Development and Validation of a Deep-Learning-Based Algorithm for Detecting and Classifying Metallic Implants in Abdominal and Spinal CT Topograms.

PURPOSE: To develop and validate a deep-learning-based algorithm (DLA) that is designed to segment and classify metallic objects in topograms of abdominal and spinal CT. METHODS: DLA training for implant segmentation and classification was based on a U-net-like architecture with 263 annotated hip implant topograms and 2127 annotated spine implant topograms. The trained DLA was validated with internal and external datasets. Two radiologists independently reviewed the external dataset consisting of 2178 abdomen anteroposterior (AP) topograms and 515 spine AP and lateral topograms, all collected in a consecutive manner. Sensitivity and specificity were calculated per pixel row and per patient. Pairwise intersection over union (IoU) was also calculated between the DLA and the two radiologists. RESULTS: The performance parameters of the DLA were consistently >95% in internal validation per pixel row and per patient. DLA can save 27.4% of reconstruction time on average in patients with metallic implants compared to the existing iMAR. The sensitivity and specificity of the DLA during external validation were greater than 90% for the detection of spine implants on three different topograms and for the detection of hip implants on abdominal AP and spinal AP topograms. The IoU was greater than 0.9 between the DLA and the radiologists. However, the DLA training could not be performed for hip implants on spine lateral topograms. CONCLUSIONS: A prototype DLA to detect metallic implants of the spine and hip on abdominal and spinal CT topograms improves the scan workflow with good performance for both spine and hip implants.

Quantitative Analysis of Prostate MRI: Correlation between Contrast-Enhanced Magnetic Resonance Fingerprinting and Dynamic Contrast-Enhanced MRI Parameters.

This research aimed to assess the relationship between contrast-enhanced (CE) magnetic resonance fingerprinting (MRF) values and dynamic contrast-enhanced (DCE) MRI parameters including (Ktrans, Kep, Ve, and iAUC). To evaluate the correlation between the MRF-derived values (T1 and T2 values, CE T1 and T2 values, T1 and T2 change) and DCE-MRI parameters and the differences in the parameters between prostate cancer and noncancer lesions in 68 patients, two radiologists independently drew regions-of-interest (ROIs) at the focal prostate lesions. Prostate cancer was identified in 75% (51/68) of patients. The CE T2 value was significantly lower in prostate cancer than in noncancer lesions in the peripheral zone and transition zone. Ktrans, Kep, and iAUC were significantly higher in prostate cancer than noncancer lesions in the peripheral zone (p < 0.05), but not in the transition zone. The CE T1 value was significantly correlated with Ktrans, Ve, and iAUC in prostate cancer, and the CE T2 value was correlated to Ve in noncancer. Some CE MRF values are different between prostate cancer and noncancer tissues and correlate with DCE-MRI parameters. Prostate cancer and noncancer tissues may have different characteristics regarding contrast enhancement.

Evaluation of Perfusion Change According to Pancreatic Cancer and Pancreatic Duct Dilatation Using Free-Breathing Golden-Angle Radial Sparse Parallel (GRASP) Magnetic Resonance Imaging.

PURPOSE: To evaluate perfusion changes in the pancreas with pancreatic cancer and pancreatic duct dilatation using dynamic contrast-enhanced MRI (DCE-MRI). METHOD: We evaluate the pancreas DCE-MRI of 75 patients. The qualitative analysis includes pancreas edge sharpness, motion artifacts, streak artifacts, noise, and overall image quality. The quantitative analysis includes measuring the pancreatic duct diameter and drawing six regions of interest (ROIs) in the three areas of the pancreas (head, body, and tail) and three vessels (aorta, celiac axis, and superior mesenteric artery) to measure the peak-enhancement time, delay time, and peak concentration. We evaluate the differences in three quantitative parameters among the ROIs and between patients with and without pancreatic cancer. The correlations between pancreatic duct diameter and delay time are also analyzed. RESULTS: The pancreas DCE-MRI demonstrates good image quality, and respiratory motion artifacts show the highest score. The peak-enhancement time does not differ among the three vessels or among the three pancreas areas. The peak-enhancement time and concentrations in the pancreas body and tail and the delay time in the three pancreas areas are significantly longer (p < 0.05) in patients with pancreatic cancer than in those without pancreatic cancer. The delay time was significantly correlated with the pancreatic duct diameters in the head (p < 0.02) and body (p < 0.001). CONCLUSION: DCE-MRI can display the perfusion change in the pancreas with pancreatic cancer. A perfusion parameter in the pancreas is correlated with the pancreatic duct diameter reflecting a morphological change in the pancreas.

