Detection Of Lesions In Patients Research Articles

Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study

PurposeTo assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC). MethodsThis single-center prospective study enrolled consecutive at-risk participants who underwent 3.0 T gadoxetate disodium-enhanced MRI. Conventional DWI was acquired using parallel imaging (PI) with SENSE (PI-DWI). In CS-DWI and DL-CS-DWI, CS but not PI with SENSE was used to accelerate the scan with 2.5 as the acceleration factor. Qualitative and quantitative image quality were independently assessed by two masked reviewers, and were compared using the Wilcoxon signed-rank test. The detection rates of clinically-relevant (LR-4/5/M based on the Liver Imaging Reporting and Data System v2018) liver lesions for each DWI sequence were independently evaluated by another two masked reviewers against their consensus assessments based on all available non-DWI sequences, and were compared by the McNemar test. Results67 participants (median age, 58.0 years; 56 males) with 197 clinically-relevant liver lesions were enrolled. Among the three DWI sequences, DL-CS-DWI showed the best qualitative and quantitative image qualities (p range, <0.001–0.039). For clinically-relevant liver lesions, the detection rates (91.4%–93.4%) of DL-CS-DWI showed no difference with CS-DWI (87.3%–89.8%, p = 0.230–0.231) but were superior to PI-DWI (82.7%–85.8%, p = 0.015–0.025). For lesions located in the hepatic dome, DL-CS-DWI demonstrated the highest detection rates (94.8%–97.4% vs 76.9%–79.5% vs 64.1%–69.2%, p = 0.002–0.045) among the three DWI sequences. ConclusionIn patients at high-risk for HCC, DL-CS-DWI improved image quality and detection for clinically-relevant liver lesions, especially for the hepatic dome.

Automated Detection of Lesions in Patients with Traumatic Brain Injury using Brain CT Images: Concept Note and Proposed Method

AbstractAccurate and early interpretation of CT scan images in TBI patients reduces the critical time for diagnosis and management. As mentioned in other studies, automated CT interpretation using the feature extraction method is a rapid and accurate tool. Despite several studies on the machine and deep learning employing algorithms for automated CT interpretations, it has its challenges. This study presents a concept note and proposes a feature-based computer-aided diagnostic method to perform automated CT interpretation in TBI. The method consists of preprocessing, segmentation, and extraction. We have described a simple way of classifying the CT scan head into five circumferential zones in this method. The zones are identified quickly based on the anatomic characteristics and specific pathologies that affect each zone. Then, we have provided an overview of different pathologies affecting each of these zones. Utilizing these zones for automated CT interpretation will also be a helpful resource for concerned physicians during the odd and rush hours.

Using a classification model for determining the value of liver radiological reports of patients with colorectal cancer.

Medical imaging is critical in clinical practice, and high value radiological reports can positively assist clinicians. However, there is a lack of methods for determining the value of reports. The purpose of this study was to establish an ensemble learning classification model using natural language processing (NLP) applied to the Chinese free text of radiological reports to determine their value for liver lesion detection in patients with colorectal cancer (CRC). Radiological reports of upper abdominal computed tomography (CT) and magnetic resonance imaging (MRI) were divided into five categories according to the results of liver lesion detection in patients with CRC. The NLP methods including word segmentation, stop word removal, and n-gram language model establishment were applied for each dataset. Then, a word-bag model was built, high-frequency words were selected as features, and an ensemble learning classification model was constructed. Several machine learning methods were applied, including logistic regression (LR), random forest (RF), and so on. We compared the accuracy between priori choosing pertinent word strings and our machine language methodologies. The dataset of 2790 patients included CT without contrast (10.2%), CT with/without contrast (73.3%), MRI without contrast (1.8%), and MRI with/without contrast (14.6%). The ensemble learning classification model determined the value of reports effectively, reaching 95.91% in the CT with/without contrast dataset using XGBoost. The logistic regression, random forest, and support vector machine also achieved good classification accuracy, reaching 95.89%, 95.04%, and 95.00% respectively. The results of XGBoost were visualized using a confusion matrix. The numbers of errors in categories I, II and V were very small. ELI5 was used to select important words for each category. Words such as "no abnormality", "suggest", "fatty liver", and "transfer" showed a relatively large degree of positive correlation with classification accuracy. The accuracy based on string pattern search method model was lower than that of machine learning. The learning classification model based on NLP was an effective tool for determining the value of radiological reports focused on liver lesions. The study made it possible to analyze the value of medical imaging examinations on a large scale.

