Detection of metabolic adaptation in a triple-negative breast cancer animal model with [18F]choline-PET imaging as a surrogate for drug resistance.

PURPOSE: Test the feasibility of an image-based method to identify taxane resistance in mouse bearing triple-negative breast cancer (TNBC) tumor xenografts. METHODS: Xenograft tumor-bearing mice from paclitaxel-sensitive and paclitaxel-resistant TNBC cells (MDA-MD-346) were generated by orthotopic injection into female NOD-SCID mice. When tumors reached 100-150 mm3, mice were scanned using [18F]choline PET/CT. Tumors were collected and sliced for autoradiography and immunofluorescence analysis. Quantitative data was analyzed accordingly. RESULTS: From fifteen mice scanned, five had taxane-sensitive cell line tumors of which two underwent taxol-based treatment. From the remaining 10 mice with taxane-resistant cell line tumors, four underwent taxol-based treatment. Only 13 mice had the tumor sample analyzed histologically. When normalized to the blood pool, both cell lines showed differences in metabolic uptake before and after treatment. CONCLUSIONS: Treated and untreated taxane-sensitive and taxane-resistant cell lines have different metabolic properties that could be leveraged before the start of chemotherapy.

Diagnostic performance of whole-body [18F]FDG PET/MR in cancer M staging: A systematic review and meta-analysis.

OBJECTIVES: To calculate the pooled diagnostic performances of whole-body [18F]FDG PET/MR in M staging of [18F]FDG-avid cancer entities. METHODS: A diagnostic meta-analysis was conducted on the [18F]FDG PET/MR in M staging, including studies: (1) evaluated [18F]FDG PET/MR in detecting distant metastasis; (2) compared[ 18F]FDG PET/MR with histopathology, follow-up, or asynchronous multimodality imaging as the reference standard; (3) provided data for the whole-body evaluation; (4) provided adequate data to calculate the meta-analytic performances. Pooled performances were calculated with their confidence interval. In addition, forest plots, SROC curves, and likelihood ratio scatterplots were drawn. All analyses were performed using STATA 16. RESULTS: From 52 eligible studies, 2289 patients and 2072 metastases were entered in the meta-analysis. The whole-body pooled sensitivities were 0.95 (95%CI: 0.91-0.97) and 0.97 (95%CI: 0.91-0.99) at the patient and lesion levels, respectively. The pooled specificities were 0.99 (95%CI: 0.97-1.00) and 0.97 (95%CI: 0.90-0.99), respectively. Additionally, subgroup analyses were performed. The calculated pooled sensitivities for lung, gastrointestinal, breast, and gynecological cancers were 0.90, 0.93, 1.00, and 0.97, respectively. The pooled specificities were 1.00, 0.98, 0.97, and 1.00, respectively. Furthermore, the pooled sensitivities for non-small cell lung, colorectal, and cervical cancers were 0.92, 0.96, and 0.86, respectively. The pooled specificities were 1.00, 0.95, and 1.00, respectively. CONCLUSION: [18F]FDG PET/MR was a highly accurate modality in M staging in the reported [18F]FDG-avid malignancies. The results showed high sensitivity and specificity in each reviewed malignancy type. Thus, our findings may help clinicians and patients to be confident about the performance of [18F]FDG PET/MR in the clinic. CLINICAL RELEVANCE STATEMENT: Although [18F]FDG PET/MR is not a routine imaging technique in current guidelines, mostly due to its availability and logistic issues, our findings might add to the limited evidence regarding its performance, showing a sensitivity of 0.95 and specificity of 0.97. KEY POINTS: • The whole-body [18F]FDG PET/MR showed high accuracy in detecting distant metastases at both patient and lesion levels. • The pooled sensitivities were 95% and 97% and pooled specificities were 99% and 97% at patient and lesion levels, respectively. • The results suggested that 18F-FDG PET/MR was a strong modality in the exclusion and confirmation of distant metastases.

