in the transmission of signals, such as growth factors and chemokines that activate oncogenic signaling pathways by autocrine and paracrine mechanisms. Moreover, the constituents of the stroma define the mechanical properties and the physical features of solid tumors, which influence cancer progression and response to therapy. Inspired by the emerging importance of tumor-stroma crosstalk and oncogenic physical forces, numerous biosensors, or advanced imaging and analysis techniques have been developed and applied to investigate complex and challenging questions in cancer research. These techniques facilitate measurements and biological readouts at scales ranging from subcellular to tissue-level with unprecedented level of spatial and temporal precision. Here we examine the application of biosensor technology for studying the complex and dynamic multiscale interactions of the tumor-host system.

Prediction of pathological response using 18F FDG PET/CT derived metabolic parameters in locally advanced breast cancer patients

AIM OF WORK

This study aims to assess the value of flurodeoxyglucose (FDG)-PET derived metabolic parameters for prediction of pathologic response in LABC postneoadjuvant therapy.

METHODS

Totally 47 patients with LABC underwent initial and postneoadjuvant therapy PET scans. ΔSUVmax%, ΔTLG% and ΔMTV% were calculated. Post-therapy histopathologic therapeutic response was assessed.

RESULTS

In total 91.5% of patients had invasive duct carcinoma and the remaining (8.5%) had invasive lobular carcinoma. Postneoadjuvant PET/CT was able to detect 91.7% of patients with pathologically proven complete response in primary tumor, 69% of those with Pathologic partial response and 88.3% of those with pathological no response (P value <0.001). However, 40 out of the 47 patients had regional nodal metastases. PET/CT was able to predict 57.1% of the patients with pathologically nonresponding nodal deposits and 93.9% of those revealed pathologic therapeutic effect (P value <0.001). Receiver operating characteristic curve (ROC) curve marked Δ1ry SUVmax of 26.25% (P value 0.003), Δ1ry TLG of 48.5% (P value 0.018). PET and pathological response correlated well with ΔSUVmax%, and Δ1ry TLG% correlated well with PET, pathologic response and expression of HER II receptors (P value <0.001, 0.003 and 0.037 respectively). ROC curve marked ΔLN SUVmax% of 80.15% (P value 0.012), ΔLN TLG% of 86.6% (P value 0.002), whereas for ΔLN MTV% cut off point of 55% (P value 0.003). ΔSUVmax%, ΔTLG % and ΔMTV% for regional nodal metastases, were significantly correlated with PET (P values <0.001, <0.001 and 0.003, respectively) and pathologic (P values 0.018, 0.001 and 0.002, respectively) response.

CONCLUSION

FDG-PET is a useful tool for monitoring the neoadjuvant therapeutic effect for primary and regional nodes in patients with LABC.

Ketogenic diet and chemotherapy combine to disrupt pancreatic cancer metabolism and growth

Background

Ketogenic diet is a potential means of augmenting cancer therapy. Here, we explore ketone body metabolism and its interplay with chemotherapy in pancreatic cancer.

Methods

Metabolism and therapeutic responses of murine pancreatic cancer were studied using KPC primary tumors and tumor chunk allografts. Mice on standard high-carbohydrate diet or ketogenic diet were treated with cytotoxic chemotherapy (nab-paclitaxel, gemcitabine, cisplatin). Metabolic activity was monitored with metabolomics and isotope tracing, including 2H- and 13C-tracers, liquid chromatography-mass spectrometry, and imaging mass spectrometry.

Findings

Ketone bodies are unidirectionally oxidized to make NADH. This stands in contrast to the carbohydrate-derived carboxylic acids lactate and pyruvate, which rapidly interconvert, buffering NADH/NAD. In murine pancreatic tumors, ketogenic diet decreases glucose's concentration and tricarboxylic acid cycle contribution, enhances 3-hydroxybutyrate's concentration and tricarboxylic acid contribution, and modestly elevates NADH, but does not impact tumor growth. In contrast, the combination of ketogenic diet and cytotoxic chemotherapy substantially raises tumor NADH and synergistically suppresses tumor growth, tripling the survival benefits of chemotherapy alone. Chemotherapy and ketogenic diet also synergize in immune-deficient mice, although long-term growth suppression was only observed in mice with an intact immune system.

Conclusions

Ketogenic diet sensitizes murine pancreatic cancer tumors to cytotoxic chemotherapy. Based on these data, we have initiated a randomized clinical trial of chemotherapy with standard versus ketogenic diet for patients with metastatic pancreatic cancer (NCT04631445).

Dynamic whole-body FDG-PET imaging for oncology studies

Introduction

Recent PET/CT systems have improved sensitivity and spatial resolution by smaller PET detectors and improved reconstruction software. In addition, continuous-bed-motion mode is now available in some PET systems for whole-body PET imaging. In this review, we describe the advantages of dynamic whole-body FDG-PET in oncology studies.

Methods

PET–CT imaging was obtained at 60 min after FDG administration. Dynamic whole-body imaging with continuous bed motion in 3 min each with flow motion was obtained over 400 oncology cases. For routine image analysis, these dynamic phases (usually four phases) were summed as early FDG imaging. The image quality of each serial dynamic imaging was visually evaluated. In addition, changes in FDG uptake were analyzed in consecutive dynamic imaging and also in early delayed (90 min after FDG administration) time point imaging (dual-time-point imaging; DTPI). Image interpretation was performed by consensus of two nuclear medicine physicians.