Identifying Enhancing Tumour Without Contrast-Enhanced Imaging

Abstract AIMS Brain tumours are heterogenous entities comprising multiple broad tissue sub-types when imaged with MRI. Delineating the enhancing tumour component is vital for neuro-oncological therapeutic planning, to-date only demonstrable with contrast-enhanced imaging. But not all patients can undergo this necessary contrast-enhanced acquisition, whether due to allergy, renal impairment, or scanning acquisition parameters. We therefore evaluated how well fully convolutional deep learning models identify a patient’s enhancing tumour when contrast-enhanced imaging was not available. METHOD We constructed a suite of deep-learning models to segment brain tumours when contrast-enhanced imaging was missing. Specifically, we developed all possible combinations of other structural sequences being provided, including T1-weighted, T2-weighted and FLAIR. Models were trained and tested with five-fold cross-validation on the 2021 BraTS-RSNA glioma population of 1251 patients, with additional out-of-sample validation with neuroradiologist hand-labelled lesions from our own centre. RESULTS Models missing post-contrast imaging still achieved a Dice coefficient for the whole tumour of 0.942. Model performances for identifying enhancing-tumour – despite no contrast-enhanced imaging being provided to the model – ranged from Dice coefficients of 0.759 (single sequence model) to 0.790 (three sequence T1 + T2 + FLAIR model). Moreover, models lacking contrast-enhanced imaging still robustly quantified the volume of enhancing tumour (R2 range 0.953-0.976). CONCLUSION Models missing contrast-enhanced imaging still identify both whole lesions and enhancing tumour components, and accurately quantifying the enhancing volumetric burden. These models provide opportunity for lesion detection in patients or clinical situations in which contrast-enhanced imaging cannot be acquired, and challenge the current nosology of defining ‘enhancing tumour’.

The Value of Multimodality PET/CT Imaging in Detecting Prostate Cancer Biochemical Recurrence.

Prostate cancer (PCa) induced death is the predominant cause of cancer-related death among men in 48 countries. After radical treatment, biochemical recurrence has become an important factor for prognosis. The early detection and diagnosis of recurrent lesions are very helpful in guiding treatment and improving the prognosis. PET/CT is a promising method for early detection of lesions in patients with biochemical recurrence of prostate cancer. This article reviews the progress of the research on PET/CT in the PCa biochemical recurrence and aims to introduce new technologies and provide more direction for future research.

Intraoperative delineation of p16+ oropharyngeal carcinoma of unknown primary origin with fluorescence lifetime imaging: Preliminary report.

This study evaluated whether fluorescence lifetime imaging (FLIm), coupled with standard diagnostic workups, could enhance primary lesion detection in patients with p16+ head and neck squamous cell carcinoma of the unknown primary (HNSCCUP). FLIm was integrated into transoral robotic surgery to acquire optical data on six HNSCCUP patients' oropharyngeal tissues. An additional 55-patient FLIm dataset, comprising conventional primary tumors, trained a machine learning classifier; the output predicted the presence and location of HNSCCUP for the six patients. Validation was performed using histopathology. Among the six HNSCCUP patients, p16+ occult primary was surgically identified in three patients, whereas three patients ultimately had no identifiable primary site in the oropharynx. FLIm correctly detected HNSCCUP in all three patients (ROC-AUC: 0.90 ± 0.06), and correctly predicted benign oropharyngeal tissue for the remaining three patients. The mean sensitivity was 95% ± 3.5%, and specificity 89% ± 12.7%. FLIm may be a useful diagnostic adjunct for detecting HNSCCUP.

