多发性骨髓瘤患者胸部CT第4胸椎平面人体成分与预后的关联性分析

doi:10.13481/j.1671-587X.20240424

Abstract

Abstract:

Objective To automatically segment four body components at the T4 thoracic veertebra plane on chest CT in the newly diagnosed multiple myeloma （MM） patients by deep learning model， and to discuss the correlation between the four body components and the prognosis of the MM patients. Methods The retrospective analysis was conducted on the clinical data of the MM patients diagnosed in our hospital from January 2017 to December 2021. The clinical informations such as age， gender， weight， height， and body mass index （BMI） of the patients were collected. The laboratory data of the patients were collected， including serum levels of lactate dehydrogenase （LDH）， calcium （Ca）， creatinine （Scr）， albumin （Alb）， hemoglobin （Hb）， β2-microglobulin （β2-MG）， and serum free light chains. The chest CT images of 79 regularly evaluated MM patients detected by deep learning model were divide into four body components： pectoralis major， pectoralis minor， subcutaneous fat， and mediastinal fat. Image J software was used to detect the areas of the four body components at the T4 thoracic vertebra plane， and their correlation with the prognosis of the MM patients was analyzed by Kaplan-Meier survival analysis. Results The univariate analysis results showed that the area of subcutaneous fat， serum Ca levels， Scr levels， and International Staging System （ISS） stage were related to the overall survival （OS） of the MM patients （HR=2.260， 95% CI： 1.116-4.578， P=0.024； HR=2.088， 95% CI： 1.007-4.327， P=0.048； HR=2.209， 95% CI： 1.105-4.414， P=0.025； HR=1.730， 95% CI： 1.040-2.879， P=0.035）. The multivariate analysis results showed that the area of subcutaneous fat among the four body components was an independent risk factor affecting the prognosis of the MM patients （95% CI： 1.228-5.782， P=0.013）. The Log-Rank test results showed that compared with high subcutaneous fat area group， the OS of the patients in low subcutaneous fat area group was decreased（P=0.018）. There was no significant difference in OS of the patients with different genders between high subcutaneous fat area group and low subcutaneous fat area group （P>0.05）. In the patients without hematopoietic stem cell transplantation， compared with high subcutaneous fat area group， the OS of the patients in low subcutaneous fat area group was decreased （P=0.037）. Conclusion Among the four body components at the T4 thoracic vertebra plane， the area of subcutaneous fat is related to the OS of the MM patients and it is an independent risk factor for the prognosis of the MM patients， while the areas of mediastinal fat， pectoralis major， and pectoralis minor have no predictive value for the prognosis of the MM patients.

Key words: Multiple myeloma, Computed tomography, Body composition, Deep learning model

CLC Number:

R733.3

Xue BAI,Chenchen WANG,Zhangzhen SHI,Lintao BI. Analysis on correlation between body components at T4 thoracic vertebra plane on chest CT in patients with multiple myeloma and prognosis[J].Journal of Jilin University(Medicine Edition), 2024, 50(4): 1098-1108.

Figures/Tables 7

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Tab. 6

Fig. 1

References 21

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Characteristic	Statistic
Age (year) Gender [n(%)] Male Female	61.5±8.7 37（46.8） 42（53.2）
BMI（kg·m^-2）	22.6±3.8
BMI≥24 kg·m^-2 [n(%)]	23（29.1）
Subcutaneous adipose area(pixel²)	5 377(3 000, 8 763)
Mediastinal adipose area(pixel²)	277（138, 443）
Pectoralis major area(pixel²)	547（235, 973）
Pectoralis minor area(pixel²)	299（167, 476）
LDH（U·L^-1）	174.1（138.5, 215.3）
LDH≥247 U·L^-1 [n(%)]	13（16.5）
Hb（g·L^-1）	94.6±31.4
Hb≤100 g·L^-1 [n(%)]	50（63.3）
Ca（mmol·L^-1）	2.43（2.20, 2.60）
Ca>2.65 mmol·L^-1 [n(%)]	18（22.8）
Scr（μmol·L^-1）	96.1（66.4, 214.1）
Scr≥177 μmol·L^-1 [n(%)]	22（27.8）
Alb（g·L^-1）	34.0±7.5
Alb<35 g·L^-1 [n(%)]	43（54.4）
β2-MG（mg·L^-1）	5.0（3.3，7.8）
β2-MG≥5.5 mg·L^-1 [n(%)]	38（48.1）
Involved/uninvolved light chain≥100 [n(%)]	17（21.5）
ISS stage [n(%)]
1	14（17.7）
2	28（35.4）
3	31（39.2）
Treatment method[n(%)]
Chemotherapy	71（89.9）
Hematopoietic stem cell transplantation	8（10.1）
Survive[n(%)]
Yes	34（43.0）
No	45（57.0）
Median follow-up time (month)	22（5-73）

Characteristic	HR	95%CI	P
Gender	0.958	0.483－1.900	0.902
Male Female
Age of diagnosis	1.023	0.983－1.064	0.259
BMI（kg·m^-2）	1.675	0.756－3.711	0.204
≥24 <24
Subcutaneous adipose area(pixel²)	2.260	1.116－4.578	0.024
≥5 377 <5 377
Mediastinal adipose area(pixel²)	1.001	0.999－1.002	0.339
≥277 <277
Pectoralis major area(pixel²)	0.965	0.487－1.912	0.918
≥547 <547
Pectoralis minor area(pixel²)	0.981	0.495－1.946	0.957
≥299 <299
LDH（U·L^-1）	1.235	0.474－3.216	0.665
<247 ≥247
Hb（g·L^-1）	1.278	0.629－2.596	0.498
>100 ≤100
Ca（mmol·L^-1）	2.088	1.007－4.327	0.048
≤2.65 >2.65
Scr（μmol·L^-1）	2.209	1.105－4.414	0.025
<177 ≥177
Alb（g·L^-1）	1.461	0.730－2.926	0.284
≥35 <35
β2-MG（mg·L^-1）	1.858	0.928－3.721	0.080
<5.5 ≥5.5
Involved/uninvolved light chain[n(%)]	1.588	0.758－3.327	0.220
<100 ≥100
ISS stage	1.730	1.040－2.879	0.035
Treatment method	0.042	0.000－8.089	0.237
Chemotherapy Hematopoietic stem cell transplantation

