Lawrence H Schwartz

New York Presbyterian Hospital, New York City, New York, United States

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Publications (200)1115.34 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Quantitative size, shape, and texture features derived from computed tomographic (CT) images may be useful as predictive, prognostic, or response biomarkers in non-small cell lung cancer (NSCLC). However, to be useful, such features must be reproducible, non-redundant, and have a large dynamic range. We developed a set of quantitative three-dimensional (3D) features to describe segmented tumors and evaluated their reproducibility to select features with high potential to have prognostic utility. Thirty-two patients with NSCLC were subjected to unenhanced thoracic CT scans acquired within 15 min of each other under an approved protocol. Primary lung cancer lesions were segmented using semi-automatic 3D region growing algorithms. Following segmentation, 219 quantitative 3D features were extracted from each lesion, corresponding to size, shape, and texture, including features in transformed spaces (laws, wavelets). The most informative features were selected using the concordance correlation coefficient across test-retest, the biological range and a feature independence measure. There were 66 (30.14 %) features with concordance correlation coefficient ≥ 0.90 across test-retest and acceptable dynamic range. Of these, 42 features were non-redundant after grouping features with R (2) Bet ≥ 0.95. These reproducible features were found to be predictive of radiological prognosis. The area under the curve (AUC) was 91 % for a size-based feature and 92 % for the texture features (runlength, laws). We tested the ability of image features to predict a radiological prognostic score on an independent NSCLC (39 adenocarcinoma) samples, the AUC for texture features (runlength emphasis, energy) was 0.84 while the conventional size-based features (volume, longest diameter) was 0.80. Test-retest and correlation analyses have identified non-redundant CT image features with both high intra-patient reproducibility and inter-patient biological range. Thus making the case that quantitative image features are informative and prognostic biomarkers for NSCLC.
    Journal of Digital Imaging 07/2014; · 1.10 Impact Factor
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    Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 05/2014;
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    ABSTRACT: The cut-off values currently used to categorize tumor response to therapy are neither biologically based nor tailored for measurement reproducibility with contemporary imaging modalities. Sources and magnitudes of discordance in response assessment in metastatic colorectal cancer (mCRC) are unknown. A subset of patients' CT images of chest, abdomen and pelvis were randomly chosen from a multi-center clinical trial evaluating IGF-1R targeted therapy in mCRC. Using Response Evaluation Criteria in Solid Tumors (RECIST), three radiologists selected target lesions and measured UNI (maximal diameter), BI (product of maximal diameter and maximal perpendicular diameter) and VOL (volume) on baseline and 6-week post-therapy scans in the following ways: (1) each radiologist independently selected and measured target lesions and (2) one radiologist's target lesions were blindly re-measured by the others. Variability in relative change of tumor measurements was analyzed using linear mixed effects models. Three radiologists independently selected 138, 101 and 146 metastatic target lesions in the liver, lungs, lymph nodes and other organs (e.g., peritoneal cavity) in 29 patients. Of 198 target lesions total, 33% were selected by all three, 28% by two, and 39% by one radiologist. With independent selection, the variability in relative change of tumor measurements was 11% (UNI), 19% (BI) and 22% (VOL), respectively. When measuring the same lesions, the corresponding numbers were 8%, 14% and 12%. The relatively low variability in change of mCRC measurements suggests that response criteria could be modified to allow more accurate and sensitive CT assessment of anti-cancer therapy efficacy.
    Clinical Cancer Research 04/2014; · 7.84 Impact Factor
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    ABSTRACT: In conjunction with biomarkers, imaging is an important component of the diagnostic work up and subsequent management of men with prostate cancer. The relevant literature was retrieved from a search of MEDLINE with appropriate key words. Osseous metastases develop in close to 90% of patients with metastatic prostate cancer, thus making bone scans (single photon, using Tc-99m labeled phosphonates) the mainstay of imaging in advanced prostate cancer. Bone scans are limited by their lack of specificity and an unclear relationship between bone scan changes and disease progression or response to therapy. In addition to Tc-99m bone scans, other technologies that accurately identify of sites of active disease would considerably aid castration resistant prostate cancer (CRPC) management. Accordingly, metabolic imaging, cell surface receptor targeting, and magnetic resonance imaging (MRI) are being studied for their role in evaluating metastatic disease. Due to the increasing availability of advanced imaging modalities, the optimal modality and appropriate clinical time point for its use remains unclear. A number of imaging modalities are currently or imminently available for use in advanced prostate cancer. Future research will focus on the appropriate incorporation of these modalities in prostate cancer management.