Role of FDG PET/CT in Patients With Lymphoma Treated With Chimeric Antigen Receptor T-Cell Therapy: Current Concepts.

Chimeric antigen receptor (CAR) T-cell therapy is a cellular therapy in which the patient's T cells are enhanced to recognize and bind to specific tumor antigens. CAR T-cell therapy was initially developed for the treatment of leukemia, but its current main indication is the treatment of relapsed or refractory non-Hodgkin lymphoma. FDG PET/CT plays a fundamental role in the diagnosis, staging, therapy response assessment, and recurrence evaluation of patients with metabolically active lymphoma. Consistent with the examination's role in lymphoma management, FDG PET/CT is also the imaging modality of choice to evaluate patients before and after CAR T-cell therapy, and evidence supporting its utility in this setting continues to accumulate. In this article, we review current concepts in CAR T-cell therapy in patients with lymphoma, emphasizing the critical role of FDG PET/CT before and after therapy. A framework is presented that entails performing FDG PET/CT at four time points over the course of CAR T-cell therapy: pretherapy at baseline at the time of decision to administer CAR T-cell therapy and after any bridging therapies and posttherapy 1 and 3 months after infusion. PET parameters assessed at these time points predict various patient outcomes.

Current Applications of PET/MR: Part II: Clinical Applications II.

Due to the major improvements in the hardware and image reconstruction algorithms, positron emission tomography/magnetic resonance imaging (PET/MR) is now a reliable state-of-the-art hybrid modality in medical practice. Currently, it can provide a broad range of advantages in preclinical and clinical imaging compared to single-modality imaging. In the second part of this review, we discussed the further clinical applications of PET/MR. In the chest, PET/MR has particular potential in the oncology setting, especially when utilizing ultrashort/zero echo time MR sequences. Furthermore, cardiac PET/MR can provide reliable information in evaluating myocardial inflammation, cardiac amyloidosis, myocardial perfusion, myocardial viability, atherosclerotic plaque, and cardiac masses. In gastrointestinal and hepato-pancreato-biliary malignancies, PET/MR is able to precisely detect metastases to the liver, being superior over the other imaging modalities. In genitourinary and gynaecology applications, PET/MR is a comprehensive diagnostic method, especially in prostate, endometrial, and cervical cancers. Its simultaneous acquisition has been shown to outperform other imaging techniques for the detection of pelvic nodal metastases and is also a reliable modality in radiation planning. Lastly, in haematologic malignancies, PET/MR can significantly enhance lymphoma diagnosis, particularly in detecting extra-nodal involvement. It can also comprehensively assess treatment-induced changes. Furthermore, PET/MR may soon become a routine in multiple myeloma management, being a one-stop shop for evaluating bone, bone marrow, and soft tissues.

[18F]-FDG PET in anal canal cancer: a systematic review and meta-analysis.

PURPOSE: To provide comprehensive data on the diagnostic and prognostic value of [18F]-FDG PET (PET) in anal canal cancer patients. METHODS: This study was designed following the PRISMA-DTA guidelines. For the meta-analysis, published original articles (until December 2022) that met the following criteria were included: Evaluated PET for locoregional and/or distant disease detection in patients with histopathology-proven anal canal cancer; Compared PET with a valid reference standard; Provided crude data to calculate meta-analytic estimates. Diagnostic measurements from subgroups were calculated in evaluating primary tumour detection, T stage, lymph node and distant metastases. Articles providing prognostic information on PET were also reported as a systematic review. For pooled meta-analytic calculations, the hierarchical method was used. The bivariate model was conducted to find the summary estimates. Analyses were performed using STATA 16. RESULTS: After the screening, 28 studies were eligible to enter the meta-analytic calculations, and data from 15 were reported descriptively. For distinguishing T3/T4 from other T-stages, PET had pooled sensitivity and specificity of 91%(95%CI:72%-97%) and 96%(95%CI:88%-98%), respectively. The sensitivity and specificity for detecting metastatic (regional and/or distant) disease were 100% (95%CI:82%-100%) and 95% (95%CI:90%-98%), respectively. For therapy response assessment, the sensitivity and specificity of PET were 96%(95%CI:78%-99%) and 86%(95%CI:75%-93%), respectively. Higher pre-treatment total metabolic tumour volume was predictive of poorer survival. Conversely, for those achieving complete metabolic response, the 2-year PFS was 94%(95%CI:91%-97%) versus 51%(95%CI:42%-59%) for others (p-value < 0.001). CONCLUSION: PET may be a useful tool for anal canal cancer therapy planning and provides valuable prognostic information.