Diagnostic accuracy of double inversion recovery (DIR) in detection of cortical gray matter lesions in patients with MS

BackgroundConventional imaging techniques have a low sensitivity for detection of cortical and deep grey matter lesions in MS which hinder accurate assessment of the total lesion burden. Aim of this work was to assess the diagnostic accuracy of double inversion recovery (DIR) sequence in the detection of cortical grey matter lesions in MS patients.ResultsForty MS patients were prospectively included in this study. Imaging was performed using Philips Ingenia 1.5 T device. The sensitivity, specificity, PPV, NPV and accuracy of DIR sequence in detection of cortical grey matter lesions were 60%, 100%, 100%, 55.6% and 73.3%, respectively. The sensitivity, specificity, positive and negative predictive values as well as accuracy of Flair sequence were 50%, 100%, 100%, 50% and 66.7%, respectively. The sensitivity, specificity, positive and negative predictive values as well as accuracy of T2 sequence in the detection of cortical grey matter lesions were 22.5%, 100%, 100%, 39.2% and 48.3%, respectively.ConclusionsDetection rate of cortical gray matter lesions was significantly higher on DIR sequence than on T2 and Flair sequences.

Clinical yield of screening colonoscopies in Jamaica.

There is still no organised national screening programme for colorectal cancer in Jamaica. We sought to evaluate the detection of colorectal cancer precursor lesions in patients who underwent opportunistic screening over three years. Patients with colorectal polyps were selected for further study. In 431 procedures, there were 84 (19.5%) patients with colorectal polyps identified at screening colonoscopy, which gave a 19.5% sensitivity to identify patients with polyps at risk of developing colorectal cancer, 9.5% being <50 years of age. At the time of examination, 16.7% had already developed invasive adenocarcinoma. We conclude that it is time for policy makers to develop a national colorectal cancer screening programme to diagnose patients early and improve their therapeutic outcomes.

Novel ECG features and machine learning to optimize culprit lesion detection in patients with suspected acute coronary syndrome

BackgroundNovel temporal-spatial features of the 12‑lead ECG can conceptually optimize culprit lesions' detection beyond that of classical ST amplitude measurements. We sought to develop a data-driven approach for ECG feature selection to build a clinically relevant algorithm for real-time detection of culprit lesion. MethodsThis was a prospective observational cohort study of chest pain patients transported by emergency medical services to three tertiary care hospitals in the US. We obtained raw 10-s, 12‑lead ECGs (500 s/s, HeartStart MRx, Philips Healthcare) during prehospital transport and followed patients 30 days after the encounter to adjudicate clinical outcomes. A total of 557 global and lead-specific features of P-QRS-T waveform were harvested from the representative average beats. We used Recursive Feature Elimination and LASSO to identify 35/557, 29/557, and 51/557 most recurrent and important features for LAD, LCX, and RCA culprits, respectively. Using the union of these features, we built a random forest classifier with 10-fold cross-validation to predict the presence or absence of culprit lesions. We compared this model to the performance of a rule-based commercial proprietary software (Philips DXL ECG Algorithm). ResultsOur sample included 2400 patients (age 59 ± 16, 47% female, 41% Black, 10.7% culprit lesions). The area under the ROC curves of our random forest classifier was 0.85 ± 0.03 with sensitivity, specificity, and negative predictive value of 71.1%, 84.7%, and 96.1%. This outperformed the accuracy of the automated interpretation software of 37.2%, 95.6%, and 92.7%, respectively, and corresponded to a net reclassification improvement index of 23.6%. Metrics of ST80; Tpeak-Tend; spatial angle between QRS and T vectors; PCA ratio of STT waveform; T axis; and QRS waveform characteristics played a significant role in this incremental gain in performance. ConclusionsNovel computational features of the 12‑lead ECG can be used to build clinically relevant machine learning-based classifiers to detect culprit lesions, which has important clinical implications.