    The Canadian Journal of Urology 04/2014; 21(2 Supp 1):42-7. · 0.74 Impact Factor
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    ABSTRACT: For patients with unresectable intrahepatic cholangiocarcinoma (ICC), treatment options are limited and survival is poor. This study summarizes the long-term outcome of two previously reported clinical trials using hepatic arterial infusion (HAI) with floxuridine and dexamethasone (with or without bevacizumab) in advanced ICC. Prospectively collected clinicopathologic and survival data were retrospectively reviewed. Response was based on Response Evaluation Criteria in Solid Tumors (RECIST). Pre-HAI dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images were reviewed, and tumor perfusion data correlated with outcome. Forty-four patients were analyzed (floxuridine, 26; floxuridine/bevacizumab, 18). At a median follow-up of 29.3 months, 41 patients had died of disease. Partial response by RECIST was observed in 48 %, and 50 % had stable disease. Three patients underwent resection after response, and 82 % received additional HAI after removal from the trials. Median survival was similar in both trials (floxuridine 29.3 months vs. floxuridine/bevacizumab 28.5 months; p = 0.96). Ten (23 %) patients survived ≥3 years, including 5 (11 %) who survived ≥5 years. Tumor perfusion measured on pre-treatment DCE-MRI [area under the gadolinium concentration curve at 90 and 180 s (AUC90 and AUC180, respectively)] was significantly higher in ≥3-year survivors and was the only factor that distinguished this group from <3-year survivors (mean AUC90 22.6 vs. 15.9 mM s, p = 0.025, and mean AUC180 48.9 vs. 32.3 mM s, p = 0.003, respectively). Median hepatic progression-free survival was longer in ≥3-year survivors (12.9 vs. 9.3 months, respectively; p = 0.008). HAI chemotherapy can result in prolonged survival in unresectable ICC. Pre-HAI DCE-MRI may predict treatment outcome.
    Annals of Surgical Oncology 03/2014; · 4.12 Impact Factor
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    ABSTRACT: Lung cancer often coexists with acute and chronic lung diseases such as chronic obstructive pulmonary disease. Therefore, mediastinal lymph nodes may be false-positive on (18)F-FDG PET because of the inflammatory disease alone. Nevertheless, (18)F-FDG PET/CT is the primary imaging modality used for staging patients with lung cancer, including nodal status. The purpose of this study was to evaluate whether volumetric CT histogram analysis can improve the characterization of lymph nodes on PET/CT staging of patients with lung cancer. Sixty histologically proven lymph nodes of 45 patients aged 43-76 y diagnosed with lung cancer were investigated. (18)F-FDG PET/CT, contrast-enhanced CT, and nonenhanced CT were performed before surgery or biopsy as part of the clinical staging procedure. Lymph nodes were analyzed on the basis of the (18)F-FDG standardized uptake value and volumetric CT histogram analysis. These findings were correlated to the gold standard of histopathology. Histologic examination revealed 36 positive and 24 negative lymph nodes, which were also successfully analyzed by volumetric CT histogram. Median CT density was significantly higher for histologically positive lymph nodes (33.2 Hounsfield units [HU]; range, -29.8 to 59.1) than for histologically negative lymph nodes (10.1 HU; range, -21.0 to 87.4; P = 0.002). The incidence of malignancy was 88% above a cutoff value of 20 HU in the ten (18)F-FDG-equivocal lymph nodes; the incidence of benign findings was 100% in the interval between -20 and +20 HU. Visual- and density-based analysis on contrast-enhanced CT failed to differentiate affected from nonaffected lymph nodes. Three-dimensional histogram analysis is a promising and potentially valuable imaging surrogate for N-stage stratification in patients with lung cancer with unclear glucose uptake during (18)F-FDG PET imaging. In cases of equivocal (18)F-FDG PET status, this technique might potentially bridge the diagnostic gap between noninvasive techniques and invasive lymph node sampling and could help improve the yield of core biopsies.
