Differentiating between active and latent tuberculosis with chest computed tomography

PurposeThe purpose of this study was to evaluate the capabilities of chest computed tomography (CT) in distinguishing between active and latent tuberculosis in patients positive for interferon-gamma release assay (IGRA) testing, and to compare the performance of CT with that of quantitative IGRA testing in a low incidence setting.Materials and methodsPatients with latent or active tuberculosis define by an IGRA positive test were retrospectively recruited. Sensitivity, specificity and accuracy were determined for CT variables and quantitative IGRA results. Final diagnosis of active tuberculosis was based on clinical data and microbiological culture. Univariable and multivariable analyses were performed using logistic regression model to identify CT variables associated with the diagnosis of active tuberculosis.ResultsA total of 92 patients with positive IGRA results who underwent CT examination were included. There were 54 men and 38 women with a mean age of 53.5 ± 18 (SD) years (range: 40–68 years). Of them, 22 patients (24%) had positive Mycobacterium tuberculosis culture and 70 (76%) had latent tuberculosis. Among CT variables, consolidation had the greatest sensitivity (77%; 95%CI: 60–95%) and “tree-in-bud” the greatest specificity (97%; 95% CI: 93–100%) for the diagnosis of active tuberculosis. At univariable analysis “tree-in-bud”, splenic calcification and non-calcified lung nodules were the significant variables independently associated with active tuberculosis. At multivariable analysis, the adjusted odds ratio of “tree-in-bud” was 42.91 (95% CI: 5.62–327.42). Using an optimal threshold of 51 spots, quantitative IGRA yielded 64% sensitivity (95% CI: 44–84%) and 61% specificity (95% CI: 50–73%) for the diagnosis of active tuberculosis.ConclusionsIn a low incidence setting, chest CT, especially when “tree-in-bud” pattern is present, is superior to quantitative IGRA testing to identify patients with active tuberculosis among those with positive IGRA testing.     

Radiomics in the evaluation of lung nodules: Intrapatient concordance between full-dose and ultra-low-dose chest computed tomography

PurposeThe purpose of this study was to retrospectively evaluate the quantitative and qualitative intrapatient concordance of pulmonary nodule risk assessment by commercially available radiomics software between full-dose (FD) chest-CT and ultra-low-dose (ULD) chest CT.Materials and methodsBetween July 2013 and September 2015, 68 patients (52 men and16 women; mean age, 65.5 ± 10.6 [SD] years; range: 35–87 years) with lung nodules ≥ 5 mm and < 30 mm who underwent the same day FD chest CT (helical acquisition; 120 kV; automated tube current modulation) and ULD chest CT (helical acquisition; 135 kV; 10 mA fixed) were retrospectively included. Each nodule on each acquisition was assessed by a commercial radiomics software providing a similarity malignancy index (mSI), classifying it as “benign-like” (mSI < 0.1); “malignant-like” (mSI > 0.9) or “undetermined” (0.1 ≤ mSI ≤ 0.9). Intrapatient qualitative agreement was evaluated with weighted Cohen–Kappa test and quantitative agreement with intraclass correlation coefficient (ICC).ResultsNinety-nine lung nodules with a mean size of 9.14 ± 4.3 (SD) mm (range: 5–25 mm) in 68 patients (mean 1.46 nodule per patient; range: 1–5) were assessed; mean mSI was 0.429 ± 0.331 (SD) (range: 0.001–1) with FD chest CT (22/99 [22%] “benign-like”, 67/99 [68%] “undetermined” and 10/99 [10%] “malignant-like”) and mean mSI was 0.487 ± 0.344 (SD) (range: 0.002–1) with ULD chest CT (20/99 [20%] “benign-like”, 59/99 [60%] “undetermined” and 20/99 [20%] “malignant-like”). Qualitative and quantitative agreement of FD chest CT with ULD chest CT were “good” with Kappa value of 0.60 (95% CI: 0.46–0.74) and ICC of 0.82 (95% CI: 0.73–0.87), respectively.ConclusionA good agreement in malignancy similarity index can be obtained between ULD chest CT and FD chest CT using radiomics software. However, further studies must be done with more case material to confirm our results and elucidate the diagnostic capabilities of radiomics software using ULD chest CT for lung nodule characterization by comparison with FD chest CT.     