Diagnostic performance of [18F]-FDG PET/MR in evaluating colorectal cancer: a systematic review and meta-analysis.

PURPOSE: To calculate the diagnostic performance of [18F]-FDG PET/MR in colorectal cancer (CRC). METHODS: This study was designed following the PRISMA-DTA guidelines. To be included, published original articles (until December 31, 2021) that met the following criteria were considered eligible: (1) evaluated [18F]-FDG PET/MR as the diagnostic method to detect CRC; (2) compared [18F]-FDG PET/MR with histopathology as the reference standard, or clinical/imaging composite follow-up when pathology was not available; (3) provided adequate crude data for meta-analysis. The diagnostic pooled measurements were calculated at patient and lesion levels. Regarding sub-group analysis, diagnostic measurements were calculated in "TNM staging," "T staging," "N staging," "M staging," and "liver metastasis" sub-groups. Additionally, we calculated the pooled performances in "rectal cancer: patient-level" and "rectal cancer: lesion-level" sub-groups. A hierarchical method was used to pool the performances. The bivariate model was conducted to find the summary points. Analyses were performed using STATA 16. RESULTS: A total of 1534 patients from 18 studies were entered. The pooled sensitivities in CRC lesion detection (tumor, lymph nodes, and metastases) were 0.94 (95%CI: 0.89-0.97) and 0.93 (95%CI: 0.82-0.98) at patient-level and lesion-level, respectively. The pooled specificities were 0.89 (95%CI: 0.84-0.93) and 0.95 (95%CI: 0.90-0.98) at patient-level and lesion-level, respectively. In sub-groups, the highest sensitivity (0.97, 95%CI: 0.86-0.99) and specificity (0.99, 95%CI: 0.84-1.00) were calculated for "M staging" and "rectal cancer: lesion-level," respectively. The lowest sensitivity (0.81, 95%CI: 0.65-0.91) and specificity (0.79, 95%CI: 0.52-0.93) were calculated for "N staging" and "T staging," respectively. CONCLUSION: This meta-analysis showed an overall high diagnostic performance for [18F]-FDG PET/MR in detecting CRC lesions/metastases. Thus, this modality can play a significant role in several clinical scenarios in CRC staging and restaging. Specifically, one of the main strengths of this modality is ruling out the existence of CRC lesions/metastases. Finally, the overall diagnostic performance was not found to be affected in the post-treatment setting.

Aortic Endoprosthesis for the Treatment of Native Aortic Coarctation and Concomitant Aneurysm in an Octogenarian Patient.

We report a case of an 82-year-old female patient with native coarctation of the aorta and poststenotic aneurysm of the descending thoracic aorta. On consultation, she was receiving 4 antihypertensive drugs, and physical examination revealed nonpalpable lower-limb pulses with intermittent claudication at 50 min. Because of her age, high surgical risk and combination of lesions, endovascular treatment was suggested. Placement of a Valiant thoracic aorta endoprosthesis followed by coarctation angioplasty was performed. At 48 hr, the patient was discharged on 1 antihypertensive drug, palpable pulses on both limbs and a normal ankle-brachial index. At 1 month follow-up, the patient remained as discharged and multislice computed tomography angiography depicted complete coarctation expansion without residual stenosis, exclusion of the aortic aneurysm, and no signs of endoleaks.

