Tumor heterogeneity for differentiation between liver tumors and normal liver tissue in 18F-FDG PET/CT.

AIM: Malignancies show higher spatial heterogeneity than normal tissue. We investigated, if textural parameters from FDG PET describing the heterogeneity function as tool to differentiate between tumor and normal liver tissue. METHODS: FDG PET/CT scans of 80 patients with liver metastases and 80 patients with results negative upper abdominal organs were analyzed. Metastases and normal liver tissue were analyzed drawing up to three VOIs with a diameter of 25 mm in healthy liver tissue of the tumoral affected and results negative liver, whilst up to 3 metastases per patient were delineated. Within these VOIs 30 different textural parameters were calculated as well as SUV. The parameters were compared in terms of intra-patient and inter-patient variability (2-sided t test). ROC analysis was performed to analyze predictive power and cut-off values. RESULTS: 28 textural parameters differentiated healthy and pathological tissue (p < 0.05) with high sensitivity and specificity. SUV showed ability to differentiate but with a lower significance. 15 textural parameters as well as SUV showed a significant variation between healthy tissues out of tumour infested and negative livers. Mean intra- and inter-patient variability of metastases were found comparable or lower for 6 of the textural features than the ones of SUV. They also showed good values of mean intra- and inter-patient variability of VOIs drawn in liver tissue of patients with metastases and of results negative ones. CONCLUSION: Heterogeneity parameters assessed in FDG PET are promising to classify tissue and differentiate malignant lesions usable for more personalized treatment planning, therapy response evaluation and precise delineation of tumors for target volume determination as part of radiation therapy planning.

Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy.

PURPOSE: Early identification of aggressive disease could improve decision support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-positron emission tomography (PET) before PRRT was analyzed. PROCEDURES: Thirty-one patients with G1/G2 pNET were enrolled (G2, n = 23/31). Prior to PRRT with [177Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET computed tomography was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUVmean/max), imaging-based TF, and clinical parameters (Ki67, CgA) for prediction of both progression-free survival (PFS) and overall survival (OS) after PRRT were evaluated. RESULTS: Within a median follow-up of 3.7 years, tumor progression was detected in 21 patients (median, 1.5 years) and 13/31 deceased (median, 1.9 years). In ROC analysis, the TF entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff = 6.7, AUC = 0.71, p = 0.02). Of note, increasing entropy could predict a longer survival (> 6.7, OS = 2.5 years, 17/31), whereas less voxel-based derangement portended inferior outcome (< 6.7, OS = 1.9 years, 14/31). These findings were supported in a G2 subanalysis (> 6.9, OS = 2.8 years, 9/23 vs. < 6.9, OS = 1.9 years, 14/23). Kaplan-Meier analysis revealed a significant distinction between high- and low-risk groups using entropy (n = 31, p < 0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n = 31, p = 0.04). Ki67 was negatively associated with PFS (p = 0.002); however, SUVmean/max failed in prognostication (n.s.). CONCLUSIONS: In contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification.

Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib.

PURPOSE: The metabolically most active lesion in 2-deoxy-2-(18F)fluoro-D-glucose (18F-FDG) PET/CT can predict progression-free survival (PFS) in patients with medullary thyroid carcinoma (MTC) starting treatment with the tyrosine kinase inhibitor (TKI) vandetanib. However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters (total lesion glycolysis, TLG) derived by pre-therapeutic 18F-FDG PET. METHODS: Eighteen patients with progressive MTC underwent baseline 18F-FDG PET/CT prior to and 3 months after vandetanib initiation. By manual segmentation of the tumor burden at baseline and follow-up PET, intratumoral TF and TLG were computed. The ability of TLG, imaging-based TF, and clinical parameters (including age, tumor marker doubling times, prior therapies and RET (rearranged during transfection) mutational status) for prediction of both PFS and OS were evaluated. RESULTS: The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low- and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3 y (vs. low-risk group, OS = 5.3 y, 8/18, AUC = 0.78, P = 0.03). Baseline TLG designated 11/18 patients to the high-risk group (OS = 3.5 y vs. low-risk group, OS = 5 y, 7/18, AUC = 0.83, P = 0.005). The Hazard Ratio for cancer-related death was 6.1 for Complexity (TLG, 9.5). Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction (P = 0.02, OS, n.s.). CONCLUSIONS: The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction.