Result

All consecutive dynamic whole-body PET images of 3 min duration had acceptable image quality. Many of the areas with physiologically high FDG uptake had altered uptake on serial images. On the other hand, most of the benign and malignant lesions did not show visual changes on serial images. In the study of 60 patients with suspected colorectal cancer, unchanged uptake was noted in almost all regions with pathologically proved FDG uptake, indicating high sensitivity with high negative predictive value on both serial dynamic imaging and on DTPI. We proposed another application of serial dynamic imaging for minimizing motion artifacts for patients who may be likely to move during PET studies.

Discussion

Dynamic whole-body imaging has several advantages over the static imaging. Serial assessment of changes in FDG uptake over a short period of time is useful for distinguishing pathological from physiological uptake, especially in the abdominal regions. These dynamic PET studies may minimize the need for DPTI. In addition, continuous dynamic imaging has the potential to reduce motion artifacts in patients who are likely to move during PET imaging. Furthermore, kinetic analysis of the FDG distribution in tumor areas has a potential for precise tissue characterization.

Conclusion

Dynamic whole-body FDG-PET imaging permits assessment of serial FDG uptake change which is particularly useful for differentiation of pathological uptake from physiological uptake with high diagnostic accuracy. This imaging can be applied for minimizing motion artifacts. Wide clinical applications of such serial, dynamic whole-body PET imaging is expected in oncological studies in the near future.

Machine learning in neuroimaging: from research to clinical practice

Neuroimaging is critical in clinical care and research, enabling us to investigate the brain in health and disease. There is a complex link between the brain's morphological structure, physiological architecture, and the corresponding imaging characteristics. The shape, function, and relationships between various brain areas change during development and throughout life, disease, and recovery. Like few other areas, neuroimaging benefits from advanced analysis techniques to fully exploit imaging data for studying the brain and its function. Recently, machine learning has started to contribute (a) to anatomical measurements, detection, segmentation, and quantification of lesions and disease patterns, (b) to the rapid identification of acute conditions such as stroke, or (c) to the tracking of imaging changes over time. As our ability to image and analyze the brain advances, so does our understanding of its intricate relationships and their role in therapeutic decision-making. Here, we review the current state of the art in using machine learning techniques to exploit neuroimaging data for clinical care and research, providing an overview of clinical applications and their contribution to fundamental computational neuroscience.

Advancements in diagnostic techniques for oral cancer detection

Oral malignancy is among the highest prevalent malignancies all over the world. In comparison to systemic malignancies such as lung cancer and colon cancer, they are frequently overlooked by the general public. Nevertheless, they can be exceedingly lethal if left ignored, regardless at the early stage of the condition. Dentists are the finest qualified healthcare specialists in this sector and are responsible for detecting benign and potentially malignant oral conditions such as oral cancers. Oral carcinoma's high prevalence and delayed appearance are serious international medical concerns. Early detection and management of oral carcinoma are the key goals of the World Health Organization (WHO). The identification of key clinical manifestations during the preliminary oral examination can enhance the patient's likelihood of living. Unfortunately, the conventional technology's practical value is limited by a number of drawbacks. Current advancements in optical scanning techniques, such as tissue-fluorescence imaging and optical coherence tomography, have proven to be quite effective. In particular, nanoparticle-based immunosensors, genomics, and salivary biomarkers, epigenetics and microarray have all received a lot of attention. Raising awareness about frequent dental examinations and using noninvasive, effective, and cost-effective screening tools would improve initial stage detection of oral carcinoma and improve patients' longevity.

Improved post-ASCT survival of relapsed/refractory classical Hodgkin lymphoma patients in the era of novel agents

Utilization of novel agents such as brentuximab vedotin (BV) and check-point inhibitors (CI) has increased in patients with relapsed/refractory (r/r) classical Hodgkin Lymphoma (cHL). We conducted a retrospective study of 209 patients who had ASCT for r/r cHL at our institution and compared outcomes of those who had ASCT from 2010-2018 (cohort 2, n = 110) with those who had ASCT between 2000 and 2009 (cohort 1, n = 99). The median OS was 7.6 years for cohort 1 [HR 2.08; 95% CI 1.14-3.80; p = 0.017] and not reached for cohort 2; with 4-year improved OS difference of 15% (80% vs 65%) in cohort 2 vs cohort 1. The median PFS of cohort 1 was 30 months vs 39 months for cohort 2[HR 1.24; 95% CI 0.82-1.88; p = 0.3]. This study highlights improved OS of r/r cHL patients who have received ASCT in the novel agent era due to the exposure to agents such as BV and CIs.

Radionuclide-Based Imaging of Breast Cancer: State of the Art

Simple Summary

Breast cancer is one of the most commonly diagnosed malignant tumors, possessing high incidence and mortality rates that threaten women’s health. Thus, early and effective breast cancer diagnosis is crucial for enhancing the survival rate. Radionuclide molecular imaging displays its advantages for detecting breast cancer from a functional perspective. Noninvasive visualization of biological processes with radionuclide-labeled small metabolic compounds helps elucidate the metabolic state of breast cancer, while radionuclide-labeled ligands/antibodies for receptor-targeted radionuclide molecular imaging is sensitive and specific for visualization of the overexpressed molecular markers in breast cancer. This review focuses on the most recent developments of novel radiotracers as promising tools for early breast cancer diagnosis.