El valor de la gammagrafía paratiroidea en la detección de lesiones en pacientes con hiperparatiroidismo primario normocalcémico

ObjectivePrimary hyperparathyroidism (PHPT) is one of the most frequent endocrine diseases. Most of the patients with PHPT are asymptomatic, and only 20% of them become symptomatic with increasing levels of calcium. It has been reported that normocalcemic primary hyperparathyroidism (NPHPT) may be the incipient period of PHPT where calcium (Ca) levels are in normal range, and it may advance to overt PHPT. Early diagnosis of PHPT is important in order to prevent its complications. In this retrospective study, we aimed to evaluate the role of 99mTc-MIBI parathyroid scintigraphy on lesion detection in patients with NPHPT. Material and methodsThe parathyroid scintigraphy database was reviewed retrospectively in patients with PHPT. 117 patients who underwent 99mTc-MIBI scintigraphy were recruited to the study. Serum calcium level above 10.5mg/dl was considered as hypercalcemia. ResultsA total of 117 patients’ (female/male:98/19) mean serum PTH levels (mean±SD) were 149±97 pg/ml in normocalcemic group (Ca:9.6±0.6mg/dL, n:38) and 189±135 pg/ml in hypercalcemic group (Ca:11.4±0.6mg/dL, n:79) (p:0.072). The sex and ages were not different between the scintigraphy positive and negative groups, but the lesion detection rates with parathyroid scintigraphy were 42% in normocalcemic group and 81% in hypercalcemic group (p<0.0001). ConclusionsSeveral factors including serum Ca, the imaging protocol, existence of multiglandular disease, the size and MIBI biokinetics of the adenoma may influence lesion detectability in parathyroid scintigraphy. Although high serum Ca level is an important parameter in predicting its success, parathyroid scintigraphy remains a valuable diagnostic method even in patients with NPHPT.

Added Value of CT Pelvic Bone Unfolding Software to Radiologist Performance in Detecting Osteoblastic Pelvic Bone Lesions in Patients With Prostate Cancer

Purpose: To evaluate the contribution of CT Bone Unfolding software to the diagnostic accuracy and efficiency for the detection of osteoblastic pelvic bone lesions in patients with prostate cancer. Methods: A total of 102 consecutive (January 2016-September 2019) patients who underwent abdominopelvic CT with prostate cancer were retrospectively evaluated for osteoblastic pelvic bone lesions, using commercially available the post-processing-pelvic bone flattening-image software package “CT Bone Unfolding.” Two radiologists with 3 and 15 years of experience in abdominal radiology evaluated CT image data sets independently in 2 separate reading sessions. At the first session, only MPR images and at the second session MPR images and additionally unfolded reconstructions were assessed. Reading time for each patient was noted. A radiologist with 25 years of experience, established the standard of reference. Results: In the evaluations performed with the MPR-Unfold method, the diagnostic accuracy were found to be 2.067 times higher compared to the MPRs method ( P &lt; 0.001). The location of the lesions or the reader variabilities did not show any influence on accuracy ( P &gt; 0.05) For all readers the reading time for MPR was significantly longer than for MPR-Unfold ( P &lt; 0.05). For both methods substantial to almost-perfect inter-reader agreement was found (0.686-0.936). Conclusions: The use of unfolded pelvic bone reconstructions increases diagnostic accuracy while decreasing the reading times in the evaluation of pelvic bone lesions. Therefore, our findings suggest that utilizing unfolded reconstructions in addition to MPR images may be preferable in patients with prostate cancer for the screening of osteoblastic pelvic bone lesions.