Role of textural heterogeneity parameters in patient selection for 177Lu-PSMA therapy via response prediction.

PURPOSE: Prostate cancer is most common tumor in men causing significant patient mortality and morbidity. In newer diagnostic/therapeutic agents PSMA linked ones are specifically important. Analysis of textural heterogeneity parameters is associated with determination of innately aggressive and therapy resistant cell lines thus emphasizing their importance in therapy planning. The objective of current study was to assess predictive ability of tumor textural heterogeneity parameters from baseline 68Ga-PSMA PET prior to 177Lu-PSMA therapy. RESULTS: Entropy showed a negative correlation (rs = -0.327, p = 0.006, AUC = 0.695) and homogeneity showed a positive correlation (rs = 0.315, p = 0.008, AUC = 0.683) with change in pre and post therapy PSA levels. CONCLUSIONS: Study showed potential for response prediction through baseline PET scan using textural features. It suggested that increase in heterogeneity of PSMA expression seems to be associated with an increased response to PSMA radionuclide therapy. MATERIALS AND METHODS: Retrospective analysis of 70 patients was performed. All patients had metastatic prostate cancer and were planned to undergo 177Lu-PSMA therapy. Pre-therapeutic 68Ga- PSMA PET scans were used for analysis. 3D volumes (VOIs) of 3 lesions each in bones and lymph nodes were manually delineated in static PET images. Five PET based textural heterogeneity parameters (COV, entropy, homogeneity, contrast, size variation) were determined. Results obtained were then compared with clinical parameters including pre and post therapy PSA, alkaline phosphate, bone specific alkaline phosphate levels and ECOG criteria. Spearman correlation was used to determine statistical dependence among variables. ROC analysis was performed to estimate the optimal cutoff value and AUC.

Correction to: Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy.

The article "Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy," was originally published electronically on the publisher's internet portal without open access.

Survival prediction in patients undergoing radionuclide therapy based on intratumoral somatostatin-receptor heterogeneity.

The NETTER-1 trial demonstrated significantly improved progression-free survival (PFS) for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET) emphasizing the high demand for response prediction in appropriate candidates. In this multicenter study, we aimed to elucidate the prognostic value of tumor heterogeneity as assessed by somatostatin receptor (SSTR)-PET/CT. 141 patients with SSTR-expressing tumors were analyzed obtaining SSTR-PET/CT before PRRT (1-6 cycles, 177Lu somatostatin analog). Using the Interview Fusion Workstation (Mediso), a total of 872 metastases were manually segmented. Conventional PET parameters as well as textural features representing intratumoral heterogeneity were computed. The prognostic ability for PFS and overall survival (OS) were examined. After performing Cox regression, independent parameters were determined by ROC analysis to obtain cut-off values to be used for Kaplan-Meier analysis. Within follow-up (median, 43.1 months), 75 patients showed disease progression (median, 22.2 m) and 54 patients died (median, 27.6 m). Cox analysis identified 8 statistically independent heterogeneity parameters for time-to-progression and time-to-death. Among them, the textural feature Entropy predicted both PFS and OS. Conventional PET parameters failed in response prediction. Imaging-based heterogeneity assessment provides prognostic information in PRRT candidates and outperformed conventional PET parameters. Its implementation in clinical practice can pave the way for individualized patient management.

A study on the value of computer-assisted assessment for SPECT/CT-scans in sentinel lymph node diagnostics of penile cancer as well as clinical reliability and morbidity of this procedure.