Abstract

Breast cancer is a malignant tumor that can affect women worldwide and endanger their health and wellbeing. Early detection of breast cancer can significantly improve the prognosis and survival rate of patients, but with traditional anatomical imagine methods, it is difficult to detect lesions before morphological changes occur. Radionuclide-based molecular imaging based on positron emission tomography (PET) and single-photon emission computed tomography (SPECT) displays its advantages for detecting breast cancer from a functional perspective. Radionuclide labeling of small metabolic compounds can be used for imaging biological processes, while radionuclide labeling of ligands/antibodies can be used for imaging receptors. Noninvasive visualization of biological processes helps elucidate the metabolic state of breast cancer, while receptor-targeted radionuclide molecular imaging is sensitive and specific for visualization of the overexpressed molecular markers in breast cancer, contributing to early diagnosis and better management of cancer patients. The rapid development of radionuclide probes aids the diagnosis of breast cancer in various aspects. These probes target metabolism, amino acid transporters, cell proliferation, hypoxia, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), gastrin-releasing peptide receptor (GRPR) and so on. This article provides an overview of the development of radionuclide molecular imaging techniques present in preclinical or clinical studies, which are used as tools for early breast cancer diagnosis.

Advances in the treatment, diagnosis, control and scientific understanding of taeniid cestode parasite infections over the past 50 years

In the past 50 years, enormous progress has been made in the diagnosis, treatment and control of taeniid cestode infections/diseases and in the scientific understanding thereof. Most interest in this group of parasites stems from the serious diseases that they cause in humans. It is through this lens that we summarize here the most important breakthroughs that have made a difference to the treatment of human diseases caused by these parasites, reduction in transmission of the taeniid species associated with human disease, or understanding of the parasites' biology likely to impact diagnosis or treatment in the foreseeable future. Key topics discussed are the introduction of anti-cestode drugs, including benzimidazoles and praziquantel, and the development of new imaging modalities that have transformed the diagnosis and post-treatment monitoring of human echinococcoses and neurocysticercosis. The availability of new anti-cestode drugs for use in dogs and a detailed understanding of the transmission dynamics of Echinococcus granulosus sensu lato have underpinned successful programs that have eliminated cystic echinococcosis in some areas of the world and greatly reduced the incidence of infection in others. Despite these successes, cystic and alveolar echinococcosis and neurocysticercosis continue to be prevalent in many parts of the world, requiring new or renewed efforts to prevent the associated taeniid infections. Major advances made in the development of practical vaccines against E. granulosus and Taenia solium will hopefully assist in this endeavour, as might the understanding of the parasites' biology that have come from an elucidation of the nuclear genomes of each of the most important taeniid species causing human diseases.

A grant-based experiment to train clinical investigators: the AACR/ASCO methods in clinical cancer research workshop

To address the need for clinical investigators in oncology, AACR and ASCO established the Methods in Clinical Cancer Research Workshop (MCCRW). The workshop's objectives were to: (1) provide training in the methods, design, and conduct of clinical trials; (2) ensure that clinical trials met federal and international ethical guidelines; (3) evaluate the effectiveness of the workshop; and (4) create networking opportunities for young investigators with mentoring senior faculty. Educational methods included: (1) didactic lectures; (2) Small Group Discussion Sessions; (3) Protocol Development Groups; (4) one-on-one mentoring. Learning focused on the development of an IRB-ready protocol, which was submitted on the last day of the workshop. Evaluation methods included: (1) pre- and post-workshop tests; (2) students' workshop evaluations; (3) faculty's ratings of protocol development; (4) students' productivity in clinical research after the workshop; (5) an independent assessment of the workshop. From 1996-2014, 1932 students from diverse backgrounds attended the workshop. There was a significant improvement in the students' level of knowledge from the pre- to the post-workshop exams (p < 0.001). Across the classes, student evaluations were very favorable. At the end of the workshop, faculty rated 92-100% of the students' protocols as ready for IRB submission. Intermediate and long-term follow-ups indicated that more than 92% of students were actively involved in patientrelated research, and 66% had implemented five or more protocols. This NCI-sponsored MCCRW has had a major impact on the training of clinicians in their ability to design and implement clinical trials in cancer research.

Positron emission tomography/computed tomography in the management of Hodgkin and B-cell non-Hodgkin lymphoma: An update

¹⁸ F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is now an integral part of lymphoma staging and management. Because of its greater accuracy compared with CT alone, PET/CT is currently routinely performed for staging and for response assessment at the end of treatment in the vast majority of FDG-avid lymphomas and is the cornerstone of response classification for these lymphomas according to the Lugano classification. Interim PET/CT, typically performed after 2 to 4 of 6 to 8 chemotherapy/chemoimmunotherapy cycles with or without radiation, is commonly performed for prognostication and potential treatment escalation or de-escalation early in the course of therapy, a concept known as response-adapted or risk-adapted treatment. Quantitative PET is an area of growing interest. Metrics, such as the standardized uptake value, changes (Δ) in the standardized uptake value, metabolic tumor volume, and total lesion glycolysis, are being investigated as more reproducible and potentially more accurate predictors of response and prognosis. Despite the progress made in standardizing the use of PET/CT in lymphoma, challenges remain, particularly with respect to its limited positive predictive value, emphasizing the need for more specific molecular probes. This review highlights the most relevant applications of PET/CT in Hodgkin and B-cell non-Hodgkin lymphoma, its strengths and limitations, as well as recent efforts at implementing PET/CT-based metrics as promising tools for precision medicine.

Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning

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Textural and second derivative textural features of CT images can be used in conjunction with machine learning models to predict breast cancer response to chemotherapy prior to the start of treatment.

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The proposed predictive model separates the patients at pre-treatment into two cohorts (responders/non-responders) with significantly different survival.

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The proposed methodology is a step forward towards the precision oncology paradigm for breast cancer patients.

Although neoadjuvant chemotherapy (NAC) is a crucial component of treatment for locally advanced breast cancer (LABC), only about 70% of patients respond to it. Effective adjustment of NAC for individual patients can significantly improve survival rates of those resistant to standard regimens. Thus, the early prediction of NAC outcome is of great importance in facilitating a personalized paradigm for breast cancer therapeutics. In this study, quantitative computed tomography (qCT) parametric imaging in conjunction with machine learning techniques were investigated to predict LABC tumor response to NAC. Textural and second derivative textural (SDT) features of CT images of 72 patients diagnosed with LABC were analysed before the initiation of NAC to quantify intra-tumor heterogeneity. These quantitative features were processed through a correlation-based feature reduction followed by a sequential feature selection with a bootstrap 0.632+ area under the receiver operating characteristic (ROC) curve (AUC0.632+) criterion. The best feature subset consisted of a combination of one textural and three SDT features. Using these features, an AdaBoost decision tree could predict the patient response with a cross-validated AUC0.632+ accuracy, sensitivity and specificity of 0.88, 85%, 88% and 75%, respectively. This study demonstrates, for the first time, that a combination of textural and SDT features of CT images can be used to predict breast cancer response NAC prior to the start of treatment which can potentially facilitate early therapy adjustments.

Differentiation between non-small cell lung cancer and radiation pneumonitis after carbon-ion radiotherapy by 18F-FDG PET/CT texture analysis

The differentiation of non-small cell lung cancer (NSCLC) and radiation pneumonitis (RP) is critically essential for selecting optimal clinical therapeutic strategies to manage post carbon-ion radiotherapy (CIRT) in patients with NSCLC. The aim of this study was to assess the ability of ¹⁸F-FDG PET/CT metabolic parameters and its textural image features to differentiate NSCLC from RP after CIRT to develop a differential diagnosis of malignancy and benign lesion. We retrospectively analyzed ¹⁸F-FDG PET/CT image data from 32 patients with histopathologically proven NSCLC who were scheduled to undergo CIRT and 31 patients diagnosed with RP after CIRT. The SUV parameters, metabolic tumor volume (MTV), total lesion glycolysis (TLG) as well as fifty-six texture parameters derived from seven matrices were determined using PETSTAT image-analysis software. Data were statistically compared between NSCLC and RP using Wilcoxon rank-sum tests. Diagnostic accuracy was assessed using receiver operating characteristics (ROC) curves. Several texture parameters significantly differed between NSCLC and RP (p < 0.05). The parameters that were high in areas under the ROC curves (AUC) were as follows: SUV_max, 0.64; GLRLM run percentage, 0.83 and NGTDM coarseness, 0.82. Diagnostic accuracy was improved using GLRLM run percentage or NGTDM coarseness compared with SUV_max (p < 0.01). The texture parameters of ¹⁸F-FDG uptake yielded excellent outcomes for differentiating NSCLC from radiation pneumonitis after CIRT, which outperformed SUV-based evaluation. In particular, GLRLM run percentage and NGTDM coarseness of ¹⁸F-FDG PET/CT images would be appropriate parameters that can offer high diagnostic accuracy.

Metabolic Control of Epilepsy: A Promising Therapeutic Target for Epilepsy

Epilepsy is a common neurological disease that is not always controlled, and the ketogenic diet shows good antiepileptic effects drug-resistant epilepsy or seizures caused by specific metabolic defects via regulating the metabolism. The brain is a vital organ with high metabolic demands, and epileptic foci tend to exhibit high metabolic characteristics. Accordingly, there has been growing interest in the relationship between brain metabolism and epilepsy in recent years. To date, several new antiepileptic therapies targeting metabolic pathways have been proposed (i.e., inhibiting glycolysis, targeting lactate dehydrogenase, and dietary therapy). Promising strategies to treat epilepsy via modulating the brain's metabolism could be expected, while a lack of thorough understanding of the role of brain metabolism in the control of epilepsy remains. Herein, this review aims to provide insight into the state of the art concerning the brain's metabolic patterns and their association with epilepsy. Regulation of neuronal excitation via metabolic pathways and antiepileptic therapies targeting metabolic pathways are emphasized, which could provide a better understanding of the role of metabolism in epilepsy and could reveal potential therapeutic targets.

