Positron Emission Tomography And Computed Tomography Scans Research Articles

18F-FMISO PET-guided dose escalation with multifield optimization intensity-modulated proton therapy in nasopharyngeal carcinoma.

The purpose of this study was to evaluate the radiotherapy planning feasibility of dose escalation with intensity-modulated proton therapy (IMPT) to hypoxic tumor regions identified on 18F-Fluoromisonidazole (FMISO) positron emission tomography and computed tomography (PET-CT) in NPC. Nine patients with stages T3-4N0-3M0 NPC underwent 18F-FMISO PET-CT before and during week 3 of radiotherapy. The hypoxic volume (GTVhypo) is automatically generated by applying a subthresholding algorithm within the gross tumor volume (GTV) with a tumor to muscle standardized uptake value (SUV) ratio of 1.3 on the 18F-FMISO PET-CT scan. Two proton plans were generated for each patient, a standard plan to 70Gy and dose escalation plan with upfront boost followed by standard 70GyE plan. The stereotactic boost was planned with single-field uniform dose optimization using two fields to deliver 10 GyE in two fractions to GTVhypo. The standard plan was generated with IMPT with robust optimization to deliver 70GyE, 60GyE in 33 fractions using simultaneous integrated boost technique. A plan sum was generated for assessment. Eight of nine patients showed tumor hypoxia on the baseline 18F-FMISO PET-CT scan. The mean hypoxic tumor volume was 3.9 cm3 (range .9-11.9cm3 ). The average SUVmax of the hypoxic volume was 2.2 (range 1.44-2.98). All the dose-volume parameters met the planning objectives for target coverage. Dose escalation was not feasible in three of eight patients as the D0.03cc of temporal lobe was greater than 75GyE. The utility of boost to the hypoxic volume before standard course of radiotherapy with IMPT is dosimetrically feasible in selected patients. Clinical trials are warranted to determine the clinical outcomes of this approach.

68Ga-PSMA PET-CT and PSMA score affecting therapeutic decision-making in high-risk prostatic carcinoma.

This research study was conducted to evaluate the impact of (68Ga)-tagged prostatic-specific membrane antigen (68Ga-PSMA) positron emission tomography and computed tomography (PET-CT), compare its role with conventional radiology in early staging of high-risk prostate cancer, and calculate the PSMA score evaluating its usefulness in 68Ga-PSMA PET-CT reporting in our patient population. 68Ga-PSMA PET-CT of 65 high-risk cases of prostate cancer was performed for staging purpo-ses. Any change in disease stage was noted after 68Ga-PSMA PET-CT findings and PSMA score leading to a change in the management plan. Change in disease stage post-PSMA imaging was seen in 39% cases, high PSMA score (03) was noted in > 80% of upstaged cases, while low score (0) and (1) was seen in 65% and 35% down-staged individuals, respectively. Change in therapeutic decision-making was observed in 32% (21) of patients. 68Ga-PSMA PET-CT scans have a significant influence on the planned clinical management of high-risk prostate cancer patients; hence, they can be utilized as a replacement for radiological imaging tools, particularly in the detection of pelvic nodal and distant metastatic disease. PSMA score can be considered as an effective tool in standardized reporting of 68Ga-PSMA imaging.

Multi-Modal Co-Learning for Liver Lesion Segmentation on PET-CT Images.

Liver lesion segmentation is an essential process to assist doctors in hepatocellular carcinoma diagnosis and treatment planning. Multi-modal positron emission tomography and computed tomography (PET-CT) scans are widely utilized due to their complementary feature information for this purpose. However, current methods ignore the interaction of information across the two modalities during feature extraction, omit the co-learning of the feature maps of different resolutions, and do not ensure that shallow and deep features complement each others sufficiently. In this paper, our proposed model can achieve feature interaction across multi-modal channels by sharing the down-sampling blocks between two encoding branches to eliminate misleading features. Furthermore, we combine feature maps of different resolutions to derive spatially varying fusion maps and enhance the lesions information. In addition, we introduce a similarity loss function for consistency constraint in case that predictions of separated refactoring branches for the same regions vary a lot. We evaluate our model for liver tumor segmentation using a PET-CT scans dataset, compare our method with the baseline techniques for multi-modal (multi-branches, multi-channels and cascaded networks) and then demonstrate that our method has a significantly higher accuracy ( ) than the baseline models.