Clinical application of axillary reverse mapping in patients with breast cancer: A systematic review and meta-analysis

BackgroundThe axillary reverse mapping (ARM) technique, identify and preserve arm nodes during sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND), was developed to prevent breast-cancer related lymphedema (BCRL) remains controversial.MethodsA comprehensive search of Medline Ovid, Pubmed, Web of Science and the Cochrane CENTRAL databases was conducted from the inception till January 2020. The key word including “breast cancer”, “axillary reverse mapping”, and “lymphedema”. Stata 15.1 software was used for the meta-analysis.ResultsAs a result, twenty-nine related studies involving 4954 patients met our inclusion criteria. The pooled overall estimate lymphedema incidence was 7% (95% CI 4%–11%, I² = 90.35%, P < 0.05), with SLNB showed a relatively lower pooled incidence of lymphedema (2%, 95% CI 1%–3%), I² = 26.06%, P = 0.23) than that of ALND (14%, 95% CI 5%–26%, I² = 93.28%, P < 0.05) or SLNB and ALND combined (11%, 95% CI 1%–30%). The ARM preservation during ALND procedure could significantly reduce upper extremity lymphedema in contrast with ARM resection (OR = 0.27, 95% CI 0.20–0.36, I² = 31%, P = 0.161). Intriguingly, the result favored ALND-ARM over standard-ALND in preventing lymphedema occurrence (OR = 0.21, 95% CI 0.14–0.31, I² = 43%, P = 0.153). The risk of metastases in the ARM-nodes was not significantly lower in the patients who had received neoadjuvant chemotherapy, as compared to those without neoadjuvant treatment (OR = 1.20, 95% CI 0.74–1.94, I² = 49.4%, P = 0.095).ConclusionsARM was found to significantly reduce the incidence of BCRL. The selection of patients for this procedure should be based on their axillary nodal status. Preoperative neoadjuvant chemotherapy has no significant impact on the ARM lymph node metastasis rate.     

Diagnosis of postoperative recurrence of Crohn disease with MR-enterography: Value of diffusion-weighted imaging

PurposeTo compare the diagnostic capabilities of MR enterography (MRE) using contrast-enhanced (CE) sequences with those of MRE using diffusion-weighted (DW) imaging for the diagnosis of postoperative recurrence at the neo-terminal ileum and/or anastomosis after ileocolonic resection in patients with Crohn disease (CD), and to clarify the role of additional DW imaging to CE-MRE in this context.Material and methodsForty patients who underwent ileal resection for CD, and both endoscopy and MRE within the first year after surgery were included. There were 21 men and 19 women, with a mean age of 38 years ± 12 (SD) years (range: 18–67 years). MRE examinations were blindly analyzed independently by one senior (R1) and one junior (R2) radiologist for the presence of small bowel postoperative recurrence at the anastomotic site. During a first reading session, T2-, steady-state- and DW-MRE were reviewed (DW-MRE or set 1). During a separate distant session, T2-, steady-state- and CE-MRE were reviewed (CE-MRE or set 2). Lastly, all sequences were analyzed altogether (set 3). Performances of each reader for the diagnosis of postoperative recurrence were evaluated using endoscopic findings as the standard of reference (Rutgeerts score ≥ i2b).ResultsFifteen patients out of 40 (37.5%) had endoscopic postoperative recurrence at the anastomotic site. Sensitivity for the diagnosis of postoperative recurrence was 73% (95% CI: 51–96%) for R1 and 67% (95% CI: 43–91%) for R2 using set 1, and 80% (95% CI: 60–100%) for both readers using set 2. There was no significant differences in sensitivity between reading set 1 and reading set 2, for either R1 or R2 (R1, P  > 0.99; R2, P = 0.48). Specificity was 96% (95% CI: 88–100%) for both readers using set 1 or using set 2. Reading set 3 yielded an area under the ROC curve (AUC) of 0.93 (95% CI: 0.84–1) versus 0.89 (95% CI: 0.75–1) with set 1 (P = 0.18) and versus 0.89 (95% CI: 0.78–1) with set 2 (P = 0.21). No significant differences in AUC were found between set 1 or 2 and set 3 (P = 0.18), nor between set 1 and 2 (P = 0.76). Accuracies were 88% (95% CI: 74–95%) and 85% (95% CI: 71–93%) for DW-MRE for R1 and R2, respectively; 90% (95% CI: 77–96%) for CE-MRE for both readers; and 93% (95% CI: 80–97%) and 88% (95% CI: 74–95%) for R1 and R2 with set 3, respectively.ConclusionDW-MRE has diagnostic capabilities similar to those of CE-MRE for the diagnosis of postoperative recurrence of CD at the anastomotic site.     