Initial experience of MR/PET in a clinical cancer center.

Magentic Resonance/positron emission tomography (PET) has been introduced recently for imaging of clinical patients. This hybrid imaging technology combines the inherent strengths of MRI with its high soft-tissue contrast and biological sequences with the inherent strengths of PET, enabling imaging of metabolism with a high sensitivity. In this article, we describe the initial experience of MR/PET in a clinical cancer center along with a review of the literature. For establishing MR/PET in a clinical setting, technical challenges, such as attenuation correction and organizational challenges, such as workflow and reimbursement, have to be overcome. The most promising initial results of MR/PET have been achieved in anatomical areas where high soft-tissue and contrast resolution is of benefit. Head and neck cancer and pelvic imaging are potential applications of this hybrid imaging technology. In the pediatric population, MR/PET can decrease the lifetime radiation dose. MR/PET protocols tailored to different types of malignancies need to be developed. After the initial exploration phase, large multicenter trials are warranted to determine clinical indications for this exciting hybrid imaging technology and thereby opening new horizons in molecular imaging.

Radiomic-based prediction of lesion-specific systemic treatment response in metastatic disease.

Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 4.5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.70 for the most precise model (FDR = 0.05). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.

Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline 18F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?

We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients.

The [18F]F-FDG PET/CT Radiomics Classifier of Histologic Subtypes and Anatomical Disease Origins across Various Malignancies: A Proof-of-Principle Study.

We aimed to investigate whether [18F]F-FDG-PET/CT-derived radiomics can classify histologic subtypes and determine the anatomical origin of various malignancies. In this IRB-approved retrospective study, 391 patients (age = 66.7 ± 11.2) with pulmonary (n = 142), gastroesophageal (n = 128) and head and neck (n = 121) malignancies were included. Image segmentation and feature extraction were performed semi-automatically. Two models (all possible subset regression [APS] and recursive partitioning) were employed to predict histology (squamous cell carcinoma [SCC; n = 219] vs. adenocarcinoma [AC; n = 172]), the anatomical origin, and histology plus anatomical origin. The recursive partitioning algorithm outperformed APS to determine histology (sensitivity 0.90 vs. 0.73; specificity 0.77 vs. 0.65). The recursive partitioning algorithm also revealed good predictive ability regarding anatomical origin. Particularly, pulmonary malignancies were identified with high accuracy (sensitivity 0.93; specificity 0.98). Finally, a model for the synchronous prediction of histology and anatomical disease origin resulted in high accuracy in determining gastroesophageal AC (sensitivity 0.88; specificity 0.92), pulmonary AC (sensitivity 0.89; specificity 0.88) and head and neck SCC (sensitivity 0.91; specificity 0.92). Adding PET-features was associated with marginal incremental value for both the prediction of histology and origin in the APS model. Overall, our study demonstrated a good predictive ability to determine patients' histology and anatomical origin using [18F]F-FDG-PET/CT-derived radiomics features, mainly from CT.

Radiomic-Based Prediction of Lesion-Specific Systemic Treatment Response in Metastatic Disease.

Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.79 for the most precise model (FDR = 0.01). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.

Evaluation of MR anatomically-guided PET reconstruction using a convolutional neural network in PSMA patients.