Diffuse large B-cell lymphoma segmentation in PET-CT images via hybrid learning for feature fusion.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive type of lymphoma with high mortality and poor prognosis that especially has a high incidence in Asia. Accurate segmentation of DLBCL lesions is crucial for clinical radiation therapy. However, manual delineation of DLBCL lesions is tedious and time-consuming. Automatic segmentation provides an alternative solution but is difficult for diffuse lesions without the sufficient utilization of multimodality information. Our work is the first study focusing on positron emission tomography and computed tomography (PET-CT) feature fusion for the DLBCL segmentation issue. We aim to improve the fusion performance of complementary information contained in PET-CT imaging with a hybrid learning module in the supervised convolutional neural network. First, two encoder branches extract single-modality features, respectively. Next, the hybrid learning component utilizes them to generate spatial fusion maps which can quantify the contribution of complementary information. Such feature fusion maps are then concatenated with specific-modality (i.e., PET and CT) feature maps to obtain a representation of the final fused feature maps in different scales. Finally, the reconstruction part of our network creates a prediction map of DLBCL lesions by integrating and up-sampling the final fused feature maps from encoder blocks in different scales. The ability of our method was evaluated to detect foreground and segment lesions in three independent body regions (nasopharynx, chest, and abdomen) of a set of 45 PET-CT scans. Extensive ablation experiments compared our method to four baseline techniques for multimodality fusion (input-level (IL) fusion, multichannel (MC) strategy, multibranch (MB) strategy, and quantitative weighting (QW) fusion). The results showed that our method achieved a high detection accuracy (99.63% in the nasopharynx, 99.51% in the chest, and 99.21% in the abdomen) and had the superiority in segmentation performance with the mean dice similarity coefficient (DSC) of 73.03% and the modified Hausdorff distance (MHD) of 4.39mm, when compared with the baselines (DSC: IL: 53.08%, MC: 63.59%, MB: 69.98%, and QW: 72.19%; MHD: IL: 12.16mm, MC: 6.46mm, MB: 4.83mm, and QW: 4.89mm). A promising segmentation method has been proposed for the challenging DLBCL lesions in PET-CT images, which improves the understanding of complementary information by feature fusion and may guide clinical radiotherapy. The statistically significant analysis based on P-value calculation has indicated a degree of significant difference between our proposed method and other baselines (almost metrics: P<0.05). This is a preliminary research using a small sample size, and we will collect data continually to achieve the larger verification study.

3D FULLY CONVOLUTIONAL NETWORKS FOR CO-SEGMENTATION OF TUMORS ON PET-CT IMAGES.

Positron emission tomography and computed tomography (PET-CT) dual-modality imaging provides critical diagnostic information in modern cancer diagnosis and therapy. Automated accurate tumor delineation is essentially important in computer-assisted tumor reading and interpretation based on PET-CT. In this paper, we propose a novel approach for the segmentation of lung tumors that combines the powerful fully convolutional networks (FCN) based semantic segmentation framework (3D-UNet) and the graph cut based co-segmentation model. First, two separate deep UNets are trained on PET and CT, separately, to learn high level discriminative features to generate tumor/non-tumor masks and probability maps for PET and CT images. Then, the two probability maps on PET and CT are further simultaneously employed in a graph cut based co-segmentation model to produce the final tumor segmentation results. Comparative experiments on 32 PET-CT scans of lung cancer patients demonstrate the effectiveness of our method.

IMPROVING TUMOR CO-SEGMENTATION ON PET-CT IMAGES WITH 3D CO-MATTING.

Positron emission tomography and computed tomography (PET-CT) plays a critically important role in modern cancer therapy. In this paper, we focus on automated tumor delineation on PET-CT image pairs. Inspired by co-segmentation model, we develop a novel 3D image co-matting technique making use of the inner-modality information of PET and CT for matting. The obtained co-matting results are then incorporated in the graph-cut based PET-CT co-segmentation framework. Our comparative experiments on 32 PET-CT scan pairs of lung cancer patients demonstrate that the proposed 3D image co-matting technique can significantly improve the quality of cost images for the co-segmentation, resulting in highly accurate tumor segmentation on both PET and CT scan pairs.