Texture analysis of apparent diffusion coefficient (ADC) map for glioma grading: Analysis of whole tumoral and peri-tumoral tissue

PurposeTo prospectively investigate the capabilities of texture analysis (TA) based on apparent diffusion coefficient (ADC) map of the entire tumor volume and the whole volume of peri-tumoral edema, in discriminating between high-grade glioma (HGG) and low-grade glioma (LGG).Materials and methodsA total of 33 patients with histopathological proven glioma were prospectively included. There were 20 men and 13 women with a mean age of 54.5 ± 14.7 (standard deviation [SD]) years (range: 34–75 years). TA parameters of whole tumor and peri-tumoral edema were extracted from the ADC map obtained with diffusion-weighted spin-echo echo-planar magnetic resonance imaging at 1.5–T. TA variables of HGG were compared to those of LGG. The optimum cut-off values of TA variables and their corresponding sensitivity, specificity and accuracy for differentiating between LGG and HGG were calculated using receiver operating characteristic curve analysis.ResultsMean and median tumoral ADC of HGG were significantly lower than those of LGG, at 1.23 × 10^?3 mm²/s and 1.21 × 10^?3 mm²/s cut-off values, yielding 70% sensitivity each (95% CI: 59–82% and 61–80%, respectively), 80% (95% CI: 79–98%) and 90% (95% CI: 82–97%) specificity, and 73% (95% CI: 66–91%) and 76% (95% CI: 72–90%) accuracy, respectively. Significant differences in tumoral and peri-tumoral kurtosis were found between HGG and LGG at 1.60 and 0.314 cut-off values yielding sensitivities of 74% (95% CI: 58–83%) and 70% (95% CI: 59–84%), specificities of 90% (95% CI: 80–95%) and 70% (95% CI: 64–83%) and accuracies of 79% (95% CI: 69–89%) and 70% (95% CI: 64–77%), respectively.ConclusionMeasurements of whole tumoral and peri-tumoral TA, based on ADC maps, provide useful information that helps distinguish between HGG and LGG.     

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%.     

Arterial endofibrosis in endurance athletes: Prospective comparison of the diagnostic accuracy of intra-arterial digital subtraction angiography and computed tomography angiography

PurposeTo prospectively compare the diagnostic capabilities of computed tomography angiography (CTA) to those of digital subtraction angiography (DSA) in endurance athletes with suspicion of arterial endofibrosis.Materials and methodsForty-five athletes (39 men, 6 women; median age: 30 years, interquartile range: 23–42 years) prospectively underwent DSA and CTA without (n = 5) or with (n = 40) electrocardiogram gating. DSA was interpreted by a single expert (experience of 15 years). CTA was independently interpreted by three other readers (experience of 5–8 years). Readers assessed the presence and degree of stenoses on iliac and femoral arteries and the overall diagnosis (negative, uncertain, positive) of endofibrosis at the limb level. Sensitivities and specificities of DSA and CTA were estimated at the limb level using histological findings and long-term follow-up as reference, and compared using the McNemar test.ResultsFor diagnosing and quantifying stenoses, concordance between DSA and CTA was moderate-to-good for common and external iliac arteries, moderate for lateral circumflex arteries and poor-to-moderate for the other branches of the deep femoral artery. It was good for all readers for the overall diagnosis of endofibrosis. After long-term follow-up (median, 95 months; interquartile range: 7–109 months), DSA sensitivity and specificity were respectively 88.6% (39/44; 95% confidence interval [CI]: 76–95%) and 75% (24/32; 95% CI: 57.9–86.7%); CTA sensitivity and specificity were respectively 88.6% (39/44; 95% CI: 76–95%; P > 0.99) and 84.4% (27/32; 95% CI: 68.2–93.1%; P = 0.51), 86.3% (38/44; 95% CI: 73.3–93.6%; P > 0.99) and 75% (24/32; 95% CI: 57.9–86.7%; P > 0.99), and 84.1% (37/44; 95% CI: 70.6–92.1%; P = 0.68) and 75% (24/32; 95% CI: 57.9–86.7%; P > 0.99) for the three readers.ConclusionCTA shows performances similar to those of DSA in predicting the long-term diagnosis of endofibrosis in endurance athletes with suggestive symptoms.     

MRI-based traditional radiomics and computer-vision nomogram for predicting lymphovascular space invasion in endometrial carcinoma

PurposeTo determine the capabilities of MRI-based traditional radiomics and computer-vision (CV) nomogram for predicting lymphovascular space invasion (LVSI) in patients with endometrial carcinoma (EC).Materials and methodsA total of 184 women (mean age, 52.9 ± 9.0 [SD] years; range, 28–82 years) with EC were retrospectively included. Traditional radiomics features and CV features were extracted from preoperative T2-weighted and dynamic contrast-enhanced MR images. Two models (Model 1, the radiomics model; Model 2, adding CV radiomics signature into the Model 1) were built. The performance of the models was evaluated by the area under the curve (AUC) of the receiver operator characteristic (ROC) in the training and test cohorts. A nomogram based on clinicopathological metrics and radiomics signatures was developed. The predictive performance of the nomogram was assessed by AUC of the ROC in the training and test cohorts.ResultsFor predicting LVSI, the AUC values of Model 1 in the training and test cohorts were 0.79 (95% confidence interval [CI]: 0.702–0.889; accuracy: 65.9%; sensitivity: 88.8%; specificity: 57.8%) and 0.75 (95% CI: 0.585–0.914; accuracy: 69.5%; sensitivity: 85.7%; specificity: 62.5%), respectively. The AUC values of Model 2 in the training and test cohorts were 0.93 (95% CI: 0.875–0.991; accuracy: 94.9%; sensitivity: 91.6%; specificity: 96.0%) and 0.81 (95% CI: 0.666–0.962; accuracy: 71.7%; sensitivity: 92.8%; specificity: 62.5%), respectively. The discriminative ability of Model 2 was significantly improved compared to Model 1 (Net Reclassification Improvement [NRI] = 0.21; P = 0.04). Based on histologic grade, FIGO stage, Rad-score and CV-score, AUC values of the nomogram to predict LVSI in the training and test cohorts were 0.98 (95% CI: 0.955–1; accuracy: 91.6%; sensitivity: 91.6%; specificity: 96.0%) and 0.92 (95% CI: 0.823–1; accuracy: 91.3%; sensitivity: 78.5%; specificity: 96.8%), respectively.ConclusionsMRI-based traditional radiomics and computer-vision nomogram are useful for preoperative risk stratification in patients with EC and may facilitate better clinical decision-making.     