The value of parathyroid scintigraphy on lesion detection in patients with normocalcemic primary hyperparathyroidism

ObjectivePrimary hyperparathyroidism (PHPT) is one of the most frequent endocrine diseases. Most of the patients with PHPT are asymptomatic, and only 20% of them become symptomatic with increasing levels of calcium. It has been reported that normocalcemic primary hyperparathyroidism (NPHPT) may be the incipient period of PHPT where calcium (Ca) levels are in normal range, and it may advance to overt PHPT. Early diagnosis of PHPT is important in order to prevent its complications. In this retrospective study, we aimed to evaluate the role of 99mTc-MIBI parathyroid scintigraphy on lesion detection in patients with NPHPT. Material and methodsThe parathyroid scintigraphy database was reviewed retrospectively in patients with PHPT. 117 patients who underwent 99mTc-MIBI scintigraphy were recruited to the study. Serum calcium level above 10.5mg/dl was considered as hypercalcemia. ResultsA total of 117 patients (female/male:98/19) mean serum PTH levels (mean±SD) were 149±97pg/ml in normocalcemic group (Ca:9.6±0.6mg/dl, n:38) and 189±135pg/ml in hypercalcemic group (Ca:11.4±0.6mg/dl, n:79) (p:0.072). The sex and ages were not different between the scintigraphy positive and negative groups, but the lesion detection rates with parathyroid scintigraphy were 42% in normocalcemic group and 81% in hypercalcemic group (p<0.0001). ConclusionsSeveral factors including serum Ca, the imaging protocol, existence of multiglandular disease, the size and MIBI biokinetics of the adenoma may influence lesion detectability in parathyroid scintigraphy. Although high serum Ca level is an important parameter in predicting its success, parathyroid scintigraphy remains a valuable diagnostic method even in patients with NPHPT.

Clinical verification of 18F-DCFPyL PET-detected lesions in patients with biochemically recurrent prostate cancer.

PurposeRadiolabeled Prostate-Specific Membrane Antigen (PSMA) PET/CT is the current standard-of-care for lesion detection in patients with biochemically recurrent (BCR) prostate cancer (PCa). However, rigorous verification of detected lesions is not always performed in routine clinical practice. To aid future 18F-radiolabeled PSMA PET/CT interpretation, we aimed to identify clinical/imaging characteristics that increase the likelihood that a PSMA-avid lesion is malignant.Materials and methods262 patients with BCR, who underwent 18F-DCFPyL PSMA PET/CT, were retrospectively analyzed. The malignant nature of 18F-DCFPyL PET-detected lesions was verified through any of the following metrics: (1) positive histopathological examination; (2) additional positive imaging; (3) a ≥50% decrease in Prostate-Specific Antigen (PSA) following irradiation of the lesion(s).ResultsIn 226/262 PET scans (86.3%) at least one lesion suspicious for recurrent PCa was detected (‘positive scan’). In 84/226 positive scans (37.2%), at least one independent verification metric was available. PSMA PET-detected lesions were most often confirmed to be malignant (PCa) in the presence of a CT-substrate (96.5% vs. 55.6% without CT-substrate), with SUVpeak ≥3.5 (91.4% vs. 60.0% with SUVpeak<3.5), in patients with a PSA-level ≥2.0 ng/mL (83.7% vs. 65.7% in patients with PSA <2.0ng/mL) and in patients with >2 PET-positive lesions (94.1% vs. 64.2% in patients with 1–2 PET-positive lesions; p<0.001–0.03).ConclusionsIn this study, the clinical verification of 18F-DCFPyL PET-positive lesions in patients with BCR was performed. Diagnostic certainty of PET-detected lesions increases in the presence of characteristic abnormalities on CT, when SUVpeak is ≥3.5, when PSA-levels exceed 2.0 ng/mL or in patients with more than two PET-positive lesions.