    Journal of Nuclear Medicine 02/2014; · 5.77 Impact Factor
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    ABSTRACT: To explore the effects of computed tomography (CT) slice thickness and reconstruction algorithm on quantification of image features to characterize tumors using a chest phantom. Twenty-two phantom lesions of known sizes (10 and 20 mm), shapes (spherical, elliptical, lobulated, and spiculated), and densities [-630, -10, and +100 Hounsfield Unit (HU)] were inserted into an anthropomorphic thorax phantom and scanned three times with relocations. The raw data were reconstructed using six imaging settings, i.e., a combination of three slice thicknesses of 1.25, 2.5, and 5 mm and two reconstruction kernels of lung and standard. Lesions were segmented and 14 image features representing lesion size, shape, and texture were calculated. Differences in the measured image features due to slice thickness and reconstruction algorithm were compared using linear regression method by adjusting three confounding variables (size, density, and shape). All 14 features were significantly different between 1.25 and 5 mm slice images. The 1.25 and 2.5 mm slice thicknesses were better than 5 mm for volume, density mean, density SD gray-level co-occurrence matrix (GLCM) energy and homogeneity. As for the reconstruction algorithm, there was no significant difference in uni-dimension, volume, shape index 9, and compactness. Lung reconstruction was better for density mean, whereas standard reconstruction was better for density SD. CT slice thickness and reconstruction algorithm can significantly affect the quantification of image features. Thinner (1.25 and 2.5 mm) and thicker (5 mm) slice images should not be used interchangeably. Sharper and smoother reconstructions significantly affect the density-based features.
    Translational oncology 02/2014; 7(1):88-93. · 3.40 Impact Factor
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    ABSTRACT: Background:Pazopanib achieved the end point of clinical activity in pretreated patients with urothelial cancer in a single-group, phase 2 trial. The objective was to identify biological predictors of clinical benefit to pazopanib in these patients.Methods:EDTA blood samples were collected at baseline (T0) and after 4 weeks (T1) of treatment, together with radiological imaging in all 41 patients to analyse plasma circulating angiogenic factor levels by multiplex ELISA plates. Changes from T0 to T1 in marker levels were matched with response with the covariance analysis. Univariable and multivariable analyses evaluated the association with overall survival (OS), adjusted for prespecified clinical variables. Net reclassification improvement (NRI) tested the performance of the recognised Cox model.Results:Increasing IL8(T1) level associated with lower response probability at covariance analysis (P=0.010). Both IL8(T0) (P=0.019) and IL8(T1) (P=0.004) associated with OS and the prognostic model, including clinical variables and IL8(T1) best-predicted OS after backward selection. The NRI for this model was 39%.When analysed as a time-varying covariate, IL8(T1) level<80 pg ml(-1) portended significantly greater response (∼80%) and 6-month OS (∼60%) probability than level80.Conclusion:IL8-level changes during pazopanib allowed for a prognostic improvement and were associated with response probability.British Journal of Cancer advance online publication, 14 November 2013; doi:10.1038/bjc.2013.719 www.bjcancer.com.
    British Journal of Cancer 11/2013; · 5.08 Impact Factor
  • Geoffrey R Oxnard, Lawrence H Schwartz
    Journal of Clinical Oncology 09/2013; · 18.04 Impact Factor
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    ABSTRACT: Aim: Radiopeptide therapy with beta emitter labeled (177)Lu/(90)Y- DOTA(0)-Phe(1)-Tyr(3)-octreotide (DOTATOC) and more recently also alpha emitting (213)Bi-DOTATOC are promising new treatments for neuroendocrine tumors. No early predictors for treatment response have been recognized and tumor-shrinkage after radiation therapy appears slowly. In some solid tumors a decline in tumor perfusion was found predictive of final treatment response but the gold standard multiphase computed tomography (CT) has a high radiation burden. Therefore we evaluated the ability of contrast-enhanced ultrasound (CEUS) to evaluate tumor perfusion as a response criteria. Materials and Methods: 14 patients with hepatic neuroendocrine tumor (NET) metastases were enrolled in the retrospective study. Eleven patients were treated with beta-emitting (177)Lu/(90)Y-DOTATOC, either intravenous (i.v.) (n = 5) or intra-arterial (i.a.) (n = 6) and three patients received alpha-emitting (213)Bi-DOTATOC (i.a.). CEUS and contrast-enhanced CT (CE-CT) were performed before and 3 months after treatment. Results: CE-CT and CEUS presented comparable results in the baseline study and in the assessment of perfusion changes due to the different treatment regimes. A therapy related decrease in tumor perfusion is an early predictor of longterm morphologic response. Conclusion: CEUS is available and radiation free technique which showed comparable results for perfusion and diameter of liver metastases compared to CE-CT. Intensity reduction in an arterial phase CEUS can be seen as a positive sign indicating long term tumor response to treatment. Therefore CEUS may be considered as an imaging modality for monitoring early treatment after focal alpha and beta targeted therapy.