An Exposition of 11C and 18F Radiotracers Synthesis for PET Imaging

The development of new radiolabeled Positron emission tomography tracers has been extensively utilized to access the increasing diversity in the research process and to facilitate the development in research methodology, clinical usage of drug discovery and patient care. Recent advances in radiochemistry, as well as the latest techniques in automated radio-synthesizer, have encouraged and challenged the radiochemists to produce the routinely developed radiotracers. Various radionuclides like 18F, 11C, 15O, 13N 99mTc, 131I, 124I and 64Cu are used for incorporating into different chemical scaffolds; among them, 18F and 11C tagged radiotracers are mostly explored such as 11C-Methionine, 11C-Choline, 18F-FDG, 18F-FLT, and 18F-FES. This review is focused on the development of radiochemistry routes to synthesize different radiotracers of 11C and 18F for clinical studies.

Paying attention to tumor blood vessels: Cancer phototherapy assisted with nano delivery strategies

Cancer phototherapy has attracted increasing attention for its promising effectiveness and relative non-invasiveness. Over the past years, tremendous efforts have been made to develop better phototherapy strategies with various nano delivery systems. This review introduces cancer phototherapy strategies based on tumor blood vessels for improved therapeutic outcomes from the angle of direct tumor destruction and improved delivery process assisted with nano delivery designs. Latest directions and ideas of cancer phototherapy with translation potential are also discussed. Focusing on the double role of tumor vessels not only as an anti-tumor target but also as part of the delivery process, we highlight the crosstalk between photo-induced extensive effects and the complicated drug delivery process. Due to the heterogeneity of tumors, deeper investigations about the interconnection between tumor vessels and cancer phototherapy remain to be carried out. More delicate and intelligent nano delivery systems are expected to help realize the full potential of this therapeutic strategy.

Is It Time to Introduce PET/CT in Colon Cancer Guidelines?

International colon cancer guidelines suggest F-FDG PET/CT in a few circumstances: (1) at disease presentation in case of suspected or proven metastatic synchronous adenocarcinoma; (2) in the workup of recurrent colon cancer with metachronous metastases documented by CT, MRI, or biopsy and in case of serial CEA elevation with negative colonoscopy and negative CT; and (3) in case of contraindication to iodine- and gadolinium-based contrast agents. However, review of the literature has shown that PET/CT can also be used in other scenarios with significant levels of diagnostic advantage. This review aims to emphasize differences between guidelines and scientific literature for the use of PET/CT in colon cancer.

Design and Synthesis of a Novel NIR Celecoxib-Based Fluorescent Probe for Cyclooxygenase-2 Targeted Bioimaging in Tumor Cells

Cyclooxygenase-2 (COX-2) imaging agents are potent tools for early cancer diagnosis. Almost all of the COX2 imaging agents using celecoxib as backbone were chemically modified in the position of N-atom in the sulfonamide group. Herein, a novel COX-2 probe (CCY-5) with high targeting ability and a near-infrared wavelength (achieved by attaching a CY-5 dye on the pyrazole ring of celecoxib using a migration strategy) was evaluated for its ability to probe COX-2 in human cancer cells. CCY-5 is expected to have high binding affinity for COX-2 based on molecular docking and enzyme inhibition assay. Meanwhile, CCY-5 caused stronger fluorescence imaging of COX-2 overexpressing cancer cells (Hela and SCC-9 cells) than that of normal cell lines (RAW 264.7 cells). Lipopolysaccharide (LPS) treated RAW264.7 cells revealed an enhanced fluorescence as LPS was known to induce COX-2 in these cells. In inhibitory studies, a markedly reduced fluorescence intensity was observed in cancer cells, when they were co-treated with a COX-2 inhibitor celecoxib. Therefore, CCY-5 may be a selective bioimaging agent for cancer cells overexpressing COX-2 and could be useful as a good monitoring candidate for effective diagnosis and therapy in cancer treatment.

Imaging Mass Spectrometry Reveals Tumor Metabolic Heterogeneity

Malignant tumors exhibit high degrees of genomic heterogeneity at the cellular level, leading to the view that subpopulations of tumor cells drive growth and treatment resistance. To examine the degree to which tumors also exhibit metabolic heterogeneity at the level of individual cells, we employed multi-isotope imaging mass spectrometry (MIMS) to quantify utilization of stable isotopes of glucose and glutamine along with a label for cell division. Mouse models of melanoma and malignant peripheral nerve sheath tumors (MPNSTs) exhibited striking heterogeneity of substrate utilization, evident in both proliferating and non-proliferating cells. We identified a correlation between metabolic heterogeneity, proliferation, and therapeutic resistance. Heterogeneity in metabolic substrate usage as revealed by incorporation of glucose and glutamine tracers is thus a marker for tumor proliferation. Collectively, our data demonstrate that MIMS provides a powerful tool with which to dissect metabolic functions of individual cells within the native tumor environment.