Simultaneous multi-slice accelerated diffusion-weighted imaging with higher spatial resolution for patients with liver metastases from neuroendocrine tumours

To evaluate the imaging characteristics of simultaneous multi-slice (SMS) accelerated diffusion-weighted imaging (DWI) with decreased section thickness, with and without motion correction, in comparison to conventional DWI (cDWI) for the detection of lesions in patients with neuroendocrine tumour (NET) liver metastases. Fifteen patients with NET liver metastases underwent cDWI (section thickness [SL]=4 mm) and SMS-DWI (SL=2 mm). Non-linear motion-corrected (Moco)-SMS-DWI was generated in addition to the original series. Qualitative imaging characteristics (five-point Likert scale), the number of high signal lesions, and the detectability and delineation of lesions were evaluated and compared using the Friedman and the Dunn-Bonferroni tests. The test-retest variability (TRV) of the cDWI and SMS-DWI techniques was investigated among 11 healthy volunteers who underwent cDWI (SL=4 mm) and SMS-DWI (SL=4 mm) twice. The Friedman and the Dunn-Bonferroni post-hoc tests were used to compare the mean apparent diffusion coefficient (ADC) and the TRV in different liver regions between the three series. Moco-SMS-DWI demonstrated significantly superior overall image quality (p<0.001) with significantly fewer artefacts (p=0.003) than cDWI. The number of lesions detected by cDWI, SMS-DWI, and Moco-SMS-DWI were 348, 504, and 523, respectively. The detectability and delineation of the lesions and the ADC values were significantly higher on the SMS-DWI and Moco-SMS-DWI images than on the cDWI images (all p<0.001). Moco-SMS-DWI showed significantly higher TRV than cDWI in regions near the liver edge (p=0.018). SMS-DWI achieves higher spatial resolution than cDWI within the same acquisition time, detects more lesions, and provides better lesion delineation. By applying motion correction, the TRV of DWI could be enhanced in regions near the liver edge.

Comparative study between double inversion recovery (DIR) and fluid-attenuated inversion recovery (FLAIR) MRI sequences for detection of cerebral lesions in multiple sclerosis

BackgroundMultiple sclerosis (MS) is a common chronic inflammatory demyelinating disorder more common in young adults. MS is characterized mainly with white matter (WM) affection; however, considerable gray matter (GM) involvement is also noted in many patients. MRI is used for diagnosis and follow up of the disease using different pulse sequences; FLAIR imaging provides the highest sensitivity in the detection of supratentorial, juxtacortical, and the periventricular lesions but is less sensitive in the posterior fossa. A double inversion recovery (DIR) pulse sequence was recently introduced to improve the visibility of GM lesions and especially cortical lesions. The aim of this study is to assess the role of DIR sequence in the detection of brain lesions in patients with MS compared to FLAIR sequence.ResultsDIR showed a significantly higher number of MS lesions in infratentorial region (2.9 ± 0.4 compared to 2.25 ± 0.3 in FLAIR) with a statistically significant difference (p = 0.002) and also in supratentorial periventricular regions (11.84 ± 8.07 in DIR and 11.31 ± 8.07 in FLAIR, p < 0.001). DIR imaging also demonstrated significantly more intracortical lesions (7.12 ± 1.2 compared to 1.4 ± 0.9 in FLAIR imaging) with a statistically significant difference (p < 0.001). On the other hand, corpus callosum lesions were significantly higher on FLAIR (0.84 ± 0.1) with respect to DIR imaging (0.68 ± 0.1) with a statistically significant difference in between (p = 0.025).ConclusionDIR is a powerful conventional MRI sequence for visualization of brain lesions in patients with MS and is superior to FLAIR sequence in detecting lesions in different locations, namely cortical, periventricular, and infratentorial regions; hence, DIR can be added to the MRI protocol of MS patients or even can replace FLAIR which would be of a good diagnostic value with only 80 s added to the scan time.

How fast can we scan patients with modern (digital) PET/CT systems?