    Experimental oncology 06/2013; 35(2):122-6.
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    ABSTRACT: BACKGROUND: Intraperitoneal chemotherapy is used to treat peritoneal surface-spreading malignancies. We sought to determine whether volume and surface area of the intraperitoneal chemotherapy compartments are associated with overall survival and posttreatment glomerular filtration rate (GFR) in malignant peritoneal mesothelioma (MPM) patients. METHODS: Thirty-eight MPM patients underwent X-ray computed tomography peritoneograms during outpatient intraperitoneal chemotherapy. We calculated volume and surface area of contrast-filled compartments by semiautomated computer algorithm. We tested whether these were associated with overall survival and posttreatment GFR. RESULTS: Decreased likelihood of mortality was associated with larger surface areas (p = 0.0201) and smaller contrast-filled compartment volumes (p = 0.0341), controlling for age, sex, histologic subtype, and presence of residual disease >0.5 cm postoperatively. Larger volumes were associated with higher posttreatment GFR, controlling for pretreatment GFR, body surface area, surface area, and the interaction between body surface area and volume (p = 0.0167). DISCUSSION: Computed tomography peritoneography is an appropriate modality to assess for maldistribution of intraperitoneal chemotherapy. In addition to identifying catheter failure and frank loculation, quantitative analysis of the contrast-filled compartment's surface area and volume may predict overall survival and cisplatin-induced nephrotoxicity. Prospective studies should be undertaken to confirm and extend these findings to other diseases, including advanced ovarian carcinoma.
    Annals of Surgical Oncology 05/2013; · 4.12 Impact Factor
  • Daniel Carl Sullivan, Lawrence H Schwartz, Binsheng Zhao
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    ABSTRACT: Tumor measurements on computed tomgoraphic or MRI scans and/or the appearance of new lesions on any of a variety of imaging studies including positron emission tomographic scans are key determinants for assessing progression-free survival as an endpoint in many clinical trials of therapies for solid tumors. Test-retest tumor measurement reproducibility may vary considerably across serial scans on the same patient unless rigorous attention is paid to standardization of image acquisition parameters and unless measurements are made by trained, experienced observers using validated objective methods. Target lesion selection also must be done with care to choose lesions that are or will be reproducibly measurable. Likewise, new lesions will be missed or misinterpreted on follow-up imaging studies unless those imaging studies are obtained using techniques suitable for detecting early, small lesions. Reader variability is clearly a major component of the problem. The increasing availability of semiautomatic image processing algorithms will help ameliorate that issue. In addition, an array of internationally accepted guidelines, standards, and accreditation programs now exist to help address these problems. Clin Cancer Res; 19(10); 2621-8. ©2013 AACR.