BACKGROUND: Because of the increasing importance of computer-assisted post processing of image data in modern medical diagnostic we studied the value of an algorithm for assessment of single photon emission computed tomography/computed tomography (SPECT/CT)-data, which has been used for the first time for lymph node staging in penile cancer with non-palpable inguinal lymph nodes. In the guidelines of the relevant international expert societies, sentinel lymph node-biopsy (SLNB) is recommended as a diagnostic method of choice. The aim of this study is to evaluate the value of the afore-mentioned algorithm and in the clinical context the reliability and the associated morbidity of this procedure. METHODS: Between 2008 and 2015, 25 patients with invasive penile cancer and inconspicuous inguinal lymph node status underwent SLNB after application of the radiotracer Tc-99m labelled nanocolloid. We recorded in a prospective approach the reliability and the complication rate of the procedure. In addition, we evaluated the results of an algorithm for SPECT/CT-data assessment of these patients. RESULTS: SLNB was carried out in 44 groins of 25 patients. In three patients, inguinal lymph node metastases were detected via SLNB. In one patient, bilateral lymph node recurrence of the groins occurred after negative SLNB. There was a false-negative rate of 4 % in relation to the number of patients (1/25), resp. 4.5 % in relation to the number of groins (2/44). Morbidity was 4 % in relation to the number of patients (1/25), resp. 2.3 % in relation to the number of groins (1/44). The results of computer-assisted assessment of SPECT/CT data for sentinel lymph node (SLN)-diagnostics demonstrated high sensitivity of 88.8 % and specificity of 86.7 %. CONCLUSIONS: SLNB is a very reliable method, associated with low morbidity. Computer-assisted assessment of SPECT/CT data of the SLN-diagnostics shows high sensitivity and specificity. While it cannot replace the assessment by medical experts, it can still provide substantial supplement and assistance.

Assessment of tumor heterogeneity in treatment-naïve adrenocortical cancer patients using (18)F-FDG positron emission tomography.

As an orphan malignancy, only limited treatment options are available in adrenocortical carcinoma (ACC). Non-invasive risk assessment has not been described but may be of value to stratify patients for treatment. We aimed to evaluate the potential value of intra-individual tumor heterogeneity as assessed by (18)F-fluorodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) for outcome prediction in treatment-naïve ACC patients. Ten patients with primary diagnosis of ACC were included in this study. Prior to any treatment initiation, baseline (18)F-FDG PET scans were performed. Tumor staging was performed using the European Network for the Study of Adrenal Tumors (ENS@T). Intratumoral heterogeneity of the primary tumor was assessed by manual segmentation using conventional PET parameters (standardized uptake values and tumor-to-liver ratios) and textural features. The impact of tumoral heterogeneity based on pre-therapeutic (18)F-FDG PET to predict progression-free (PFS) and overall survival (OS) was evaluated by receiver operating characteristic analysis. On average, tumor recurrence or progression was detected after median of 561 days (range 71-1434 days) after the pre-therapeutic baseline PET scan. 50 % of the patients died of ACC within the follow-up period (mean 983 ± 404 days). Pre-therapeutic tumor volume was associated with PFS (r = -0.67, p = 0.05) and Ki67 index with OS (r = -0.66, p = 0.04). ENS@T tumor stage was the only parameter to correlate with both PFS and OS (r = -0.82, p = 0.001, and r = -0.72, p = 0.01, respectively). In the subgroup of patients without distant metastases (ENS@T stages II and III), age and pre-therapeutic tumor volume correlated significantly with PFS (r = 0.96, p = 0.01 and r = -0.93, p = 0.02, respectively) and OS (r = 0.95, p = 0.02 and r = -0.90, p = 0.04, respectively). None of the investigated classic or textural PET parameters predicted PFS or OS. In this pilot study in treatment-naïve ACC patients, conventional (18)F-FDG PET-derived parameters and textural tumor heterogeneity features were not suitable to identify high-risk patients.

Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy.

BACKGROUND: Textural features in FDG-PET have been shown to provide prognostic information in a variety of tumor entities. Here we evaluate their predictive value for recurrence and prognosis in NSCLC patients receiving primary stereotactic radiation therapy (SBRT). METHODS: 45 patients with early stage NSCLC (T1 or T2 tumor, no lymph node or distant metastases) were included in this retrospective study and followed over a median of 21.4 months (range 3.1-71.1). All patients were considered non-operable due to concomitant disease and referred to SBRT as the primary treatment modality. Pre-treatment FDG-PET/CT scans were obtained from all patients. SUV and volume-based analysis as well as extraction of textural features based on neighborhood gray-tone difference matrices (NGTDM) and gray-level co-occurence matrices (GLCM) were performed using InterView Fusion™ (Mediso Inc., Budapest). The ability to predict local recurrence (LR), lymph node (LN) and distant metastases (DM) was measured using the receiver operating characteristic (ROC). Univariate and multivariate analysis of overall and disease-specific survival were executed. RESULTS: 7 out of 45 patients (16%) experienced LR, 11 (24%) LN and 11 (24%) DM. ROC revealed a significant correlation of several textural parameters with LR with an AUC value for entropy of 0.872. While there was also a significant correlation of LR with tumor size in the overall cohort, only texture was predictive when examining T1 (tumor diameter < = 3 cm) and T2 (>3 cm) subgroups. No correlation of the examined PET parameters with LN or DM was shown. In univariate survival analysis, both heterogeneity and tumor size were predictive for disease-specific survival, but only texture determined by entropy was determined as an independent factor in multivariate analysis (hazard ratio 7.48, p = .016). Overall survival was not significantly correlated to any examined parameter, most likely due to the high comorbidity in our cohort. CONCLUSIONS: Our study adds to the growing evidence that tumor heterogeneity as described by FDG-PET texture is associated with response to radiation therapy in NSCLC. The results may be helpful into identifying patients who might profit from an intensified treatment regime, but need to be verified in a prospective patient cohort before being incorporated into routine clinical practice.

Prognostic value of positron emission tomography-assessed tumor heterogeneity in patients with thyroid cancer undergoing treatment with radiopeptide therapy.

INTRODUCTION: Peptide receptor radionuclide therapy (PRRT) is a treatment option for both iodine-refractory differentiated and advanced medullary thyroid cancer (TC). It requires over-expression of somatostatin receptor subtype II (SSTR) that can be non-invasively assessed by positron emission tomography (PET). Assessment of tumor heterogeneity is increasingly used as a tool for prognostication prediction. We investigated the potential of SSTR-PET to assess intraindividual tumor heterogeneity and thereby treatment response prior to PRRT. METHODS: 12 patients with progressive radioiodine-refractory differentiated (1 papillary, 1 oxyphilic, 2 oncocytic, 4 follicular) or medullary (n=4) TC were enrolled. SSTR-PET was performed at baseline. Conventional PET parameters and heterogeneity parameters were analyzed regarding their potential to predict progression-free (PFS, mean, 221 days) and overall survival (OS, mean, 450 days). Parameters of a subgroup of lesions (n=23) were also correlated with morphological response according to modified RECIST criteria. RESULTS: In patient-based analysis, all conventional parameters failed to predict PFS. Several textural parameters showed a significant capability to assess PFS. Thereby, "Grey level non uniformity" had the highest area under the curve (AUC, 0.93) in Receiver operating characteristics analysis followed by "Contrast" (AUC, 0.89). In lesion-based analysis, only "Entropy" revealed potential to evaluate disease progression. OS could not be assessed by any parameter investigated. CONCLUSIONS: Tumor heterogeneity seems to be a predictor of response to PRRT in patients with iodine-refractory differentiated/advanced medullary thyroid cancer and outperforms conventional PET parameters like standardized uptake value. In a "theranostic" approach, assessment of textural parameters may help in selecting patients who might benefit from PRRT.