Preoperative assessment of patient comorbidities before left colectomy: Comparison between ASA performance status scale and a new computed tomography physical status score

PurposeTo compare a newly developed preoperative computed tomography physical status (CT-PS) score with the American Society of Anesthesiology performance status (ASA-PS) scale in the assessment of patient preoperative health status and stratification of perioperative risk before left colectomy.Materials and methodsPreoperative chest-abdomen-pelvis CT examinations of patients who were scheduled to undergo elective laparoscopic left colonic resection for cancer in two centers were reviewed by two radiologists blinded to clinical data for the presence of several key imaging features in order to assess general, cardiac, pulmonary, abdominal, renal, vascular and musculoskeletal status. CT examinations of patients from center 1 were used to build a CT-PS score to predict ASA-PS ≥ III. CT-PS score was further validated using an external cohort of patients from center 2.ResultsDuring a 2-year period, 117 consecutive patients (63 men, 54 women; mean age, 65 ± 13 [SD] years; age range: 53–90 years) who underwent laparoscopic left colectomy for cancer in center 1 (66 patients, building cohort) and center 2 (51 patients, validation cohort) were retrospectively included. Ninety-one percent of patients were ASA-PS 1–2. Overall postoperative morbidity was 23% and severe morbidity 12%. The area under the receiver operating characteristic curve of CT-PS score was 0.968 (95% CI: 0.901–1.000) in the building cohort and 0.828 (95% CI: 0.693–0.963) in the validation cohort. The optimal thresholds yielded 87% (95% CI: 83–91%) sensitivity and 100% (95% CI: 91–100%) specificity in the building cohort and 75% (95% CI: 69–81%) sensitivity and 83% (95% CI: 77–88%) specificity in the validation cohort for the prediction of ASA-PS.ConclusionPreoperative chest-abdomen-pelvis CT thoroughly and wisely read is highly accurate to differentiate patients with ASA-PS I/II from those with ASA-PS III/IV before left colectomy.     

Reproducibility of LI-RADS treatment response algorithm for hepatocellular carcinoma after locoregional therapy

PurposeTo determine inter-reader agreement in categorizing hepatocellular carcinoma (HCC) treated with locoregional therapy using the Liver Imaging Reporting and Data System (LI-RADS) treatment response (LR-TR) algorithm.Materials and methodsA total of 93 patients with a total of 112 HCC nodules that were treated using thermal ablation or transarterial chemoembolization were prospectively included. There were 79 men and 14 women with a mean age of 55 ± 2.6 (SD) years (range: 48–63 years). All patients underwent magnetic resonance imaging (MRI) examination of the liver and MR images were analyzed by two independent observers. Treated HCC nodules were categorized into four groups according to LR-TR scoring system including: (i) LR-TR non-evaluable (treated, response not evaluable); (ii) LR-TR nonviable (treated, probably or definitively not viable); (iii) LR-TR equivocal (treated, equivocally viable) and (iv) LR-TR viable (treated, probably or definitively viable). The inter-observer agreement in LR-TR categorization was assessed using the kappa statistics.ResultsThere was excellent inter-observer agreement between the two reviewers for overall treated HCC according to LR-TR algorithm (kappa = 0.938; 95% CI: 0.89–1.00; P = 0.001) with 97.31% agreement. The LR-TR categories by both reviewers were non-viable (77/112; 69.6% and 76/112; 67.9%), viable (30/112; 26.8% and 32/112; 27.7%) and equivocal (5/112; 4.4% and 4/112; 3.6%). There was excellent inter-observer agreement for LR-TR nonviable (kappa = 0.938; 95% CI: 0.87–1.0; P = 0.001) with 97.3% agreement, LR-TR viable (kappa = 0.955; 95% CI: 0.89–1.00; P = 0.001) with 98.2% agreement and good inter-observer agreement for LR-TR equivocal (kappa = 0.700; 95% CI: 0.28–1.0; P = 0.001) with 97.3% agreement.ConclusionLR-TR algorithm conveys high degrees of inter-observer agreement for the evaluation of treatment response of HCC after thermal ablation and transarterial chemoembolization.     