    Clinical Cancer Research 05/2013; 19(10):2621-8. · 7.84 Impact Factor
  • Michael L Maitland, Lawrence H Schwartz, Mark J Ratain
    Journal of Clinical Oncology 05/2013; · 18.04 Impact Factor
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    ABSTRACT: PURPOSEIn clinical trials, traditional monitoring methods, paper documentation, and outdated collection systems lead to inaccuracies of study information and inefficiencies in the process. Integrated electronic systems offer an opportunity to collect data in real time. PATIENTS AND METHODS We created a computer software system to collect 13 patient-reported symptomatic adverse events and patient-reported Karnofsky performance status, semi-automated RECIST measurements, and laboratory data, and we made this information available to investigators in real time at the point of care during a phase II lung cancer trial. We assessed data completeness within 48 hours of each visit. Clinician satisfaction was measured.ResultsForty-four patients were enrolled, for 721 total visits. At each visit, patient-reported outcomes (PROs) reflecting toxicity and disease-related symptoms were completed using a dedicated wireless laptop. All PROs were distributed in batch throughout the system within 24 hours of the visit, and abnormal laboratory data were available for review within a median of 6 hours from the time of sample collection. Manual attribution of laboratory toxicities took a median of 1 day from the time they were accessible online. Semi-automated RECIST measurements were available to clinicians online within a median of 2 days from the time of imaging. All clinicians and 88% of data managers felt there was greater accuracy using this system. CONCLUSION Existing data management systems can be harnessed to enable real-time collection and review of clinical information during trials. This approach facilitates reporting of information closer to the time of events, and improves efficiency, and the ability to make earlier clinical decisions.
    Journal of Clinical Oncology 04/2013; · 18.04 Impact Factor
  • Yongqiang Tan, Lawrence H Schwartz, Binsheng Zhao
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    ABSTRACT: Purpose: Lung lesions vary considerably in size, density, and shape, and can attach to surrounding anatomic structures such as chest wall or mediastinum. Automatic segmentation of the lesions poses a challenge. This work communicates a new three-dimensional algorithm for the segmentation of a wide variety of lesions, ranging from tumors found in patients with advanced lung cancer to small nodules detected in lung cancer screening programs.Methods: The authors' algorithm uniquely combines the image processing techniques of marker-controlled watershed, geometric active contours as well as Markov random field (MRF). The user of the algorithm manually selects a region of interest encompassing the lesion on a single slice and then the watershed method generates an initial surface of the lesion in three dimensions, which is refined by the active geometric contours. MRF improves the segmentation of ground glass opacity portions of part-solid lesions. The algorithm was tested on an anthropomorphic thorax phantom dataset and two publicly accessible clinical lung datasets. These clinical studies included a same-day repeat CT (prewalk and postwalk scans were performed within 15 min) dataset containing 32 lung lesions with one radiologist's delineated contours, and the first release of the Lung Image Database Consortium (LIDC) dataset containing 23 lung nodules with 6 radiologists' delineated contours. The phantom dataset contained 22 phantom nodules of known volumes that were inserted in a phantom thorax.Results: For the prewalk scans of the same-day repeat CT dataset and the LIDC dataset, the mean overlap ratios of lesion volumes generated by the computer algorithm and the radiologist(s) were 69% and 65%, respectively. For the two repeat CT scans, the intra-class correlation coefficient (ICC) was 0.998, indicating high reliability of the algorithm. The mean relative difference was -3% for the phantom dataset.Conclusions: The performance of this new segmentation algorithm in delineating tumor contour and measuring tumor size illustrates its potential clinical value for assisting in noninvasive diagnosis of pulmonary nodules, therapy response assessment, and radiation treatment planning.
    Medical Physics 04/2013; 40(4):043502. · 2.91 Impact Factor
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    ABSTRACT: OBJECTIVE: Understanding magnitudes of variability when measuring tumor size may be valuable in improving detection of tumor change and thus evaluating tumor response to therapy in clinical trials and care. Our study explored intra- and inter-reader variability of tumor uni-dimensional (1D), bi-dimensional (2D), and volumetric (VOL) measurements using manual and computer-aided methods (CAM) on CT scans reconstructed at different slice intervals. MATERIALS AND METHODS: Raw CT data from 30 patients enrolled in oncology clinical trials was reconstructed at 5, 2.5, and 1.25mm slice intervals. 118 lesions in the lungs, liver, and lymph nodes were analyzed. For each lesion, two independent radiologists manually and, separately, using computer software, measured the maximum diameter (1D), maximum perpendicular diameter, and volume (CAM only). One of them blindly repeated the measurements. Intra- and inter-reader variability for the manual method and CAM were analyzed using linear mixed-effects models and Bland-Altman method. RESULTS: For the three slice intervals, the maximum coefficients of variation for manual intra-/inter-reader variability were 6.9%/9.0% (1D) and 12.3%/18.0% (2D), and for CAM were 5.4%/9.3% (1D), 11.3%/18.8% (2D) and 9.3%/18.0% (VOL). Maximal 95% reference ranges for the percentage difference in intra-reader measurements for manual 1D and 2D, and CAM VOL were (-15.5%, 25.8%), (-27.1%, 51.6%), and (-22.3%, 33.6%), respectively. CONCLUSIONS: Variability in measuring the diameter and volume of solid tumors, manually and by CAM, is affected by CT slice interval. The 2.5mm slice interval provides the least measurement variability. Among the three techniques, 2D has the greatest measurement variability compared to 1D and 3D.
