Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma

PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10⁻³ mm²/s [range: (0.91 - 1.3) × 10⁻³ mm²/s] vs. [1.4 ± 0.2 (SD)] × 10⁻³ mm²/s [range: (1.1 - 1.6) × 10⁻³ mm²/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Reduced nontarget embolization and increased targeted delivery with a reflux-control microcatheter in a swine model

PurposeTo evaluate the potential differences in non-target embolization and vessel microsphere filling of a reflux-control microcatheter (RCM) compared to a standard end-hole microcatheter (SEHM) in a swine model.Materials and methodsRadiopaque microspheres were injected with both RCM and SEHM (2.4-Fr and 2.7-Fr) in the kidneys of a preclinical swine model. Transarterial renal embolization procedures with RCM or SEHM were performed in both kidneys of 14 pigs. Renal arteries were selectively embolized with an automated injection protocol of radio-opaque microspheres. Ex-vivo X-ray microtomography images of the kidneys were utilized to evaluate the embolization by quantification of the deposition of injected microspheres in the target vs. the non-target area of injection. X-ray microtomography images were blindly analyzed by five interventional radiologists. The degree of vessel filling and the non-target embolization were quantified using a scale from 1 to 5 for each parameter. An analysis of variance was used to compare the paired scores.ResultsTotal volumes of radio-opaque microspheres injected were similar for RCM (11.5 ± 3.6 [SD] mL; range: 6–17 mL) and SEHM (10.6 ± 5.2 [SD] mL; range: 4–19 mL) (P = 0.38). The voxels enhanced ratio in the target (T) vs. non-target (NT) areas was greater with RCM (T = 98.3% vs. NT = 1.7%) than with SEHM (T = 89% vs. NT = 11%) but the difference was not significant (P = 0.30). The total score blindly given by the five interventional radiologists was significantly different between RCM (12.3 ± 2.1 [SD]; range: 6–15) and the standard catheter (11.3 ± 2.5 [SD]; range: 4–15) (P = 0.0073), with a significant decrease of non-target embolization for RCM (3.8 ± 1.3 [SD]; range: 3.5–4.2) compared to SEHM (3.2 ± 1.5 [SD]; range: 2.9–3.5) (P = 0.014).ConclusionIn an animal model, RCM microcatheters reduce the risk of non-target embolization from 11% to 1.7%, increasing the delivery of microspheres of 98% to the target vessels, compared to SEHM microcatheters.     

Brain impedance variation of directional leads implanted in subthalamic nuclei of Parkinsonian patients

ObjectiveConventional deep brain stimulation (DBS) systems with ring-shaped leads generate spherical electrical fields. In contrast, novel directional leads use segmented electrodes. Aim of this study was to quantify the impedance variations over time in subjects with the directional Cartesia-Boston® system.MethodsImpedance records, programming settings, and clinical data of 11 consecutive Parkinsonian patients implanted with DBS directional leads in two Italian centers (Udine and Vicenza) were retrospectively evaluated. Data were collected before starting stimulation (in the operating room and at days 5 and 40) and after switching stimulation on at the successive follow-up visits (1, 6 and 12 months).ResultsDirectional leads have significantly higher impedance than ring leads. Stimulated contacts had always lower impedance compared to non-stimulated contacts. Before DBS-on, all contacts had higher impedance in the operating room, with an initial decrease five days post-surgery and a subsequent increase at day 40, more evident for directional contacts. The impedance of directional leads increased post-implantation at 1 and 6 months with a plateau at 12 months.ConclusionsThere was a significant difference between the directional and ring leads at baseline (before activation of DBS) and during follow-up (chronic DBS).SignificanceOur study reveals new information about the impedance of segmented electrodes that is useful for patient management during the initial test period, as well as during long-term DBS follow-up.