The effects of thyroid hormones on brown adipose tissue in humans: a PET‐CT study

Brown adipose tissue (BAT) is important for energy expenditure through thermogenesis, although its regulatory factors are not well known in humans. There is evidence suggesting that thyroid hormones affect BAT functions in some mammals, but the effects of thyroid hormones on BAT activity in humans are still unclear. The aim of this study was to investigate the effects of thyroid hormones on glucose metabolism of BAT and other organs in humans. Nine Graves' disease-caused hyperthyroid patients who were newly diagnosed and untreated were studied. Putative brown adipose tissue activity was determined by the integrated ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron-emission tomography and computed tomography (PET-CT). All hyperthyroid patients were treated with methimazole and had been monitored until their symptoms disappeared and thyroid hormone levels returned to normal. At the end, a second PET-CT scan was performed. The average follow-up period was 77 days. Meanwhile, compared with a group of seventy-five brown adipose tissue-negative controls, thyroid hormones of seventy-five BAT-positive healthy subjects were measured. Active brown adipose tissue was not present in any of the hyperthyroid patients. However, one patient with normalized thyroid function showed active BAT after therapy. The free T3 levels and free T4 levels were significantly lower in the 75 BAT-positive subjects than in the BAT-negative subjects. All hyperthyroid patients showed symmetrically increased uptake of fluorodeoxyglucose in skeletal muscles before treatment, whereas, the standardized uptake value was substantially decreased after treatment. Abnormally high circulating thyroid hormone levels may not increase brown adipose tissue activity, which may be limited by the increased obligatory thermogenesis of muscle in adult humans.

Value of 18F-FETNIM PET-CT for detection of tumor hypoxia in non-small-cell lung cancer

To assess the feasibility of [(18)F]fluoroerythronitroimidazole ((18)F-FETNIM) with integrated positron emission tomography and computed tomography (PET-CT) imaging in detection of hypoxia in non-small-cell lung cancer (NSCLC) patients. Forty-two patients with newly diagnosed NSCLC underwent (18)F-FETNIM PET-CT before treatment. Nineteen patients rested for approximately 120 minutes before undergoing PET-CT, 23 patients underwent 2 sequential PET-CT scans at 60 minutes and 120 minutes after intravenous injection (18)F-FETNIM. (18)F-FETNIM uptake was quantified by calculating the maximum standardized uptake value in the tumor (SUVmax-T) and contralateral normal lung tissue (SUVmax-N). Regions of interest (ROIs) were drawn in the tumor and contralateral position and the radioactivity ratio of tumor to normal (T/N) was calculated. SUVmax-T (2.43 +/- 1.34) was significantly higher than SUVmax-N (0.87 +/- 0.46, P < 0.001) at 120 min. SUVmax-T (2.80 +/- 1.09) and SUVmax-N (1.16 +/- 0.56) at 60 min were significantly higher than SUVmax-T (2.61 +/- 1.10) and SUVmax-N (P < 0.01) at 120 min. T/N (2.56 +/- 0.71) at 60 min was higher than that at 120 min (2.48 +/- 0.60), but the difference between them was not significant (P = 0.324). Our results indicate that (18)F-FETNIM PET-CT may be a useful tool for evaluating hypoxia and may be a means to target specifically tumor cells resistant to conventional treatment before and during ongoing therapy in NSCLC.

Correlation between PET-CT 18FDG uptake in primary lesions and clinicopathological parameters in esophageal carcinoma patients

To investigate the correlation between 18F-fluorodeoxyglucose (18FDG) uptake of primary lesions during PET-CT (positron emission tomography and computed tomography) examination and clinicopathological parameters such as the tumor length, depth of invasion, differentiation of the primary lesions and lymph node metastasis status in the patients with esophageal carcinoma. From June 2004 to November 2006, 68 operable esophageal carcinoma patients were enrolled into this study, and all had a whole body 18FDG PET-CT scan before operation. The maximum standardized uptake value (SUVmax) of the primary lesions was measured. The tumor length, depth of invasion, differentiation of the primary lesions and lymph node metastasis status were determined by postoperative pathological examination. The correlation between the standardized uptake value (SUV) of primary lesions and the above mentioned clinicopathological parameters was analyzed. The overall length of primary lesion was positively correlated with SUVmax (r=0.512, P=0.01). Depth of invasion was also positively correlated with SUVmax (r=0.860, P=0.000). There was a statistically significant difference in SUVmax between poorly differentiated group and moderately or well differentiated group (r=0.781, P=0.000), and also between the groups with or without lymph node metastasis (r=0.852, P=0.000). The tumor length, depth of invasion and differentiation of the primary lesions of the esophageal carcinoma are all positively correlated with maximum standardized uptake value of 18FDG. The more poorly differentiated lesions show a higher 18FDG maximum standardized uptake value. The lesions with lymph node metastasis have also a significantly higher 18FDG maximum standardized uptake value than those without lymph node metastases.