    European journal of radiology 03/2013; · 2.65 Impact Factor
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    ABSTRACT: Purpose:To retrospectively identify quantitative computed tomographic (CT) features that correlate with epidermal growth factor receptor (EGFR) mutation in surgically resected lung adenocarcinomas stratified by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) classification in an East Asian cohort of patients known to have a high prevalence of EGFR mutations.Materials and Methods:An institutional review board approved this study and waived informed consent. In 153 surgically resected lung adenocarcinomas, EGFR mutation was determined by direct DNA sequencing. Histologic subtype was classified according to IASLC/ATS/ERS classification of lung adenocarcinoma. At preoperative chest CT, the percentage of ground-glass opacity (GGO) volume and total tumor volume of each tumor were measured by using a semiautomated algorithm. Distribution of EGFR mutation according to histologic subtype, percentage of GGO volume, and total tumor volume was evaluated by using the Fisher exact test, the Student t test, trend analysis, and multiple logistic regression analysis.Results:Exon 21 missense mutation was more frequent in lepidic predominant adenocarcinomas than in other histologic subtypes (odds ratio, 3.44; 95% confidence interval: 1.53, 7.74; P = .003). GGO volume percentage in tumors with exon 21 missense mutation (61.7% ± 31.9 [standard deviation]) was significantly higher than that in EGFR wild-type tumors (30.0% ± 38.5) (P = .0001) and exon 19-mutated tumors (28.9% ± 37.7) (P = .0006). A significant trend of prevalence of exon 21 missense mutation increasing along with increasing GGO volume (P = .0008) was found.Conclusion:GGO volume percentage in tumors with exon 21 missense mutation was significantly higher than that in tumors with other EGFR mutation status. This can be related to the fact that exon 21 missense mutation was significantly more frequent in lepidic predominant adenocarcinomas, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic predominant invasive adenocarcinoma, according to IASLE/ATS/ERS classification.© RSNA, 2013Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13112553/-/DC1.
    Radiology 03/2013; · 6.34 Impact Factor
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    ABSTRACT: Aim: Positron-emission tomography/computed tomography (PET/CT) with [68Ga]DOTA0-Phe1-Tyr3-octreotide (68Ga-DOTA-TOC) became a standard for somatostatin receptor imaging. We investigated the potential changes of normal tissue uptake in patients with neuroendocrine tumor undergoing peptide receptor radionuclide therapy (PRRT). Methods: Sixteen patients underwent [68Ga]-DOTA-TOC-PET/CT prior and after 4-6 cycles of PRRT (mean administered activity: 13.8 GBq 90Y+ 9.6 177Lu). The maximum standardized uptake values (SUVmax) of pituitary, thyroid, spleen, liver parenchyma, pancreas, kidneys and adrenals were determined, respectively. Results: SUVmax values prior and after PRRT were in pituitary (5, 56±2,91/ 4,47±2,53), thyroid (2.05±1.11/ 2.49±2.47), spleen (24.95±14.20/20.06±8.53), liver (7.13±3.96/6.62±2.63), pancreas (6.96±1.99/6.83±2.00), kidneys (13.0±3.85/11.31±3.31) and adrenals (9.65± 4.20/7.10±2.86). A comparison of pre- and post treatment values revealed no significant differences (P>0.05) in any of these organs. Conclusion: The uptake of [68Ga] DOTA-TOC in normal tissue is not significantly affected by PRRT. This is relevant with regards to therapeutic monitoring were tumor-to-non-tumor ratio seems to be the most robust biomarker.