PurposeTo seek for the minimal duration per bed position with a digital PET system without compromising image quality and lesion detection in patients requiring fast 18F-FDG PET imaging. Materials and methods19 cancer patients experiencing pain or dyspnea and 9 pediatric patients were scanned on a Vereos system. List mode data were reconstructed with decreasing time frame down to 10 s per bed position. Noise was evaluated in the liver, blood pool and muscle, and using target-to-background ratios. Five PET readers recorded image quality, number of clinically relevant foci and of involved anatomical sites in reconstructions ranging from 60 to 10 s per bed position, compared to the standard 90 s reconstruction. ResultsThe following reconstructions, which harboured a noise not significantly higher than that of the standard reconstruction, were selected for clinical evaluation: 1iterations/10 subsets/20sec (1i10 s20sec), 1i10 s30sec, and 2i10 sPSF60sec.Only the 60 s per bed acquisition displayed similar target-to-background ratios compared to the standard reconstruction, but mean ratios were still higher than 2.0 for the 30 s reconstruction. Inter-rater agreement for the number of involved anatomical sites and detected lesion was good or almost perfect (Kappa: 0.64−0.91) for all acquisitions. In particular, kappa for the 30 s per bed acquisition was 0.78 and 0.91 for lesion and anatomical sites number, respectively. Intra-rater agreement was also excellent for the 30 s reconstruction (kappa = 0.72). Median estimated total PET acquisition time for the 1i10 s30sec, and the standard reconstruction were 4 and 12 min, respectively. ConclusionsFast imaging is feasible with state-of-the-art PET systems. Acquisitions of 30 s per bed position are feasible with the Vereos system, requiring optimization of reconstruction parameters.

64Cu-DOTATATE PET in Patients with Neuroendocrine Neoplasms: Prospective, Head-to-Head Comparison of Imaging at 1 Hour and 3 Hours After Injection

64Cu-DOTATATE PET/CT imaging 1 h after injection is excellent for lesion detection in patients with neuroendocrine neoplasms (NENs). We hypothesized that the imaging time window can be extended up to 3 h after injection without significant differences in the number of lesions detected. Methods: From a prospective study, we compared, on a head-to-head basis, sets of 64Cu-DOTATATE PET/CT images from 35 patients with NENs scanned 1 and 3 h after injection of 200 MBq of 64Cu-DOTATATE. The number of lesions on both PET scans was counted and grouped according to organs or regions and compared with negative binomial regression. Discordant lesions (visible on only the 1-h images or only the 3-h 64Cu-DOTATATE PET images) were considered true if found on simultaneous CT or later MR, CT, or somatostatin receptor imaging. We measured lesion SUVmax, reference normal-organ or -tissue SUVmean, and tumor-to-normal-tissue ratios calculated from SUVmax and SUVmean Results: We found 822 concordant lesions (visible on both 1-h and 3-h 64Cu-DOTATATE PET) and 5 discordant lesions, of which 4 were considered true. One discordant case in 1 patient involved a discordant organ system (lymph node) detected on 3-h but not 1-h 64Cu-DOTATATE PET that did not alter the patient's disease stage (stage IV) because the patient had 11 additional concordant liver lesions. We found no significant differences between the number of lesions detected on 1-h and 3-h 64Cu-DOTATATE PET. Throughout the 1- to 3-h imaging window, the mean tumor-to-normal-tissue ratio remained high in all key organs: liver (1 h: 12.6 [95% confidence interval (CI), 10.2-14.9]; 3 h: 11.0 [95%CI, 8.7-13.4]), intestines (1 h: 24.2 [95%CI, 14.9-33.4]; 3 h: 28.2 [95%CI, 16.5-40.0]), pancreas (1 h: 42.4 [95%CI, 12.3-72.5]; 3 h: 41.1 [95%CI, 8.7-73.4]), and bone (1 h: 103.0 [95%CI, 38.6-167.4]; 3 h: 124.2 [95%CI, 57.1-191.2]). Conclusion: The imaging time window of 64Cu-DOTATATE PET/CT for patients with NENs can be expanded from 1 h to 1-3 h without significant differences in the number of lesions detected.

FASpecT/CT, A New SPECT/CT Acquisition With Higher Sensitivity and Efficiency in Radioiodine Thyroid Cancer Imaging.