Background. Recently, approaches have utilized the superior anatomical information provided by magnetic resonance imaging (MRI) to guide the reconstruction of positron emission tomography (PET). One of those approaches is the Bowsher's prior, which has been accelerated lately with a convolutional neural network (CNN) to reconstruct MR-guided PET in the imaging domain in routine clinical imaging. Two differently trained Bowsher-CNN methods (B-CNN0 and B-CNN) have been trained and tested on brain PET/MR images with non-PSMA tracers, but so far, have not been evaluated in other anatomical regions yet.Methods. A NEMA phantom with five of its six spheres filled with the same, calibrated concentration of 18F-DCFPyL-PSMA, and thirty-two patients (mean age 64 ± 7 years) with biopsy-confirmed PCa were used in this study. Reconstruction with either of the two available Bowsher-CNN methods were performed on the conventional MR-based attenuation correction (MRAC) and T1-MR images in the imaging domain. Detectable volume of the spheres and tumors, relative contrast recovery (CR), and background variation (BV) were measured for the MRAC and the Bowsher-CNN images, and qualitative assessment was conducted by ranking the image sharpness and quality by two experienced readers.Results. For the phantom study, the B-CNN produced 12.7% better CR compared to conventional reconstruction. The small sphere volume (<1.8 ml) detectability improved from MRAC to B-CNN by nearly 13%, while measured activity was higher than the ground-truth by 8%. The signal-to-noise ratio, CR, and BV were significantly improved (p< 0.05) in B-CNN images of the tumor. The qualitative analysis determined that tumor sharpness was excellent in 76% of the PET images reconstructed with the B-CNN method, compared to conventional reconstruction.Conclusions. Applying the MR-guided B-CNN in clinical prostate PET/MR imaging improves some quantitative, as well as qualitative imaging measures. The measured improvements in the phantom are also clearly translated into clinical application.

Disparity and Diversity in NSCLC Imaging and Genomics: Evaluation of a Mature, Multicenter Database.

Lung cancer remains the leading cancer-related death across North America. Imaging is fundamental. Recently, healthcare disparities came into research focus. Our aim was to explore disparity from an imaging, genetic, and outcome perspective. We utilized the AACR Project GENIE Biopharma Consortium (BPC) dataset v 1.1 to build a collated NSCLC dataset. Descriptive and analytical statistics were applied according to data characteristics. From 1849 patients, mean age was 64.4 y (±10.5), 58% (n = 1065) were female, 23% (n = 419) never smoked, 84% (n = 1545) were of white race, and 57% (n = 1052) were < stage III. No difference (p > 0.05) was found for baseline imaging by race. White race showed higher 3-month surveillance imaging (p = 0.048) and a baseline stage < IV (OR 0.61). KRAS (33.3 vs. 17.9%), STK11 (14.8 vs. 7.3%), and KEAP1 (13.3 vs. 5.3%) mutations were predominant among white patients while EGFR mutation (19.2 vs. 44.1%) was less predominant. Mutations in TP53 or KEAP1 had worse PFS and OS. The latter was also reduced in STK11, KRAS + STK11, and KRAS + KEAP1 mutations. Meanwhile, EGFR mutation had increased OS. Multivariate analysis showed that progression on imaging at 3 or 6 months (HR 1.69 and 1.43, respectively), TP53 (HR 1.37) and KRAS (HR 1.26) had lower OS while EGFR and LRP1B (HR 0.69 and 0.39, respectively) had higher OS. No racial disparity at baseline imaging was observed. Higher initial stages among non-white patients might reflect inequalities in accessing healthcare. However, race wasn't associated to OS. Finally, progression in imaging at 3 or 6 months showed the higher hazard ratios for death.

Respiratory and cardiac motion correction in positron emission tomography using elastic motion approach for simultaneous abdomen and thorax positron emission tomography-magnetic resonance imaging.