Machine learning-based radiomic computed tomography phenotyping of thymic epithelial tumors: Predicting pathological and survival outcomes

ObjectiveFor patients with thymic epithelial tumors, accurately predicting clinicopathological outcomes remains challenging. We aimed to investigate the performance of machine learning-based radiomic computed tomography phenotyping for predicting pathological (World Health Organization [WHO] type and TNM stage) and survival outcomes (overall and progression-free survival) in patients with thymic epithelial tumors.MethodsThis retrospective study included patients with thymic epithelial tumors between January 2001 and January 2022. The radiomic features were extracted from preoperative unenhanced computed tomography images. After strict feature selection, random forest and random survival forest models were fitted to predict pathological and survival outcomes, respectively. The model performance was assessed by the area under the curve (AUC) and validated internally by the bootstrap method.ResultsIn total, 124 patients with a median age of 61 years were included. The radiomics random forest models of WHO type and TNM stage showed satisfactory performance with an AUC_WHO of 0.898 (95% CI, 0.753-1.000) and an AUC_TNM of 0.766 (95% CI, 0.642-0.886). For overall survival and progression-free survival prediction, the radiomics random survival forest models showed good performance (integrated AUCs, 0.923; 95% CI, 0.691-1.000 and 0.702; 95% CI, 0.513-0.875, respectively), and the integrated AUCs increased to 0.935 (95% CI, 0.705-1.000) and 0.811 (95% CI, 0.647-0.942), respectively, when combined with clinicopathological features.ConclusionsMachine learning-based radiomic computed tomography phenotyping might allow for the satisfactory prediction of pathological and survival outcomes and further improve prognostic performance when integrated with clinicopathological features in patients with thymic epithelial tumors.     

Advanced preoperative three-dimensional planning decreases the surgical complications of using large-for-size grafts in pediatric living donor liver transplantation

BackgroundUsing “large-for-size” liver graft, graft-to-recipient weight ratio (GRWR) ≥4%, has been debated in pediatric liver transplantation due to possible graft compartment after abdomen closure. Meticulous preoperative evaluation with three-dimensional (3D) techniques may prevent these problems. This study compared the safety of large-for-size grafts in pediatric living donor liver transplantation (PLDLT) during the eras with or without 3D planning.MethodsWe defined the 3D era was after November 2017 due to our first implication of 3D printing for surgical planning and subsequently developing a 3D simulation implanting model. From November 2004 to July 2021, we enrolled 30 PLDLT patients with body weight (BW) < 10 kg and categorized them into conventional group: GRWR ≥4% before the 3D era (n = 9), 3D group: GRWR ≥4% in the 3D era (n = 8), and control group: GRWR <4% (n = 13). We followed and compared their clinical outcomes.ResultsThe 3D group had the lowest BW and the highest graft volume reduction rate, with all receiving modified left lateral segments (LLS), such as reduced LLS (n = 2), hyperreduced LLS (n = 5), and segment 2 monosegment (n = 1). Overall postoperative complications were similar in conventional and control groups but significantly lower in the 3D group (OR 0.06, 95% CI 0.006?0.70, p = 0.025). However, all groups had similar graft and patient survival at 1, 2, and 4 years.ConclusionAdvanced preoperative 3D planning can decrease post-transplant complications and increase the safety of large-for-size grafts in PLDLT.Level of EvidenceType of study: Retrospective comparative study; Evidence level: Level III     

Evaluation of efficacy and safety of PARP inhibitors in breast cancer: A systematic review and meta-analysis

BackgroundMany breast cancer clinical trials with PARPi have been completed or are currently carried out, either by monotherapy or combined with chemotherapy. We aim to assess the efficacy and safety of PARPi in breast cancer patients as compared to chemotherapy.MethodsA comprehensive literature search of PubMed, EMBASE, CENTRAL, conference meetings and clinical trial registry was performed. The primary outcomes were progression-free survival (PFS), overall survival (OS), overall response rate (ORR). The secondary outcome was safety profile. The comparative effects were measured using hazard ratio (HR) or relative risk (RR) with 95% confidence interval. Subgroup analyses were conducted based on types of intervention and baseline characteristics of patients.ResultsSix RCTs (n = 1953) were included. Two RCTs were recognized as high risk. PARPi was associated with an improved PFS (HR, 0.65; 95% CI, 0.56–0.74), OS (HR, 0.86; 95% CI, 0.73–1.01), and a higher ORR (RR, 1.38; 95% CI, 1.05–1.82). PARPi, however, significantly increased risk of grade 3–4 thrombocytopenia (RR, 1.63; 95% CI, 1.06–2.52). Monotherapy was observed with lower risk of disease progression and higher ORR rate than combination therapy, 0.56 to 0.65 and 2.21 to 1.05, respectively. For patients without prior platinum treatment, PARPi significantly improved PFS (HR, 0.64; 95% CI, 0.52–0.79).ConclusionsPARPi was observed with a significantly improved efficacy in aspects of PFS and ORR, but also higher risk of grade 3–4 thrombocytopenia as compared to chemotherapy. PARPi was a better choice for patients who had not received previous platinum treatment.     