Recent and Current Advances in FDG-PET Imaging within the Field of Clinical Oncology in NSCLC: A Review of the Literature

Lung cancer is the leading cause of cancer-related deaths around the world, the most common type of which is non-small-cell lung cancer (NSCLC). Computed tomography (CT) is required for patients with NSCLC, but often involves diagnostic issues and large intra- and interobserver variability. The anatomic data obtained using CT can be supplemented by the metabolic data obtained using fluorodeoxyglucose F 18 (FDG) positron emission tomography (PET); therefore, the use of FDG-PET/CT for staging NSCLC is recommended, as it provides more accuracy than either modality alone. Furthermore, FDG-PET/magnetic resonance imaging (MRI) provides useful information on metabolic activity and tumor cellularity, and has become increasingly popular. A number of studies have described FDG-PET/MRI as having a high diagnostic performance in NSCLC staging. Therefore, multidimensional functional imaging using FDG-PET/MRI is promising for evaluating the activity of the intratumoral environment. Radiomics is the quantitative extraction of imaging features from medical scans. The chief advantages of FDG-PET/CT radiomics are the ability to capture information beyond the capabilities of the human eye, non-invasiveness, the (virtually) real-time response, and full-field analysis of the lesion. This review summarizes the recent advances in FDG-PET imaging within the field of clinical oncology in NSCLC, with a focus on surgery and prognostication, and investigates the site-specific strengths and limitations of FDG-PET/CT. Overall, the goal of treatment for NSCLC is to provide the best opportunity for long-term survival; therefore, FDG-PET/CT is expected to play an increasingly important role in deciding the appropriate treatment for such patients.

Exposure Doses to Technologists Working in 7 PET/CT Departments

Objective:

The aim of this study was to measure occupational exposure doses of technologists who dispense and inject radiopharmaceuticals in 7 positron emission tomography/computed tomography (PET/CT) departments. This was done with the goal to help improving protective designs in PET departments and/or establishing national protection standards.

Method:

Common LiF thermoluminescence dosimeters (TLDs) were placed on the chest and necklace of the technologists to monitor whole-body and thyroid doses, respectively. Ring TLDs were also worn on both index fingers to measure individual hand doses. All TLDs were assembled and measured once every 3 months for a total of 12 months. Additionally, we measured and compared the dose of TLDs attached to both the inside and the outside of the technologist’s lead coat.

Results:

Technologists received relatively high exposures, which accounted for 64% to 94% of the collective dose in their respective departments. Their thyroid doses ranged from 1.2 to 1.7 mSv/a; some technologists’ hand doses exceeded 500 mSv/a. Use of a lead coat reduced the average dose by 8%.

Conclusion:

Technologists working in PET/CT departments were the main population exposed to radiation. This work underscores the need for enhanced protective measures for these workers to better reduce their exposure, particularly for their hands.

A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning

Response to Neoadjuvant chemotherapy (NAC) has demonstrated a high correlation to survival in locally advanced breast cancer (LABC) patients. An early prediction of responsiveness to NAC could facilitate treatment adjustments on an individual patient basis that would be expected to improve treatment outcomes and patient survival. This study investigated, for the first time, the efficacy of quantitative computed tomography (qCT) parametric imaging to characterize intra-tumour heterogeneity and its application in predicting tumour response to NAC in LABC patients. Textural analyses were performed on CT images acquired from 72 patients before the start of chemotherapy to determine quantitative features of intra-tumour heterogeneity. The best feature subset for response prediction was selected through a sequential feature selection with bootstrap 0.632 + area under the receiver operating characteristic (ROC) curve (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{A}\mathrm{U}\mathrm{C}}_{0.632+}$$\end{document}AUC0.632+) as a performance criterion. Several classifiers were evaluated for response prediction using the selected feature subset. Amongst the applied classifiers an Adaboost decision tree provided the best results with cross-validated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{A}\mathrm{U}\mathrm{C}}_{0.632+}$$\end{document}AUC0.632+, accuracy, sensitivity and specificity of 0.89, 84%, 80% and 88%, respectively. The promising results obtained in this study demonstrate the potential of the proposed biomarkers to be used as predictors of LABC tumour response to NAC prior to the start of treatment.

Machine Learning-Based A Priori Chemotherapy Response Prediction in Breast Cancer Patients using Textural CT Biomarkers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020;2020:1250-1253. [PMID: 33018214 DOI: 10.1109/embc44109.2020.9176099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Early prediction of cancer response to neoadjuvant chemotherapy (NAC) could permit personalized treatment adjustments for patients, which would improve treatment outcomes and patient survival. For the first time, the efficiency of quantitative computed tomography (qCT) textural and second derivative of textural (SDT) features were investigated and compared in this study. It was demonstrated that intra-tumour heterogeneity can be probed through these biomarkers and used as chemotherapy tumour response predictors in breast cancer patients prior to the start of treatment. These features were used to develop a machine learning approach which provided promising results with cross-validated AUC0.632+, accuracy, sensitivity and specificity of 0.86, 81%, 74% and 88%, respectively.Clinical Relevance- The results obtained in this study demonstrate the potential of textural CT biomarkers as response predictors of standard NAC before treatment initiation.