Background: Cardiac and respiratory motions in clinical positron emission tomography (PET) are a major contributor to inaccurate PET quantification and lesion characterisation. In this study, an elastic motion-correction (eMOCO) technique based on mass preservation optical flow is adapted and investigated for positron emission tomography-magnetic resonance imaging (PET-MRI) applications. Methods: The eMOCO technique was investigated in a motion management QA phantom and in twenty-four patients who underwent PET-MRI for dedicated liver imaging and nine patients for cardiac PET-MRI evaluation. Acquired data were reconstructed with eMOCO and gated motion correction techniques at cardiac, respiratory and dual gating modes, and compared to static images. Standardized uptake value (SUV), signal-to-noise ratio (SNR) of lesion activities from each gating mode and correction technique were measured and their means/standard deviation (SD) were compared using 2-ways ANOVA analysis and post-hoc Tukey's test. Results: Lesions' SNR are highly recovered from phantom and patient studies. The SD of the SUV resulted from the eMOCO technique was statistically significantly less (P<0.01) than the SD resulted from conventional gated and static SUVs at the liver, lung and heart. Conclusions: The eMOCO technique was successfully implemented in PET-MRI in a clinical setting and produced the lowest SD compared to gated and static images, and hence provided the least noisy PET images. Therefore, the eMOCO technique can potentially be used on PET-MRI for improved respiratory and cardiac motion correction.

Impact of the COVID-19 Pandemic on Staging Oncologic PET/CT Imaging and Patient Outcome in a Public Healthcare Context: Overview and Follow Up of the First Two Years of the Pandemic.

To assess the impact of the COVID-19 pandemic on the diagnosis, staging and outcome of a selected population throughout the first two years of the pandemic, we evaluated oncology patients undergoing PET/CT at our institution. A retrospective population of lung cancer, melanoma, lymphoma and head and neck cancer patients staged using PET/CT during the first 6 months of the years 2019, 2020 and 2021 were included for analysis. The year in which the PET was performed was our exposure variable, and our two main outcomes were stage at the time of the PET/CT and overall survival (OS). A total of 1572 PET/CTs were performed for staging purposes during the first 6 months of 2019, 2020 and 2021. The median age was 66 (IQR 16), and 915 (58%) were males. The most prevalent staged cancer was lung cancer (643, 41%). The univariate analysis of staging at PET/CT and OS by year of PET/CT were not significantly different. The multivariate Cox regression of non-COVID-19 significantly different variables at univariate analysis and the year of PET/CT determined that lung cancer (HR 1.76 CI95 1.23-2.53, p < 0.05), stage III (HR 3.63 CI95 2.21-5.98, p < 0.05), stage IV (HR 11.06 CI95 7.04-17.36, p < 0.05) and age at diagnosis (HR 1.04 CI95 1.02-1.05, p < 0.05) had increased risks of death. We did not find significantly higher stages or reduced OS when assessing the year PET/CT was performed. Furthermore, OS was not significantly modified by the year patients were staged, even when controlled for non-COVID-19 significant variables (age, type of cancer, stage and gender).

CT Radiomics and Whole Genome Sequencing in Patients with Pancreatic Ductal Adenocarcinoma: Predictive Radiogenomics Modeling.

We investigate whether computed tomography (CT) derived radiomics may correlate with driver gene mutations in patients with pancreatic ductal adenocarcinoma (PDAC). In this retrospective study, 47 patients (mean age 64 ± 11 years; range: 42-86 years) with PDAC, who were treated surgically and who underwent preoperative CT imaging at our institution were included in the study. Image segmentation and feature extraction was performed semi-automatically with a commonly used open-source software platform. Genomic data from whole genome sequencing (WGS) were collected from our institution's web-based resource. Two statistical models were then built, in order to evaluate the predictive ability of CT-derived radiomics feature for driver gene mutations in PDAC. 30/47 of all tumor samples harbored 2 or more gene mutations. Overall, 81% of tumor samples demonstrated mutations in KRAS, 68% of samples had alterations in TP53, 26% in SMAD4 and 19% in CDKN2A. Extended statistical analysis revealed acceptable predictive ability for KRAS and TP53 (Youden Index 0.56 and 0.67, respectively) and mild to acceptable predictive signal for SMAD4 and CDKN2A (Youden Index 0.5, respectively). Our study establishes acceptable correlation of radiomics features and driver gene mutations in PDAC, indicating an acceptable prognostication of genomic profiles using CT-derived radiomics. A larger and more homogenous cohort may further enhance the predictive ability.