This article demonstrates the use of a new SPECT/CT acquisition protocol in patients with differentiated thyroid cancer (DTC). SPECT/CT scans (FASpecT/CT) with fewer angle acquisitions were retrospectively reviewed in 30 DTC patients treated with radioiodine at University Hospital, San Antonio, Tex, from July 2017 to March 2019. This FASpecT/CT of 12 versus 60 to 64 sampled views for convention SPECT was made possible by iterative reconstruction. The FASpecT/CT protocol was judged to increase lesion detection in patients with low count rates. Furthermore, in patients with higher count rates, this technique reduced the acquisition time. FASpecT/CT patient images are shown as case examples in 4 of the 30 patients reviewed. This FASpecT/CT acquisition in radioiodine-treated DTC offers the potential of higher sensitivity for metastatic lymph node detection in low count rates and a significant decrease in imaging time in high count rates. These advantages make SPECT/CT imaging more acceptable for patients who have difficulty with longer imaging times, to include the pediatric population.

Use of a Risk Stratification Tool to Guide Evaluation of Patients With Asymptomatic Microscopic Hematuria

OBJECTIVETo determine if use of the hematuria risk index can reduce testing and cost, while maintaining equivalent lesion detection in patients with asymptomatic microscopic hematuria. MATERIALS AND METHODSRetrospective cohort study of 1049 patients at single institution. Hematuria risk index score was calculated based on clinical factors including age, sex, smoking history, and degree of hematuria for each patient along with evaluation studies performed and total number of tumors discovered. Cost benefit analysis was performed based on published Medicare averages. RESULTSTumor detection rate in overall, low-risk, and moderate-risk groups were 1.2%, 0%, and 2.96% at a total cost of $408,376. When low-risk group is not screened cost decreases to $166,252 with no lesions missed. The cost to discover one lesion/cancer in the overall group was $34,031.3, the cost to find one high-grade clinically significant lesion/cancer was $136,125.3 for the overall group. When the low-risk group was removed, the cost to find a high-grade clinically significant lesion/cancer decreased to $55,417.3 without missing any significant lesions. Ultrasound may be utilized instead of computed tomography with minimal loss of lesion detection in select moderate risk patients. CONCLUSIONNone of the low-risk hematuria risk patients were diagnosed with any lesions, as such these patients may not need an evaluation. Furthermore, by utilizing a risk-stratified approach to the assessment of asymptomatic microscopic hematuria health care costs can be significantly decreased with limited negative consequences in terms of lesion detection.

Second-look breast ultrasonography after galactography in patients with nipple discharge.

The objective of this study was to evaluate the diagnostic performance of second-look breast ultrasound (US) immediatelyafter galactography in patients with nipple discharge. Between January 2010 and November2018, 89 patients with nipple discharge were retrospectively analyzed. All patients were examined by galactography and US.US was performed twice, before and after galactography. Galactography, mammography and US findings were categorizedaccording to the Breast Imaging Reporting and Data System (BI-RADS). The final diagnosis was established by histopathologicalexamination. Out of 89 patients, 25 (28.1%) patients had positive findings as evident by US before galactography.Forty-eight (53.9%) patients had positive findings as demonstrated by galactography. Fifty-nine (66.3%) patients hadpositive findings as evident by second-look US after galactography (13 patients with benign, 37 with borderline and 9 withmalignant lesions). Second-look US after galactography showed the highest diagnostic accuracy (83.2%), sensitivity (95.8%)and negative predictive value (93.3%) for borderline and malignant lesions. For the detection of malignant lesions, secondlookUS after galactography showed the highest sensitivity (90%) and negative predictive value (96.7%). Agreement betweenimaging and histological result using Bland-Altman analysis exhibited no significant difference between the size establishedby ultrasound and galactography. The second-look US after galactography is a powerful diagnostic tool for thedetection of lesions in patients with nipple discharge and demonstrates high diagnostic accuracy, sensitivity and negativepredictive value.