Instant labeling of therapeutic cells for multimodality imaging

Autologous therapeutic cells are typically harvested and transplanted in one single surgery. This makes it impossible to label them with imaging biomarkers through classical transfection techniques in a laboratory. To solve this problem, we developed a novel microfluidic device, which provides highly efficient labeling of therapeutic cells with imaging biomarkers through mechanoporation. Methods: Studies were performed with a new, custom-designed microfluidic device, which contains ridges, which compress adipose tissue-derived stem cells (ADSCs) during their device passage. Cell relaxation after compression leads to cell volume exchange for convective transfer of nanoparticles and nanoparticle uptake into the cell. ADSCs were passed through the microfluidic device doped with iron oxide nanoparticles and 18F-fluorodeoxyglucose (FDG). The cellular nanoparticle and radiotracer uptake was evaluated with DAB-Prussian blue, fluorescent microscopy, and inductively coupled plasma spectrometry (ICP). Labeled and unlabeled ADSCs were imaged in vitro as well as ex vivo in pig knee specimen with magnetic resonance imaging (MRI) and positron emission tomography (PET). T2 relaxation times and radiotracer signal were compared between labeled and unlabeled cell transplants using Student T-test with p<0.05. Results: We report significant labeling of ADSCs with iron oxide nanoparticles and 18F-FDG within 12+/-3 minutes. Mechanoporation of ADSCs with our microfluidic device led to significant nanoparticle (> 1 pg iron per cell) and 18F-FDG uptake (61 mBq/cell), with a labeling efficiency of 95%. The labeled ADSCs could be detected with MRI and PET imaging technologies: Nanoparticle labeled ADSC demonstrated significantly shorter T2 relaxation times (24.2±2.1 ms) compared to unlabeled cells (79.6±0.8 ms) on MRI (p<0.05) and 18F-FDG labeled ADSC showed significantly higher radiotracer uptake (614.3 ± 9.5 Bq / 1×104 cells) compared to controls (0.0 ± 0.0 Bq/ 1×104 cells) on gamma counting (p<0.05). After implantation of dual-labeled ADSCs into pig knee specimen, the labeled ADSCs revealed significantly shorter T2 relaxation times (41±0.6 ms) compared to unlabeled controls (90±1.8 ms) (p<0.05). Conclusion: The labeling of therapeutic cells with our new microfluidic device does not require any chemical intervention, therefore it is broadly and immediately clinically applicable. Cellular labeling using mechanoporation can improve our understanding of in vivo biodistributions of therapeutic cells and ultimately improve long-term outcomes of therapeutic cell transplants.

Update on Hodgkin lymphoma from a radiologist's perspective

Recent advances in the management of Hodgkin lymphoma, due to new staging and response assessment systems as well as new therapies, have redefined the role of imaging for this disease. The purpose of this article is to provide radiologists with an update on the current role of imaging in Hodgkin lymphoma from diagnosis to assessment of treatment response, in view of the new staging and response assessment system and current treatment strategies.

Staging FDG PET-CT changes management in patients with gastric adenocarcinoma who are eligible for radical treatment

AIM

18-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) is valuable in the management of patients with oesophageal cancer, but a role in gastric cancer staging is debated. Our aim was to review the role of FDG PET-CT in a large gastric cancer cohort in a tertiary UK centre.

METHODS

We retrospectively reviewed data from 330 patients presenting with gastric adenocarcinoma between March 2014 and December 2016 of whom 105 underwent pre-treatment staging FDG PET-CT scans. FDG PET-CT scans were graded qualitatively and quantitatively (SUVmax) and compared with staging diagnostic CT and operative pathology results (n = 30) in those undergoing resection.

RESULTS

Of the 105 patients (74 M, median age 73 years) 86% of primary tumours were metabolically active (uptake greater than normal stomach) on FDG PET-CT [41/44 (93%) of the intestinal histological subtype (SUVmax 14.1 ± 1.3) compared to 36/46 (78%) of non-intestinal types (SUVmax 9.0 ± 0.9), p = 0.005]. FDG PET-CT upstaged nodal or metastastic staging of 20 patients (19%; 13 intestinal, 6 non-intestinal, 1 not reported), with 17 showing distant metastases not evident on other imaging. On histological analysis, available in 30 patients, FDG PET-CT showed low sensitivity (40%) but higher specificity (73%) for nodal involvement.

CONCLUSION

FDG PET-CT provides new information in a clinically useful proportion of patients, which leads to changes in treatment strategy, most frequently by detecting previously unidentified metastases, particularly in those with intestinal-type tumours.

Hounsfield units and fractal dimension (test HUFRA) for determining PET positive/negative lymph nodes in pediatric Hodgkin's lymphoma patients

Objectives

We had developed a method that can help detect and identify lymph nodes affected by the neoplastic process. Our group evaluated the fractal dimension (FD) and X-ray attenuation (XRA) of lymph nodes in HL and compared to their metabolic activity as measured by 18F-FDG-PET examination.

Methods

The training set included 72 lymph nodes from 31 consecutive patients, and the tested set of 71 lymph nodes from next 19 patients. The measurement of FD of each lymph node was performed before the start of therapy using original software. X-ray attenuation (XRA) expressed in HU (Hounsfield Units) from CT scans was compared with the metabolic activity of the lymphatic nodes, measured by 18F-FDG-PET examination.

Results

Significant differences were observed between XRA_max and FD_max values in assessing the PET(+) and PET(-) nodes. All nodes were scored from 0 to 2. The HUFRA test properly qualified 95% with a score of 2 and 0 points as PET(+) or PET(-).