Prognostic value of PET/CT and MR-based baseline radiomics among patients with non-metastatic nasopharyngeal carcinoma.

Purpose: Radiomics is an emerging imaging assessment technique that has shown promise in predicting survival among nasopharyngeal carcinoma (NPC) patients. Studies so far have focused on PET or MR-based radiomics independently. The aim of our study was to evaluate the prognostic value of clinical and radiomic parameters derived from both PET/CT and MR. Methods: Retrospective evaluation of 124 NPC patients with PET/CT and radiotherapy planning MR (RP-MR). Primary tumors were segmented using dedicated software (LIFEx version 6.1) from PET, CT, contrast-enhanced T1-weighted (T1-w), and T2-weighted (T2-w) MR sequences with 376 radiomic features extracted. Summary statistics describe patient, disease, and treatment characteristics. The Kaplan-Meier (KM) method estimates overall survival (OS) and progression-free survival (PFS). Clinical factors selected based on univariable analysis and the multivariable Cox model were subsequently constructed with radiomic features added. Results: The final models comparing clinical, clinical + RP-MR, clinical + PET/CT and clinical + RP-MR + PET/CT for OS and PFS demonstrated that combined radiomic signatures were significantly associated with improved survival prognostication (AUC 0.62 vs 0.81 vs 0.75 vs 0.86 at 21 months for PFS and 0.56 vs 0.85 vs 0.79 vs 0.96 at 24 months for OS). Clinical + RP-MR features initially outperform clinical + PET/CT for both OS and PFS (<18 months), and later in the clinical course for PFS (>42 months). Conclusion: Our study demonstrated that PET/CT-based radiomic features may improve survival prognostication among NPC patients when combined with baseline clinical and MR-based radiomic features.

Direct 64-row MDCT venography in the diagnosis of an inferior vena cava leiomyosarcoma.

We report the usefulness of a technique called direct-MDCT venography in the diagnostic workup of a patient with an inferior vena cava leiomyosarcoma. The technique consists in the injection of contrast agent through both lower limbs achieving maximum enhancement in the inferior vena cava. Images are similar to those of the gold standard conventional cavography. To our knowledge, this is the first description of the direct-MDCT imaging appearance of an inferior vena cava leiomyosarcoma.

The impact of orthopedic metal artifact reduction software on interreader variability when delineating areas of interest in the head and neck.

PURPOSE: Metal artifacts during computed tomography (CT) hinder the evaluation of diagnostic images and impair the delineation of tumor volume in treatment planning. Several solutions are available to minimize these artifacts. Our objective was to determine the impact of one of those tools on the interreader variability when measuring head and neck structures in the presence of metal artifacts. METHODS AND MATERIALS: Eleven patients were retrospectively selected from an institutional review board-approved study based on the presence of metallic artifacts in the head and neck region. CT raw data were postprocessed using a metal artifact reduction tool. A single matching CT slice from the filtered backprojection and postprocessed data sets was selected in the region of the metal artifact. Areas of selected anatomical structures were measured by independent readers, including an anatomical structure selected from a CT slice with no metal artifact in each patient as control. The intraclass correlation coefficient was calculated. RESULTS: Two extreme outliers were identified and the intraclass correlation coefficient was performed with and without them. The intraclass correlation on filtered backprojection, postprocessed, and control images was 0.903, 0.948, and 0.985 with outliers and 0.884, 0.971, and 0.989 without outliers, respectively, for all readers. On the other hand, the intraclass correlation on filtered backprojection, postprocessed, and control images for experienced readers was 0.904, 0.979, and 0.976 with outliers and 0.934, 0.975, and 0.990 without outliers, respectively. CONCLUSIONS: The interreader variability of areas measured in the presence of metal artifact was greatly decreased by the use of the metal artifact reduction tool and almost matched the variability observed in the absence of the metal artifact.