Growth Pattern of Hepatic Metastasis as a Prognostic Index Reflecting Liver Metastasis-Associated Survival in Breast Cancer Liver Metastasis.

Breast cancer with liver metastasis (BCLM) frequently cause hepatic failure owing to extensive liver metastasis compared to other cancers; however, there are no clinicopathologic or radiologic parameters for estimating BCLM prognosis. We analyzed the relationship between radiologic and clinicopathologic characteristics with survival outcomes in BCLM. During 2009-2019, baseline and final abdomen computed tomography or liver magnetic resonance imaging of BCLM patients were reviewed. Liver metastasis patterns were classified as oligometastasis (≤3 metastatic lesions), non-confluent or confluent mass formation, infiltration, and pseudocirrhosis. Thirty-one surgical or biopsy specimens for liver metastasis were immunostained for L1 adhesion molecule (L1CAM), Yes-associated protein 1/Transcriptional co-activator with PDZ-binding motif (YAP/TAZ), and ß1-integrin. Out of 156 patients, 77 initially had oligometastasis, 58 had nonconfluent mass formation, 14 had confluent mass formation, and 7 had infiltrative liver metastasis. Confluent or infiltrative liver metastasis showed inferior liver metastasis-associated survival (LMOS) compared to others (p = 0.001). Positive staining for L1CAM and YAP/TAZ was associated with inferior survival, and YAP/TAZ was related to final liver metastasis. Initial hepatic metastasis was associated with LMOS, especially confluent mass formation, and infiltrative liver metastasis pattern was associated with poor survival. Positive staining for YAP/TAZ and L1CAM was associated with inferior LMOS, and YAP/TAZ was related to final liver metastasis.

The Image Quality and Diagnostic Performance of CT with Low-Concentration Iodine Contrast (240 mg Iodine/mL) for the Abdominal Organs.

Purpose: To evaluate the difference between CT examinations using 240 mgI/mL contrast material (CM) and 320 mgI/mL CM in the contrast enhancement of the abdominal organs and the diagnostic performance for focal hepatic lesions. Materials and methods: This retrospective study included 422 CT examinations, using 240 mgI/mL iohexol (Group A, 206 examinations) and 320 mgI/mL ioversol (Group B, 216 examinations), performed between April 2019 and May 2020. Two CT scanners (single-source CT (machine A) and dual-source CT (machine B)) were used to obtain CT images. Two radiologists independently drew regions of interest (ROIs) in the liver, pancreas, spleen, kidney, aorta, portal vein, and paraspinal muscle. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated for each organ. They evaluated the degree of subjective enhancement of the organs and detected/differentiated focal hepatic lesions. Results: The SNR, CNR, and subjective enhancement of most organs were significantly higher in Group B than in Group A (p < 0.05). The sensitivity and specificity for cysts and malignancy were higher than 85.0% in both groups. The sensitivity for hemangioma was lower in Group B (<75%) than in Group A. In Group A, the SNR and CNR were significantly higher in most organs with machine B than with machine A. Conclusion: Although the SNR and CNR of the abdominal organs were lower with 240 mgI/mL CM than with 320 mgI/mL CM, 240 mgI/mL CM was feasible for evaluating the liver. A CT scanner with more advanced specifications may be beneficial for examinations with 240 mgI/mL CM by using lower tube voltage.