Conclusion

The HUFRA test can differentiate about 70–80% of lymph nodes as PET(+) or PET(-) based solely on the CT examination. It can be useful in patients who were not subjected to 18FFDG-PET/CT examination before the treatment, or who had an unreliable result of 18F-FDG-PET/CT with further research requirements.

The immunological Warburg effect: Can a metabolic-tumor-stroma score (MeTS) guide cancer immunotherapy?

The "glycolytic switch" also known as the "Warburg effect" is a key feature of tumor cells and leads to the accumulation of lactate and protons in the tumor environment. Intriguingly, non-malignant lymphocytes or stromal cells such as tumor-associated macrophages and cancer-associated fibroblasts contribute to the lactate accumulation in the tumor environment, a phenomenon described as the "Reverse Warburg effect." Localized lactic acidosis has a strong immunosuppressive effect and mediates an immune escape of tumors. However, some tumors do not display the Warburg phenotype and either rely on respiration or appear as a mosaic of cells with different metabolic properties. Based on these findings and on the knowledge that T cell infiltration is predictive for patient outcome, we suggest a metabolic-tumor-stroma score to determine the likelihood of a successful anti-tumor immune response: (a) a respiring tumor with high T cell infiltration ("hot"); (b) a reverse Warburg type with respiring tumor cells but glycolytic stromal cells; (c) a mixed type with glycolytic and respiring compartments; and (d) a glycolytic (Warburg) tumor with low T cell infiltration ("cold"). Here, we provide evidence that these types can be independent of the organ of origin, prognostically relevant and might help select the appropriate immunotherapy approach.

Hyperglycemia and 18F-FDG PET/CT, issues and problem solving: a literature review

Positron emission tomography/computed tomography (PET/CT) is a standard procedure for imaging cancer commonly used in the clinical practice for several diseases, in particular for cancer staging, restaging, treatment monitoring and radiation therapy planning. Despite the availability of many radiotracers, 18F-fluoro-2-deoxy-2-D-glucose ([18F]FDG) is the most used. International PET/CT guidelines propose protocols for patients' correct preparation before [18F]FDG injection, in particular with the regard of diabetic patients and therapy management. Hyperglycemic conditions and oral or insulin medication showed advantages and disadvantages on PET/CT scan accuracy: A correct knowledge of effects of these conditions on glucose metabolism assumes a fundamental role on patients management before [18F]FDG PET/CT scan.

Clinical significance of PET/CT uptake for peripheral clinical N0 non-small cell lung cancer

Objective

In this cohort study, we determined the clinical value of the maximum standardized uptake value (SUVmax) of primary tumors in non‐small cell lung cancer (NSCLC).

Study Design

A retrospective review of NSCLC patients was performed from January 2011 to December 2017. Peripheral cN0 NSCLC patients with tumor size ≤2 cm were included. SUVmax was calculated as a continuous variable for semiquantitative analyses. A receiver operating characteristic curve was analyzed to assess the cutoff threshold of SUVmax on pathological (p) nodal metastasis. We further evaluated the clinical relevance of SUVmax in peripheral cN0 NSCLC patients.

Results

A total of 670 peripheral NSCLC patients with tumor size ≤2 cm were deemed cN0 by preoperative PET/CT scan. Statistical analyses suggested significant correlations of SUVmax with smoking status (P = .026), tumor volume (P = .001), pathology type (P = .008), tumor differentiation (P < .001), vessel invasion (P = .001), plural invasion (P < .001), pT stage (P < .001), nodal involvement (P < .001), and pathological tumor node metastasis stage (P < .001). A cutoff point of SUVmax of 3.8 (P < .001) could be used to predict pathological nodal metastasis. Multivariable analyses indicated that preoperative SUVmax >3.8 (odds ratio, 12.149; P < .001) was an independent predictor of nodal metastasis. Overall survival analyses further suggested that SUVmax was an independent prognostic indicator (hazard ratio, 2.050; P = .017).

Conclusion

Preoperative SUVmax is a predictor of pathological nodal metastasis and prognosis for peripheral cN0 NSCLC patients with tumor size ≤2 cm. Our results indicate that assessment of PET SUVmax could improve stratification of these patients.

Biomarker selection and imaging design in cancer: A link with biochemical pathways for imminent engineering

Malignant cells reprogram metabolic pathways to meet the demands of growth and proliferation. These altered manners of metabolism are now identified as hallmarks of cancer. Studies have revealed tumor cells alter specific pathways such as glycolysis, fatty acid synthesis and amino acid synthesis to support their proliferation. In this review, we provide a theoretical framework to understand metabolic reprogramming and the mechanisms accompanying distorted metabolism to tumor progression. How these alterations will be assisting in cancer diagnostics and advances in standard techniques in marker identification and imagining are also discussed.

Molecular imaging and immunotherapy

The utility of positron emission tomography (PET) for the evaluation of response to immunotherapy has been considered a hot topic, particularly in the last 2 to 3 years. Different experiences have been collected in clinical practice, with 18F-Fluorodeoxyglucose (FDG) PET/computed tomography (CT), particularly in patients affected by lymphoma, malignant melanoma, and lung cancer. It has been tested in different settings of disease, from the prediction to the prognosis relative to the response to immunotherapy. In the present mini-review, some evidence is reported about the role of FDG PET/CT in patient candidates to or treated with immunotherapy.