Textural Parameters of Tumor Heterogeneity in ¹8F-FDG PET/CT for Therapy Response Assessment and Prognosis in Patients with Locally Advanced Rectal Cancer.

UNLABELLED: (18)F-FDG PET/CT is effective in the assessment of therapy response. Changes in glucose uptake or tumor size are used as a measure. Tumor heterogeneity was found to be a promising predictive and prognostic factor. We investigated textural parameters for their predictive and prognostic capability in patients with rectal cancer using histopathology as the gold standard. In addition, a comparison to clinical outcome was performed. METHODS: Twenty-seven patients with rectal cancer underwent (18)F-FDG PET/CT before, 2 wk after the start, and 4 wk after the completion of neoadjuvant chemoradiotherapy. In all PET/CT scans, conventional parameters (tumor volume, diameter, maximum and mean standardized uptake values, and total lesion glycolysis [TLG]) and textural parameters (coefficient of variation [COV], skewness, and kurtosis) were determined to assess tumor heterogeneity. Values on pretherapeutic PET/CT as well as changes early in the course of therapy and after therapy were compared with histopathologic response. In addition, the prognostic value was assessed by correlation with time to progression and survival time. RESULTS: The COV showed a statistically significant capability to assess histopathologic response early in therapy (sensitivity, 68%; specificity, 88%) and after therapy (79% and 88%, respectively). Thereby, the COV had a higher area under the curve in receiver-operating-characteristic analysis than did any analyzed conventional parameter for early and late response assessment. The COV showed a statistically significant capability to evaluate disease progression and to predict survival, although the latter was not statistically significant. CONCLUSION: Tumor heterogeneity assessed by the COV, being superior to the investigated conventional parameters, is an important predictive factor in patients with rectal cancer. Furthermore, it can provide prognostic information. Therefore, its application is an important step for personalized treatment of rectal cancer.

PET-CT based automated lung nodule detection.

An automatic method is presented in order to detect lung nodules in PET-CT studies. Using the foreground and background mean ratio independently in every nodule, we can detect the region of the nodules properly. The size and intensity of the lesions do not affect the result of the algorithm, although size constraints are present in the final classification step. The CT image is also used to classify the found lesions built on lung segmentation. We also deal with those cases when nearby and similar nodules are merged into one by a split-up post-processing step. With our method the time of the localization can be decreased from more than one hour to maximum five minutes. The method had been implemented and validated on real clinical cases in Interview Fusion clinical evaluation software (Mediso). Results indicate that our approach is very effective in detecting lung nodules and can be a valuable aid for physicians working in the daily routine of oncology.

Automated material map generation from MRI scout pairs for preclinical PET attenuation correction.

A novel method is presented to perform material map segmentation from preclinical MRI for corresponding PET attenuation correction. MRI does not provide attenuation ratio, hence segmenting a material map from it is challenging. Furthermore the MRI images often suffer from ghost artifacts. On the contrary MRI has no radiation dose. Our method operated with fast spin echo scout pairs that had perpendicular frequency directions. This way the direction of the ghost artifacts were perpendicular as well. Our body-air segmentation method built on this a priori information and successfully erased the ghost artifacts from the final binary mask. Visual and quantitative validation was performed by two preclinical specialists. Results indicate that our method is effective against MRI scout ghost artifacts and that PET attenuation correction based on MRI makes sense even on preclinical images.

New workflows and algorithms of bone scintigraphy based on SPECT-CT.