Bladder endometriosis: Preoperative MRI analysis with assessment of extension to ureteral orifices

PurposeThe purpose of this study was to retrospectively evaluate the performance of magnetic resonance imaging (MRI) in locating endometriosis implants within the bladder wall with assessment of ureteral orifice extension using surgical findings as standard of reference.Materials and methodsMRI examinations of 39 consecutive women (mean age: 31.2 ± 5.5 [SD] years; age range: 22–42 years) operated in 3 university hospitals for bladder endometriosis over a 6-year period were reviewed by 2 independent readers. Interobserver agreement was assessed using Kappa tests. Results of consensus reading were used to calculate sensitivity, specificity and accuracy of MRI for the diagnosis, location and extent of endometriosis implants using surgical findings as the standard of reference.ResultsMean bladder repletion volume was 134 ± 110 [SD] mL (range: 21–479 mL). The mean largest endometriosis implant diameter was 30 ± 7 [SD] mm (range: 19–41 mm). On MR images, 34/39 (87%) endometriosis implants were present in the two anterior thirds of the dome (k = 0.45), 31/39 (79%) extended or were present in the posterior third pouch (k = 0.92) and 25/39 (64%) extended into the bladder base (k = 0.84) with sensitivities of 100% (31/31; 95% confidence interval [CI]: 89–100%), 100% (30/30; 95% CI: 88–100%) and 90% (19/21; 95% CI: 69–98%), respectively, specificities of 83% (5/6, 95% CI: 36–100), 88% (7/8, 95% CI: 47–100%), 87% (13/15; 95% CI: 52–96), respectively and accuracies of 97% (36/37, 95% CI: 86–100%), 97% (37/38; 95% CI: 86–100%), and 89% (32/36; 95% CI: 74–97%), respectively. In 9 (9/25; 36%) patients with bladder base involvement, a zero distance was reported between endometriosis implants and ureteral orifices, all but one presenting with low-to-moderate bladder volumes. In the two patients who needed ureteral resection-reimplantation, ureteral dilation was associated with a zero distance. External adenomyosis was reported in 26/39 (66%) patients (k = 0.94).ConclusionA dedicated preoperative MRI work-up for bladder endometriosis helps accurately depict and locate endometriosis implants. Adequate bladder filling is needed to improve appropriate estimate of the distance between endometriosis implants and ureteral orifices to better predict requirement of ureteral resection-reimplantation.     

Prediction of overall survival in patients with hepatocellular carcinoma treated with Y-90 radioembolization by imaging response criteria

PurposeTo evaluate the potential of imaging criteria in predicting overall survival of patients with hepatocellular carcinoma (HCC) after a first transcatheter arterial yttrium-90 radioembolization (TARE)Materials and methodsFrom October 2013 to July 2017, 37 patients with HCC were retrospectively included. There were 34 men and 3 women with a mean age of 60.5 ± 10.2 (SD) years (range: 32.7–78.9 years). Twenty-five patients (68%) were Barcelona Clinic Liver Cancer (BCLC) C and 12 (32%) were BCLC B. Twenty-four primary index tumors (65%) were > 5 cm. Three radiologists evaluated tumor response on pre- and 4–7 months post-TARE magnetic resonance imaging or computed tomography examinations, using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, modified RECIST (mRECIST), European Association for Study of the Liver (EASL), volumetric RECIST (vRECIST), quantitative EASL (qEASL) and the Liver Imaging Reporting and Data System treatment response algorithm. Kaplan–Meier survival curves were used to compare responders and non-responders for each criterion. Univariate and multivariate Cox proportional hazard ratio (HR) analysis were used to identify covariates associated with overall survival. Fleiss kappa test was used to assess interobserver agreement.ResultsAt multivariate analysis, RECIST 1.1 (HR: 0.26; 95% confidence interval [95% CI]: 0.09–0.75; P = 0.01), mRECIST (HR: 0.22; 95% CI: 0.08–0.59; P = 0.003), EASL (HR: 0.22; 95% CI: 0.07–0.63; P = 0.005), and qEASL (HR: 0.30; 95% CI: 0.12–0.80; P = 0.02) showed a significant difference in overall survival between responders and nonresponders. RECIST 1.1 had the highest interobserver reproducibility.ConclusionRECIST and mRECIST seem to be the best compromise between reproducibility and ability to predict overall survival in patients with HCC treated with TARE.     