    The quarterly journal of nuclear medicine and molecular imaging: official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR), [and] Section of the Society of... 02/2013; · 1.92 Impact Factor
  • David Leung, Lawrence Schwartz
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    ABSTRACT: Neuroendocrine tumors (NETs) are a heterogeneous group of neoplasms that differ in their biological, chemical, and physical behaviors depending on the degree of differentiation and locations. Consequently, evaluation of these tumors is complex, requiring clinical history, physical examination, laboratory data, and imaging. With advances in morphologic and functional imaging techniques, we now have tools for caring of patients with these tumors at diagnosis, staging, treatment assessment, and prognosis prediction. In general, no single imaging modality can provide all the necessary information. However, well-chosen combinations of available imaging modalities based on the indications, strength and limitations of the modalities, and local expertise will provide optimal evaluation of patients with NETs.
    Seminars in Oncology 02/2013; 40(1):109-19. · 4.33 Impact Factor
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    ABSTRACT: The majority of radiological reports are lacking a standard structure. Even within a specialized area of radiology, each report has its individual structure with regards to details and order, often containing too much of non-relevant information the referring physician is not interested in. For gathering relevant clinical key parameters in an efficient way or to support long-term therapy monitoring, structured reporting might be advantageous. Despite of new technologies in medical information systems, medical reporting is still not dynamic. To improve the quality of communication in radiology reports, a new structured reporting system was developed for abdominal aortic aneurysms (AAA), intended to enhance professional communication by providing the pertinent clinical information in a predefined standard. Actual state analysis was performed within the departments of radiology and vascular surgery by developing a Technology Acceptance Model. The SWOT (strengths, weaknesses, opportunities, and threats) analysis focused on optimization of the radiology reporting of patients with AAA. Definition of clinical parameters was achieved by interviewing experienced clinicians in radiology and vascular surgery. For evaluation, a focus group (4 radiologists) looked at the reports of 16 patients. The usability and reliability of the method was validated in a real-world test environment in the field of radiology. A Web-based application for radiological "structured reporting" (SR) was successfully standardized for AAA. Its organization comprises three main categories: characteristics of pathology and adjacent anatomy, measurements, and additional findings. Using different graphical widgets (eg, drop-down menus) in each category facilitate predefined data entries. Measurement parameters shown in a diagram can be defined for clinical monitoring and be adducted for quick adjudications. Figures for optional use to guide and standardize the reporting are embedded. Analysis of variance shows decreased average time required with SR to obtain a radiological report compared to free-text reporting (P=.0001). Questionnaire responses confirm a high acceptance rate by the user. The new SR system may support efficient radiological reporting for initial diagnosis and follow-up for AAA. Perceived advantages of our SR platform are ease of use, which may lead to more accurate decision support. The new system is open to communicate not only with clinical partners but also with Radiology Information and Hospital Information Systems.
    JMIR research protocols. 01/2013; 2(2):e30.

Publication Stats

10k Citations
1,115.34 Total Impact Points

Institutions

  • 2011–2014
    • New York Presbyterian Hospital
      • Department of Radiology
      New York City, New York, United States
    • University of Texas Southwestern Medical Center
      • Division of Surgical Oncology
      Dallas, TX, United States
  • 2010–2014
    • Columbia University
      • Department of Radiology
      New York City, New York, United States
  • 2012–2013
    • Dana-Farber Cancer Institute
      Boston, Massachusetts, United States
    • Icahn School of Medicine at Mount Sinai
      Manhattan, New York, United States
    • New York University
      • Department of Radiology
      New York City, NY, United States
  • 2004–2011
    • Memorial Sloan-Kettering Cancer Center
      • • Department of Radiology
      • • Department of Surgery
      • • Genitourinary Oncology Service
      • • Department of Medical Physics
      New York City, NY, United States
    • Shanghai Jiao Tong University
      • School of Biomedical Engineering
      Shanghai, Shanghai Shi, China
  • 2005–2010
    • Cornell University
      • • Department of Medicine
      • • Department of Public Health
      Ithaca, NY, United States
  • 2006–2008
    • Thomas Jefferson University
      • Department of Radiology
      Philadelphia, PA, United States
    • Rutgers, The State University of New Jersey
      • Department of Computer Science
      New Brunswick, NJ, United States
  • 2007
    • University of Iowa
      • Department of Radiology
      Iowa City, IA, United States
  • 2002–2005
    • Weill Cornell Medical College
      New York City, New York, United States