Gold standard bone scintigraphy workflow contains acquisition of planar anterior and posterior images and if necessary, additional SPECTs as well. Planar acquisitions are time consuming and not enough for accurately locating hotspots. Current paper proposes a novel workflow for fast whole body bone SPECT scintigraphy. We present a novel stitching method to generate a whole body SPECT based on the SPECT projections. Our stitching method is performed on the projection series not on the reconstructed SPECTs, thus stitching artifacts are greatly reduced. Our workflow does not require any anterior-posterior image pairs, since these images are derived from the reconstructed whole body SPECT automatically. Our stitching method has been validated on real clinical data performed by medical physicians. Results show that our method is very effective for whole body SPECT generations leaving no signs of artifacts. Our workflow required overall 16 minutes to acquire a whole body SPECT which is comparable to the 60 minutes acquisition time required for gold standard techniques including planar images and additional SPECT acquisitions.

Automated patient couch removal algorithm on CT images.

The current paper proposes a novel automated patient couch removal method on Computed Tomography (CT) images. Patient couch is often considered to be an unnecessary artifact especially when 3D rendered techniques are used. The method is based on measuring similarity between selected axial slices and the assumption that the bed object is constant on different slices. Due to the weight of the patient the couch could bend which is identifiable as sagittal movement on consecutive axial slices. Therefore the method focuses on finding this movement after an initial segmentation. According to initial validation performed on real medical data, our method is an effective tool to remove patient couch without user interaction.

An extended registration framework for the triple registration of IBZM SPECT, DATSCAN SPECT and MRI brain images to support the evaluation of brain dopamine receptor scintigraphies.

An extended registration model is presented to register medical image triples acquired for brain dopamine receptor scintigraphies. The model operates with rigid and nonlinear transformations in parallel, where all transformation parameters are optimized by one optimization method. The concept of the transformation-sampling-similarity measurement minimizes the memory usage of a real implementation. A partial-fine sampling method is proposed to decrease the processing time of the registration. Real medical data was collected to compare our method with well-known prior ones. The first tests show that the model outperforms the classic registration methods in both speed and accuracy.

Hextuple registration of interim and follow-up PET-CT images for the accurate tracking of patient recovery after therapy.

An extended registration framework is presented to accurately register follow-up PET-CT study triples. Since there are six images to register, sophisticated feature extraction and similarity measurement methods are proposed. An irregular sampling method is introduced to decrease the processing speed of the hextuple registration. The similarity measurement is based on a normalized hybrid extended SSD (Sum of Squared Differences) and and extended NMI (Normalized mutual Information). The method has been tested on a huge amount of simulated data to avoid observer specific results. Based on the validation, our method outperforms prior solutions in both speed and accuracy, hence it should be the subject of further investigations.

Automated lymph node detection and classification on breast and prostate cancer SPECT-CT images.

We present a novel detection and classification method to process SPECT-CT images representing breast and prostate lymph nodes. Lymph nodes are those nodes that are near the primer tumor and may become cancerous in time, hence their early detection is a key factor for the successful treatment of the patient. Prior methods focus on the visual aid to manually detect the lymph nodes which still makes the process time-consuming. Other solutions segment the lymph nodes only on CT, where the small lymph nodes may not be located accurately. Our solution processed both SPECT and CT data to provide an accurate classification of all SPECT hot spots. The method has been validated on a huge amount of medical data. Results show that our method is a very effective tool to support physicians working with related images in the field of nuclear medicine.

Parallel registration of multi-modal medical image triples having unknown inter-image geometry.

A method is proposed to register three multimodal medical data, where none of the images are superimposed. Contrary to previously presented solutions that perform more simultaneous registrations after one-by-one, present method registers all images in parallel. The method minimizes the registration error by seeking the optimum of a vector including rigid transformation parameters of both reslice images. To measure the similarity among all three images, a higher dimensional extended normalized mutual information have been adopted. Comparison with simultaneous methods have been performed on brain and femoral multi-modal image triples. Based on the comparative results, presented parallel method significantly outperforms the simultaneous methods in both translation and rotation registration error minimizations. On the contrary, the simultaneous methods need less computational time to converge.