Discriminating between benign and malignant salivary gland tumors using diffusion-weighted imaging and intravoxel incoherent motion at 3 Tesla

PurposeThe purpose of this study was to retrospectively evaluate the diagnostic performances of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for discriminating between benign and malignant salivary gland tumors (SGTs).Materials and methodsSixty-seven patients with 71 SGTs who underwent MRI examination at 3 Tesla were included. There were 34 men and 37 women with a mean age of 57 ± 17 (SD) years (age range: 20–90 years). SGTs included 21 malignant tumors (MTs) and 50 benign SGTs (33 pleomorphic adenomas [PAs] and 17 Warthin's tumors [WTs]). For each SGT, DWI and IVIM parameters, mean, skewness, and kurtosis of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion volume fraction (f) were calculated and further compared between SGTs using univariable analysis. Areas under the curves (AUC) of receiver operating characteristic of significant parameters were compared using the Delong test.ResultsSignificant differences in ADC_mean, D_mean and D*_mean were found between SGTs (P < 0.001). The highest AUC values were obtained for ADC_mean (0.949) for identifying PAs and D*_mean (0.985) for identifying WTs and skewness and kurtosis did not outperform mean. To discriminate benign from malignant SGTs with thresholds set to maximize Youden index, IVIM and DWI produced accuracies of 85.9% (61/71; 95% CI: 75.6–93.0) and 77.5% (55/71; 95% CI: 66.0–86.5) but misdiagnosed MTs as benign in 28.6% (6/21) and 61.9% (13/21) of SGTs, respectively. After maximizing specificity to 100% for benign SGTs, the accuracies of IVIM and DWI decreased to 76.1% (54/71; 95% CI: 64.5–85.4) and 64.8% (46/71; 95% CI: 52.5–75.8) but no MTs were misdiagnosed as benign. IVIM and DWI correctly diagnosed 66.0% (33/50) and 50.0% (25/50) of benign SGTs and 46.5% (33/71) and 35.2% (25/71) of all SGTs, respectively.ConclusionIVIM is more accurate than DWI for discriminating between benign and malignant SGTs because of its advantage in detecting WTs. Thresholds set by maximizing specificity for benign SGTs may be advantageous in a clinical setting.     

Single breath-hold compressed sensing real-time cine imaging to assess left ventricular motion in myocardial infarction

PurposeTo evaluate the reliability of a real-time compressed sensing (CS) cine sequence for the detection of left ventricular wall motion disorders after myocardial infarction in comparison with the reference steady-state free precession cine sequence.Materials and MethodsOne hundred consecutive adult patients referred for either initial work-up or follow-up by cardiac magnetic resonance (CMR) in the context of myocardial infarction were prospectively included. There were 77 men and 23 women with a mean age of 63.12 ± 11.3 (SD) years (range: 29–89 years). Each patient underwent the reference segmented multi-breath-hold steady-state free precession cine sequence including one short-axis stack and both vertical and horizontal long-axis slices (SSFP_ref) and the CS real-time single-breath-hold evaluated sequence (CS_rt) providing the same slices. Wall motion disorders were independently and blindly assessed with both sequences by two radiologists, using the American Heart Association left ventricle segmentation. Paired Wilcoxon signed-rank test was used to search for differences in wall motion disorders conspicuity between both sequences and receiver operating characteristic curve (ROC) analysis was performed to assess the diagnosis performance of CS_rt sequence using SSFP_ref as the reference method.ResultsEach patient had at least one cardiac segment with wall motion abnormality on SSFP_ref and CS_rt images. The 1700 segments analyzed with SSFP_ref were classified as normokinetic (360/1700; 21.2%), hypokinetic (783/1700; 46.1%), akinetic (526/1700; 30.9%) or dyskinetic (31/1700; 1.8%). Sensitivity and specificity of the CS sequence were 99.6% (95% CI: 99.1–99.9%) and 99.7% (95% CI: 98.5–100%), respectively. Area under ROC of CS_rt diagnosis performance was 0.997 (95% CI: 0.993–0.999).ConclusionCS real-time cine imaging significantly reduces acquisition time without compromising the conspicuity of left ventricular -wall motion disorders in the context of myocardial infarction.     