Deferring Planned Neck Dissection Following Chemoradiation for Stage IV Head and Neck Cancer: The Utility of PET‐CT

To determine whether combined positron emission tomography and computed tomography (PET-CT) may be of value in deferring planned neck dissections for patients with advanced head and neck squamous cell carcinoma (HNSCC). Observational study of patients with de novo cervical > or =N2 regional spread of HNSCC in a tertiary care academic medical center. Forty-three patients were identified who underwent post-treatment PET-CT within 6 months of completing neoadjuvant chemotherapy combined with radiation therapy (CRT). The PET-CT was "positive" if the radiologist recommended tissue sampling or resection of cervical lymph nodes, or if there was progressive neck disease in the setting of distant metastatic disease. Patients who had positive PET-CT underwent confirmatory biopsy given clinical suspicion for regional cervical metastasis without distant disease. Patients with negative PET-CT were followed clinically and radiographically for a minimum of 5 months (median 18.1 months) after CRT. Ten (22%) of the 43 post-treatment PET-CT studies were positive. Seven of the 10 PET-CT scans (70% of positives) were true-positive given histologically-confirmed residual viable tumor or progressive disease including disease in the neck. The 3 remaining studies (30% of positives) were false-positive PET-CT results, given resolution of fluorodeoxyglucose (FDG) avidity on subsequent imaging or tissue sampling demonstrating absence of viable tumor cells. Of the 33 patients with negative PET-CTs in the neck, 1 patient had absence of FDG-avidity in the setting of malignant disease in the neck (3% false negatives); otherwise, patients with an initially negative PET-CT scan had no recurrences during the study (97% true negatives). This corresponds to a sensitivity of 87.5% (7/8), a specificity of 91% (32/35), a positive predictive value of 70% (7/10), a negative predictive value of 97% (32/33), and accuracy of 91% (39/43) for PET-CT scans in the detection of cervical metastatic disease after CRT. Overall, 37 (86%) of 43 patients were spared neck dissection using this technology without evidence of recurrent disease in the neck at extended follow-up. Our results suggest that planned neck dissection after CRT for HNSCC may be deferred in favor of serial PET-CT imaging, and that sampling of areas of suspicious FDG-avid uptake can be rationally considered prior to therapeutic neck dissection. These data also suggest that negative PET-CT scans are highly reliable for the absence of residual cervical nodal disease.

Diagnostic Utility of Positron Emission Tomography‐Computed Tomography for Predicting Malignancy in Cystic Neck Masses in Adults

Combined positron emission tomography and computed tomography (PET-CT) is used for the diagnostic evaluation and staging of squamous cell carcinoma of the head and neck (SCCHN). By superimposing anatomic localization of CT with the physiologic data of PET, occult primary and metastatic neoplasms might be identified. Because the diagnostic algorithm for cystic neck masses in adults often overlaps with the work-up of cancer of unknown primary site, we evaluated the utility of PET-CT scans to identify the presence of malignancy and the location of primary tumor. Single-institution retrospective case review series. We reviewed the PET-CT imaging of cystic neck masses occurring in five patients over 40 years of age with significant risk factors for SCCHN and correlated this information with histopathology. In each patient in our series, the PET portion of a combined PET-CT was misleading, whereas the CT examination was more suggestive of the correct pathology. Ultimately, clinical judgment and endoscopic evaluation, guided by CT findings, were most valuable for distinguishing malignant versus benign processes and identifying the primary tumor sites. PET-CT may not be a reliable modality for identifying malignancy in adults with suspicious cystic neck masses. A thorough clinical evaluation by an experienced head and neck surgeon, in conjunction with contrast-enhanced CT, may be sufficient to facilitate the optimal management of such patients.