Variable	Model 1		Model 2		Model 3
Variable	95%CI of HR	P	95%CI of HR	P	95%CI of HR	P
Subcutaneous adipose area(pixel²)	1.200－7.064	0.018	1.503－8.129	0.004	1.228－5.782	0.013
≥5 377
<5 377
BMI（kg·m^-2）	0.713－5.317	0.193	－	－	－	－
≥24
<24
Gender	0.350－2.193	0.778	－	－	－	－
Male
Female
Age of diagnosis	0.988－1.107	0.124	－	－	－	－
Hb（g·L^-1）	0.204－2.254	0.527	0.191－1.630	0.286	－	－
>100
≤100
LDH（U·L^-1）	0.496－5.681	0.405	0.419－4.152	0.636	0.526－4.437	0.436
<247
≥247
Ca（mmol·L^-1）	0.878－5.172	0.094	0.803－4.163	0.151	0.969－4.398	0.060
≤2.65
>2.65
Scr（μmol·L^-1）	0.566－6.669	0.291	0.372－3.330	0.847	－	－
<177
≥177
Alb（g·L^-1）	1.245－11.163	0.019	1.072－9.200	0.037	0.924－5.131	0.075
≥35
<35
β2-MG（mg·L^-1）	0.384－26.681	0.282	0.209－7.466	0.808	0.549－2.536	0.673
<5.5
≥5.5
Involved/uninvolved light chain	0.385－2.703	0.969	0.545－3.470	0.500	－	－
<100
≥100
ISS	0.075－1.932	0.244	0.340－3.672	0.855	－	－
Treatment method	－	0.973	－	－	－	－
Chemotherapy
Hematopoietic stem cell transplantation

Variable	Model 1		Model 2		Model 3
Variable	95%CI of HR	P	95%CI of HR	P	95%CI of HR	P
Mediastinal adipose area(pixel²)	0.551-3.152	0.536	1.503-8.129	0.589	0.523-2.201	0.847
≥277
<277
BMI（kg·m^-2）	0.959-7.149	0.060	-	-	-	-
≥24
<24
Gender	0.308-1.936	0.582	-	-	-	-
Male
Female
Age of diagnosis	0.983-1.099	0.178	-	-	-	-
Hb（g·L^-1）	0.212-2.673	0.660	0.191-1.630	0.364	-	-
>100
≤100
LDH（U·L^-1）	0.390-4.198	0.684	0.419-4.152	0.994	0.437-3.593	0.674
<247
≥247
Ca（mmol·L^-1）	0.758-4.230	0.184	0.803-4.163	0.284	0.933-4.167	0.076
≤2.65
>2.65
Scr（μmol· L^-1）	0.806-10.448	0.103	0.372-3.330	0.318	-	-
<177
≥177
Alb（g· L^-1）	0.988-8.086	0.053	1.072-9.200	0.364	0.643-3.150	0.384
≥35
<35
β2-MG（mg·L^-1）	0.288-15.360	0.464	0.209-7.466	0.846	0.719-3.252	0.270
<5.5
≥5.5
Involved/uninvolved light chain	0.315-2.256	0.734	0.545-3.470	0.915	-	-
<100
≥100
ISS stage	0.102-2.052	0.307	0.340-3.672	0.756	-	-
Treatment method	-	0.974	-	-	-	-
Chemotherapy
Hematopoietic stem cell transplantation

Variable	Model 1		Model 2		Model 3
Variable	95%CI of HR	P	95%CI of HR	P	95%CI of HR	P
Pectoralis major area(pixel²)	0.513-3.561	0.542	0.545-2.582	0.666	0.489-1.970	0.957
≥547
<547
BMI（kg·m^-2）	0.972-8.749	0.056	-	-	-	-
≥24
<24
Gender	0.224-2.031	0.483	-	-	-	-
Male
Female
Age of diagnosis	0.979-1.094	0.220	-	-	-	-
Hb（g·L^-1）	0.220-2.165	0.486	0.178-1.645	0.280	-	-
>100
≤100
LDH（U·L^-1）	0.414-4.718	0.590	0.324-3.219	0.972	0.437-3.584	0.676
<247
≥247
Ca（mmol·L^-1）	0.758-4.214	0.184	0.721-3.492	0.251	0.942-4.188	0.071
≤2.65
>2.65
Scr（μmol·L^-1）	0.813-9.625	0.103	0.568-5.369	0.331	-	-
<177
≥177
Alb（g·L^-1）	0.977-7.527	0.056	0.732-5.703	0.172	0.647-3.021	0.395
≥35
<35
β2-MG（mg·L^-1）	0.334-20.016	0.363	0.229-7.582	0.757	0.704-3.262	0.288
<5.5
≥5.5
Involved/uninvolved light chain	0.308-2.107	0.660	0.400-2.483	0.995	-	-
<100
≥100
ISS stage	0.088-2.030	0.281	0.368-3.774	0.781	-	-
Treatment method	-	0.974	-	-	-	-
Chemotherapy
Hematopoietic stem cell transplantation

Analysis on correlation between body components at T4 thoracic vertebra plane on chest CT in patients with multiple myeloma and prognosis

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