Survival outcomes of breast cancer patients with brain metastases: A multicenter retrospective study in Korea (KROG 16–12)

PurposeThis study evaluated the influence of prognostic factors and whole brain radiotherapy (WBRT) on overall survival (OS) of breast cancer (BC) patients with brain metastases (BM).Methods and materialsMedical records of 730 BC patients diagnosed with BM from 2000 to 2014 at 17 institutions were retrospectively reviewed. OS was calculated from BM diagnosis. Median follow-up duration was 11.9 months (range, 0.1–126.2).ResultsMedian OS was 15.0 months (95% CI: 14.0–16.9). Patients with different BC-specific graded prognostic assessment (GPA) scores showed significant differences (p < 0.001) in OS. In multivariate analysis, histologic grade 3 (p = 0.014), presence of extracranial metastasis (p < 0.001), the number of BM (>4; p = 0.002), hormone receptor negativity (p = 0.005), HER2-negativity (p = 0.003), and shorter time interval (<30 months) between BC and BM diagnosis (p = 0.007) were associated with inferior OS. By summing the β-coefficients of variables that were prognostic in multivariate analyses, we developed a prognostic model that stratified patients into low-risk (≤0.673) and high-risk (>0.673) subgroups; the high-risk subgroup had poorer median OS (10.1 months, 95% CI: 7.9–11.9 vs. 21.9 months, 95% CI: 19.5–27.1, p < 0.001). Univariate and multivariate analyses of propensity score-matched patients diagnosed with BM ≥ 30 months after BC diagnosis (n = 389, “late BM”) revealed that WBRT-treated patients showed superior OS compared to non-WBRT-treated patients (p = 0.070 and 0.030, respectively).ConclusionOur prognostic model identified high-risk BC patients with BM who might benefit from increased surveillance; if validated, our model could guide treatment selection for such patients. Patients with late BM might benefit from WBRT as initial local treatment.     

The impact of liver resection on survival for patients with metastatic breast cancer – A systematic review and meta-analysis

IntroductionThere is uncertainty surrounding the role of resection as an option for curative treatment of breast cancer with liver metastases (BCLM).AimTo perform a systematic review and meta-analysis evaluating the role of liver resection for BCLM.MethodsA systematic review was performed as per PRISMA guidelines. Hazard ratio (HR) for overall survival (OS) and standard error was obtained from each study and expressed using the generic inverse variance method, with a corresponding 95% confidence interval (CI). OS outcomes at 1- 3- and 5-years were expressed as dichotomous variables and pooled as odds ratios (OR) using the Mantel-Haenszel method.ResultsNine studies with 1732 patients were included. Of these, 24.5% underwent surgical resection of BCLM (424/1732) and 75.5% did not (1308/1732). Overall, OS was significantly better among those who underwent surgery versus controls (HR: 0.69, 95% CI: 0.59–0.80, P < 0.00001). Mortality rates were significantly reduced at 1-year (7.5% (10/134) vs 20.3% (79/390), OR: 0.25, 95% CI: 0.08–0.74, P = 0.010) and 5-years (54.0% (190/352) vs 75.3% (940/1249), OR: 0.46, 95% CI: 0.25–0.87, P = 0.020) respectively for those undergoing surgery versus controls. Mortality rates at 3 years after surgery were lower than the control group (19.1% (29/152) vs 53.0% (222/419)), however this failed to achieve statistical significance at meta-analysis (OR: 0.32, 95% CI: 0.09–1.12, P = 0.070).ConclusionLiver resection may be considered at multidisciplinary meetings for those with BCLM and offers a potentially curative option. However, judicious patient selection is crucial prior to making decisions in relation to resection of BCLM.     

Body mass index and early outcomes following mitral valve surgery for degenerative disease

ObjectiveUsing a large national database, we sought to better define the relationship between obesity measures and early clinical outcomes following mitral valve surgery for degenerative disease.MethodsFor the outcomes of in-hospital mortality, postoperative cerebrovascular event (CVA), and deep sternal wound infection (DSWI), a retrospective cohort study was performed using data acquired from the United Kingdom National Adult Cardiac Surgery Audit. Multivariable Cox proportional hazard regression modeling was used to investigate associations with individual measures of obesity. Progressively adjusted body mass index (BMI)-specific hazard ratios (HRs) were plotted against mean BMI values in each World Health Organization category using floated variances to investigate specific shapes of association.ResultsMultivariable Cox proportional hazard modeling failed to demonstrate an association between mortality and an increase in BMI of 5 points (HR, 0.93, 95% confidence interval [CI], 0.81-1.07), a BMI quintile increase (HR, 0.98; 95% CI, 0.90-1.07), or being classed “obese” by World Health Organization standards (HR, 1.03; 95% CI, 0.74-1.42). A 5-point BMI increase was associated with an increased hazard of DSWI (HR, 1.38; 95% CI, 1.08-1.77) but was not associated with perioperative CVA (HR, 1.05; 95% CI, 0.91-1.21). The shape of association between BMI and mortality appeared approximately U-shaped. DSWI appeared linear, whereas CVA demonstrated an inverted U, or a possible hourglass.ConclusionsAlthough individual measures of obesity were not associated with an increased mortality risk on regression modeling, the U-shaped relationship between mortality and increasing BMI demonstrates lower mortality risks in lower obesity classes. Increasing BMI was associated with an increased hazard for DSWI.